diff --git a/dev/.buildinfo b/dev/.buildinfo
index 94ab366c..aa05b14c 100644
--- a/dev/.buildinfo
+++ b/dev/.buildinfo
@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 80ca7f735dfcccb8968a28ca7e645b35
+config: b0e1d99bae3f0f1cd9fb9e9fbf7e56ee
 tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip b/dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip
index dd674069..ceb17ab9 100644
Binary files a/dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip and b/dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip differ
diff --git a/dev/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip b/dev/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip
index 65605b3a..0ef00652 100644
Binary files a/dev/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip and b/dev/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip differ
diff --git a/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_cropped_001.png b/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_cropped_001.png
index 22e4f949..847e337f 100644
Binary files a/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_cropped_001.png and b/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_cropped_001.png differ
diff --git a/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_cropped_thumb.png b/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_cropped_thumb.png
index 0cfb720d..f3399973 100644
Binary files a/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_cropped_thumb.png and b/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_cropped_thumb.png differ
diff --git a/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_trial_001.png b/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_trial_001.png
index 682bfd3b..4b34ddcd 100644
Binary files a/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_trial_001.png and b/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_trial_001.png differ
diff --git a/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_trial_thumb.png b/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_trial_thumb.png
index 5753c73d..ae0d7b74 100644
Binary files a/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_trial_thumb.png and b/dev/_images/sphx_glr_plot_bcic_iv_2a_moabb_trial_thumb.png differ
diff --git a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_001.png b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_001.png
index f2037cb1..196e957d 100644
Binary files a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_001.png and b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_001.png differ
diff --git a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png
index a0b9b599..3eddb48f 100644
Binary files a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png and b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png differ
diff --git a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_thumb.png b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_thumb.png
index 192f00fe..a79e0352 100644
Binary files a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_thumb.png and b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_thumb.png differ
diff --git a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_001.png b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_001.png
index 458bd98f..0272e20d 100644
Binary files a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_001.png and b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_001.png differ
diff --git a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_002.png b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_002.png
index 45f09c3b..4af829a0 100644
Binary files a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_002.png and b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_002.png differ
diff --git a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_thumb.png b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_thumb.png
index 168d8e5a..72018620 100644
Binary files a/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_thumb.png and b/dev/_images/sphx_glr_plot_bcic_iv_4_ecog_trial_thumb.png differ
diff --git a/dev/_images/sphx_glr_plot_benchmark_preprocessing_001.png b/dev/_images/sphx_glr_plot_benchmark_preprocessing_001.png
index feae43a6..18bcd97d 100644
Binary files a/dev/_images/sphx_glr_plot_benchmark_preprocessing_001.png and b/dev/_images/sphx_glr_plot_benchmark_preprocessing_001.png differ
diff --git a/dev/_images/sphx_glr_plot_benchmark_preprocessing_thumb.png b/dev/_images/sphx_glr_plot_benchmark_preprocessing_thumb.png
index d49f840e..017d0aa0 100644
Binary files a/dev/_images/sphx_glr_plot_benchmark_preprocessing_thumb.png and b/dev/_images/sphx_glr_plot_benchmark_preprocessing_thumb.png differ
diff --git a/dev/_images/sphx_glr_plot_regression_001.png b/dev/_images/sphx_glr_plot_regression_001.png
index 67ee02ff..8d34d856 100644
Binary files a/dev/_images/sphx_glr_plot_regression_001.png and b/dev/_images/sphx_glr_plot_regression_001.png differ
diff --git a/dev/_images/sphx_glr_plot_regression_002.png b/dev/_images/sphx_glr_plot_regression_002.png
index 242c9b9c..ed3438c6 100644
Binary files a/dev/_images/sphx_glr_plot_regression_002.png and b/dev/_images/sphx_glr_plot_regression_002.png differ
diff --git a/dev/_images/sphx_glr_plot_regression_thumb.png b/dev/_images/sphx_glr_plot_regression_thumb.png
index 9fdad5f1..66b2bb32 100644
Binary files a/dev/_images/sphx_glr_plot_regression_thumb.png and b/dev/_images/sphx_glr_plot_regression_thumb.png differ
diff --git a/dev/_images/sphx_glr_plot_relative_positioning_001.png b/dev/_images/sphx_glr_plot_relative_positioning_001.png
index d54fda79..2b6dba3e 100644
Binary files a/dev/_images/sphx_glr_plot_relative_positioning_001.png and b/dev/_images/sphx_glr_plot_relative_positioning_001.png differ
diff --git a/dev/_images/sphx_glr_plot_relative_positioning_002.png b/dev/_images/sphx_glr_plot_relative_positioning_002.png
index de5dd899..a296f7e2 100644
Binary files a/dev/_images/sphx_glr_plot_relative_positioning_002.png and b/dev/_images/sphx_glr_plot_relative_positioning_002.png differ
diff --git a/dev/_images/sphx_glr_plot_relative_positioning_thumb.png b/dev/_images/sphx_glr_plot_relative_positioning_thumb.png
index becd4f92..66c7d68c 100644
Binary files a/dev/_images/sphx_glr_plot_relative_positioning_thumb.png and b/dev/_images/sphx_glr_plot_relative_positioning_thumb.png differ
diff --git a/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_001.png b/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_001.png
index b1731b27..48340a7a 100644
Binary files a/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_001.png and b/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_001.png differ
diff --git a/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_002.png b/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_002.png
index 1f13b307..07a9efa4 100644
Binary files a/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_002.png and b/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_002.png differ
diff --git a/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_003.png b/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_003.png
index 7e098785..1d15f9c7 100644
Binary files a/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_003.png and b/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_003.png differ
diff --git a/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_thumb.png b/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_thumb.png
index 24bf539c..6850440a 100644
Binary files a/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_thumb.png and b/dev/_images/sphx_glr_plot_sleep_staging_chambon2018_thumb.png differ
diff --git a/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_001.png b/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_001.png
index 1fb1da6f..2a3724ad 100644
Binary files a/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_001.png and b/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_001.png differ
diff --git a/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_thumb.png b/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_thumb.png
index 7d05661f..6897dd40 100644
Binary files a/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_thumb.png and b/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_thumb.png differ
diff --git a/dev/_images/sphx_glr_plot_sleep_staging_usleep_001.png b/dev/_images/sphx_glr_plot_sleep_staging_usleep_001.png
index 8fbae197..c758e3f8 100644
Binary files a/dev/_images/sphx_glr_plot_sleep_staging_usleep_001.png and b/dev/_images/sphx_glr_plot_sleep_staging_usleep_001.png differ
diff --git a/dev/_images/sphx_glr_plot_sleep_staging_usleep_thumb.png b/dev/_images/sphx_glr_plot_sleep_staging_usleep_thumb.png
index c690bff4..bc1405f7 100644
Binary files a/dev/_images/sphx_glr_plot_sleep_staging_usleep_thumb.png and b/dev/_images/sphx_glr_plot_sleep_staging_usleep_thumb.png differ
diff --git a/dev/_static/documentation_options.js b/dev/_static/documentation_options.js
index d40ea2b7..6f9016d3 100644
--- a/dev/_static/documentation_options.js
+++ b/dev/_static/documentation_options.js
@@ -1,5 +1,5 @@
 const DOCUMENTATION_OPTIONS = {
-    VERSION: '0.8',
+    VERSION: '0.8.1',
     LANGUAGE: 'en',
     COLLAPSE_INDEX: false,
     BUILDER: 'html',
diff --git a/dev/api.html b/dev/api.html
index 289c9253..ffc4adf1 100644
--- a/dev/api.html
+++ b/dev/api.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>API Reference &#8212; Braindecode 0.8 documentation</title>
+    <title>API Reference &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="_static/documentation_options.js?v=cc929139"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/auto_examples/advanced_training/index.html b/dev/auto_examples/advanced_training/index.html
index c4dac0c2..ca3425b3 100644
--- a/dev/auto_examples/advanced_training/index.html
+++ b/dev/auto_examples/advanced_training/index.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Advanced neural network training strategies &#8212; Braindecode 0.8 documentation</title>
+    <title>Advanced neural network training strategies &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/auto_examples/advanced_training/plot_bcic_iv_4_ecog_cropped.html b/dev/auto_examples/advanced_training/plot_bcic_iv_4_ecog_cropped.html
index 8a270cd0..07b70555 100644
--- a/dev/auto_examples/advanced_training/plot_bcic_iv_4_ecog_cropped.html
+++ b/dev/auto_examples/advanced_training/plot_bcic_iv_4_ecog_cropped.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset &#8212; Braindecode 0.8 documentation</title>
+    <title>Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -598,7 +598,7 @@ <h3>Preprocessing<a class="headerlink" href="#preprocessing" title="Link to this
 <a href="../../generated/braindecode.preprocessing.preprocess.html#braindecode.preprocessing.preprocess" title="braindecode.preprocessing.preprocess" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-function"><span class="n">preprocess</span></a><span class="p">(</span><a href="../../generated/braindecode.datasets.BaseConcatDataset.html#braindecode.datasets.BaseConcatDataset" title="braindecode.datasets.BaseConcatDataset" class="sphx-glr-backref-module-braindecode-datasets sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">test_set</span></a><span class="p">,</span> <span class="p">[</span><a href="../../generated/braindecode.preprocessing.Preprocessor.html#braindecode.preprocessing.Preprocessor" title="braindecode.preprocessing.Preprocessor" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-class"><span class="n">Preprocessor</span></a><span class="p">(</span><span class="s1">&#39;crop&#39;</span><span class="p">,</span> <span class="n">tmin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">tmax</span><span class="o">=</span><span class="mi">24</span><span class="p">)],</span> <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8149c400&gt;
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f3131378130&gt;
 </pre></div>
 </div>
 <p>In time series targets setup, targets variables are stored in mne.Raw object as channels
@@ -823,14 +823,14 @@ <h2>Training<a class="headerlink" href="#training" title="Link to this heading">
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    r2_train    r2_valid    train_loss    valid_loss      lr     dur
 -------  ----------  ----------  ------------  ------------  ------  ------
-      1    -16.9036     -8.3098        2.5378       20.7346  0.0006  1.0870
-      2    -13.7536     -7.1257        1.9596       18.0738  0.0006  0.5969
-      3    -12.7771     -6.7413        1.6787       17.1884  0.0005  0.5724
-      4    -11.7976     -6.3917        1.5638       16.4413  0.0004  0.6026
-      5    -11.2720     -6.1845        1.4237       16.0095  0.0002  0.6533
-      6    -10.5744     -5.9208        1.3549       15.4433  0.0001  0.5924
-      7     -9.8236     -5.6185        1.3132       14.7797  0.0000  0.6048
-      8     -9.0650     -5.3051        1.3316       14.0882  0.0000  0.6093
+      1    -16.9037     -8.3086        2.5378       20.7324  0.0006  0.5038
+      2    -13.7539     -7.1244        1.9596       18.0720  0.0006  0.4052
+      3    -12.7768     -6.7402        1.6787       17.1870  0.0005  0.4036
+      4    -11.7970     -6.3910        1.5638       16.4409  0.0004  0.4095
+      5    -11.2712     -6.1840        1.4237       16.0095  0.0002  0.4032
+      6    -10.5735     -5.9203        1.3549       15.4436  0.0001  0.4052
+      7     -9.8228     -5.6181        1.3132       14.7799  0.0000  0.4031
+      8     -9.0643     -5.3047        1.3316       14.0884  0.0000  0.4024
 </pre></div>
 </div>
 <p>Obtaining predictions and targets for the test, train, and validation dataset</p>
@@ -940,8 +940,8 @@ <h2>Plot Results<a class="headerlink" href="#plot-results" title="Link to this h
 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.tight_layout.html#matplotlib.pyplot.tight_layout" title="matplotlib.pyplot.tight_layout" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span></a><span class="p">()</span>
 </pre></div>
 </div>
-<img src="../../_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png" srcset="../../_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png" alt="plot bcic iv 4 ecog cropped" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 55.097 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  810 MB</p>
+<img src="../../_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png" srcset="../../_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png" alt="plot bcic iv 4 ecog cropped" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (2 minutes 41.420 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  777 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-advanced-training-plot-bcic-iv-4-ecog-cropped-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/c494db8fb7ce5921127c670340744634/plot_bcic_iv_4_ecog_cropped.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_bcic_iv_4_ecog_cropped.py</span></code></a></p>
diff --git a/dev/auto_examples/advanced_training/plot_data_augmentation.html b/dev/auto_examples/advanced_training/plot_data_augmentation.html
index 41a89c6b..0c0edae0 100644
--- a/dev/auto_examples/advanced_training/plot_data_augmentation.html
+++ b/dev/auto_examples/advanced_training/plot_data_augmentation.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Data Augmentation on BCIC IV 2a Dataset &#8212; Braindecode 0.8 documentation</title>
+    <title>Data Augmentation on BCIC IV 2a Dataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -589,7 +589,7 @@ <h3><a class="toc-backref" href="#id3" role="doc-backlink">Preprocessing</a><a c
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f4b71698940&gt;
+&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f3131301330&gt;
 </pre></div>
 </div>
 </section>
@@ -784,10 +784,10 @@ <h3><a class="toc-backref" href="#id10" role="doc-backlink">Create an EEGClassif
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2500        1.6077       0.2500            0.2500        3.0178  0.0006  2.7489
-      2            0.2569        1.3809       0.2569            0.2569        2.1896  0.0005  2.3996
-      3            0.3021        1.2767       0.2569            0.2569        1.7959  0.0002  2.3702
-      4            0.3229        1.1763       0.2674            0.2674        1.6416  0.0000  2.3995
+      1            0.2500        1.6077       0.2500            0.2500        3.0179  0.0006  1.7346
+      2            0.2569        1.3809       0.2569            0.2569        2.1898  0.0005  1.5458
+      3            0.3021        1.2767       0.2604            0.2604        1.7960  0.0002  1.5160
+      4            0.3229        1.1763       0.2674            0.2674        1.6417  0.0000  1.5309
 
 &lt;class &#39;braindecode.classifier.EEGClassifier&#39;&gt;[initialized](
   module_=============================================================================================================================================
@@ -841,8 +841,8 @@ <h3><a class="toc-backref" href="#id12" role="doc-backlink">Setting the data aug
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><a href="../../generated/braindecode.datasets.BaseConcatDataset.html#braindecode.datasets.BaseConcatDataset" title="braindecode.datasets.BaseConcatDataset" class="sphx-glr-backref-module-braindecode-datasets sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">train_set</span></a><span class="o">.</span><a href="../../generated/braindecode.augmentation.FrequencyShift.html#braindecode.augmentation.FrequencyShift" title="braindecode.augmentation.FrequencyShift" class="sphx-glr-backref-module-braindecode-augmentation sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">transform</span></a> <span class="o">=</span> <a href="../../generated/braindecode.augmentation.Compose.html#braindecode.augmentation.Compose" title="braindecode.augmentation.Compose" class="sphx-glr-backref-module-braindecode-augmentation sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">composed_transforms</span></a>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 21.750 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  468 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 16.183 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  518 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-advanced-training-plot-data-augmentation-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/e3845395de44913c970dbf26671a7cba/plot_data_augmentation.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_data_augmentation.py</span></code></a></p>
diff --git a/dev/auto_examples/advanced_training/plot_data_augmentation_search.html b/dev/auto_examples/advanced_training/plot_data_augmentation_search.html
index 073878ea..bd9d3f45 100644
--- a/dev/auto_examples/advanced_training/plot_data_augmentation_search.html
+++ b/dev/auto_examples/advanced_training/plot_data_augmentation_search.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Searching the best data augmentation on BCIC IV 2a Dataset &#8212; Braindecode 0.8 documentation</title>
+    <title>Searching the best data augmentation on BCIC IV 2a Dataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -610,7 +610,7 @@ <h3><a class="toc-backref" href="#id10" role="doc-backlink">Preprocessing</a><a
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f4b714d6410&gt;
+&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f3131677cd0&gt;
 </pre></div>
 </div>
 </section>
@@ -960,8 +960,8 @@ <h3><a class="toc-backref" href="#id19" role="doc-backlink">References</a><a cla
 Journal of Neural Engineering, 18(4), 046020.</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 51.725 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  106 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 31.663 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  503 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-advanced-training-plot-data-augmentation-search-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/0f763ae384277e558103757157e170fb/plot_data_augmentation_search.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_data_augmentation_search.py</span></code></a></p>
diff --git a/dev/auto_examples/advanced_training/plot_relative_positioning.html b/dev/auto_examples/advanced_training/plot_relative_positioning.html
index 35cfff75..2d2739dc 100644
--- a/dev/auto_examples/advanced_training/plot_relative_positioning.html
+++ b/dev/auto_examples/advanced_training/plot_relative_positioning.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Self-supervised learning on EEG with relative positioning &#8212; Braindecode 0.8 documentation</title>
+    <title>Self-supervised learning on EEG with relative positioning &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -604,7 +604,7 @@ <h3><a class="toc-backref" href="#id21" role="doc-backlink">Preprocessing</a><a
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.sleep_physionet.SleepPhysionet object at 0x7f4b71698670&gt;
+&lt;braindecode.datasets.sleep_physionet.SleepPhysionet object at 0x7f313047dd80&gt;
 </pre></div>
 </div>
 </section>
@@ -646,7 +646,7 @@ <h3><a class="toc-backref" href="#id23" role="doc-backlink">Preprocessing window
 <a href="../../generated/braindecode.preprocessing.preprocess.html#braindecode.preprocessing.preprocess" title="braindecode.preprocessing.preprocess" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-function"><span class="n">preprocess</span></a><span class="p">(</span><a href="../../generated/braindecode.datasets.BaseConcatDataset.html#braindecode.datasets.BaseConcatDataset" title="braindecode.datasets.BaseConcatDataset" class="sphx-glr-backref-module-braindecode-datasets sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">windows_dataset</span></a><span class="p">,</span> <span class="p">[</span><a href="../../generated/braindecode.preprocessing.Preprocessor.html#braindecode.preprocessing.Preprocessor" title="braindecode.preprocessing.Preprocessor" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-class"><span class="n">Preprocessor</span></a><span class="p">(</span><a href="https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html#sklearn.preprocessing.scale" title="sklearn.preprocessing.scale" class="sphx-glr-backref-module-sklearn-preprocessing sphx-glr-backref-type-py-function"><span class="n">standard_scale</span></a><span class="p">,</span> <span class="n">channel_wise</span><span class="o">=</span><span class="kc">True</span><span class="p">)])</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b6393bc40&gt;
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f31313c03d0&gt;
 </pre></div>
 </div>
 </section>
@@ -867,31 +867,31 @@ <h2><a class="toc-backref" href="#id27" role="doc-backlink">Training</a><a class
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_acc    train_loss    valid_acc    valid_loss    cp     dur
 -------  -----------  ------------  -----------  ------------  ----  ------
-      1       0.5234        0.7013       0.6680        0.6320     +  1.5210
-      2       0.5938        0.7149       0.4880        0.8357        1.2055
-      3       0.4922        1.0039       0.6440        0.6172     +  1.1741
-      4       0.5234        0.7031       0.6120        0.5988     +  1.1792
-      5       0.5391        0.6751       0.5920        0.6208        1.1589
-      6       0.6719        0.6235       0.5840        0.6256        1.1662
-      7       0.6641        0.6315       0.6200        0.6109        1.1501
-      8       0.6562        0.6261       0.6480        0.5934     +  1.1736
-      9       0.6484        0.6235       0.6720        0.5778     +  1.1405
-     10       0.6562        0.6161       0.6920        0.5739     +  1.1579
-     11       0.6172        0.6322       0.7000        0.5788        1.1569
-     12       0.6172        0.6260       0.6840        0.5776        1.1694
-     13       0.6328        0.6427       0.6880        0.5794        1.1691
-     14       0.6562        0.5923       0.6800        0.5763        1.1791
-     15       0.6484        0.6193       0.6760        0.5727     +  1.1568
-     16       0.7344        0.5650       0.6760        0.5677     +  1.1645
-     17       0.7031        0.5943       0.7000        0.5627     +  1.1551
-     18       0.7578        0.5444       0.6960        0.5535     +  1.1598
-     19       0.7812        0.5250       0.7120        0.5440     +  1.1485
-     20       0.6641        0.5657       0.7160        0.5369     +  1.1501
-     21       0.7422        0.5285       0.7280        0.5309     +  1.1529
-     22       0.6797        0.5494       0.7200        0.5262     +  1.1672
-     23       0.6328        0.6264       0.7240        0.5229     +  1.1711
-     24       0.7031        0.5611       0.7120        0.5210     +  1.1790
-     25       0.7031        0.5018       0.7280        0.5204     +  1.1591
+      1       0.5234        0.7013       0.6680        0.6320     +  1.1660
+      2       0.5938        0.7149       0.4880        0.8358        0.8803
+      3       0.4922        1.0040       0.6440        0.6172     +  0.8777
+      4       0.5234        0.7031       0.6120        0.5990     +  0.8684
+      5       0.5391        0.6751       0.5920        0.6213        0.8710
+      6       0.6719        0.6227       0.5920        0.6263        0.8768
+      7       0.6562        0.6309       0.6240        0.6117        0.8771
+      8       0.6641        0.6272       0.6480        0.5950     +  0.8705
+      9       0.6328        0.6238       0.6680        0.5797     +  0.8819
+     10       0.6406        0.6177       0.6800        0.5746     +  0.9290
+     11       0.6250        0.6323       0.7040        0.5787        0.8672
+     12       0.6094        0.6281       0.6760        0.5772        0.8615
+     13       0.6328        0.6422       0.6880        0.5790        0.8652
+     14       0.6406        0.5920       0.6840        0.5765        0.8659
+     15       0.6562        0.6170       0.6920        0.5730     +  0.8657
+     16       0.7578        0.5608       0.6960        0.5676     +  0.8648
+     17       0.6875        0.5936       0.7120        0.5612     +  0.8691
+     18       0.7734        0.5472       0.7080        0.5500     +  0.8600
+     19       0.7656        0.5245       0.7120        0.5400     +  0.8745
+     20       0.6641        0.5641       0.7160        0.5333     +  0.8807
+     21       0.7422        0.5307       0.7200        0.5272     +  0.8768
+     22       0.7109        0.5499       0.7360        0.5211     +  0.8677
+     23       0.6250        0.6259       0.7400        0.5164     +  0.8719
+     24       0.7031        0.5712       0.7400        0.5120     +  0.8672
+     25       0.7109        0.5030       0.7280        0.5120        0.8638
 </pre></div>
 </div>
 </section>
@@ -950,16 +950,16 @@ <h3><a class="toc-backref" href="#id29" role="doc-backlink">Inspecting pretext t
 <span class="nb">print</span><span class="p">(</span><a href="https://scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html#sklearn.metrics.classification_report" title="sklearn.metrics.classification_report" class="sphx-glr-backref-module-sklearn-metrics sphx-glr-backref-type-py-function"><span class="n">classification_report</span></a><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y_true</span></a><span class="p">,</span> <a href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="torch.Tensor" class="sphx-glr-backref-module-torch sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y_pred</span></a><span class="p">))</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[89 32]
- [42 87]]
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[90 31]
+ [41 88]]
               precision    recall  f1-score   support
 
-         0.0       0.68      0.74      0.71       121
-         1.0       0.73      0.67      0.70       129
+         0.0       0.69      0.74      0.71       121
+         1.0       0.74      0.68      0.71       129
 
-    accuracy                           0.70       250
-   macro avg       0.71      0.70      0.70       250
-weighted avg       0.71      0.70      0.70       250
+    accuracy                           0.71       250
+   macro avg       0.71      0.71      0.71       250
+weighted avg       0.71      0.71      0.71       250
 </pre></div>
 </div>
 </section>
@@ -1019,26 +1019,26 @@ <h3><a class="toc-backref" href="#id30" role="doc-backlink">Using the learned re
     https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
   n_iter_i = _check_optimize_result(
 Sleep staging performance with logistic regression:
-Train bal acc: 0.8877
-Valid bal acc: 0.5425
-Test bal acc: 0.6449
+Train bal acc: 0.8924
+Valid bal acc: 0.5215
+Test bal acc: 0.6011
 Results on test set:
-[[110  23   2   5   2]
- [  8  74   9   2  16]
- [ 28  52 416   3  63]
- [  0   0  53  52   0]
- [  0  60  19   0  91]]
+[[107  26   3   4   2]
+ [  7  75   9   2  16]
+ [ 70  60 350   2  80]
+ [  0   0  55  50   0]
+ [  0  77  14   0  79]]
               precision    recall  f1-score   support
 
-           0       0.75      0.77      0.76       142
-           1       0.35      0.68      0.47       109
-           2       0.83      0.74      0.78       562
-           3       0.84      0.50      0.62       105
-           4       0.53      0.54      0.53       170
+           0       0.58      0.75      0.66       142
+           1       0.32      0.69      0.43       109
+           2       0.81      0.62      0.70       562
+           3       0.86      0.48      0.61       105
+           4       0.45      0.46      0.46       170
 
-    accuracy                           0.68      1088
-   macro avg       0.66      0.64      0.63      1088
-weighted avg       0.73      0.68      0.69      1088
+    accuracy                           0.61      1088
+   macro avg       0.60      0.60      0.57      1088
+weighted avg       0.68      0.61      0.62      1088
 </pre></div>
 </div>
 <p>The balanced accuracy is much higher than chance-level (i.e., 20% for our
@@ -1066,7 +1066,7 @@ <h3><a class="toc-backref" href="#id30" role="doc-backlink">Using the learned re
 <img src="../../_images/sphx_glr_plot_relative_positioning_002.png" srcset="../../_images/sphx_glr_plot_relative_positioning_002.png" alt="plot relative positioning" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/examples/advanced_training/plot_relative_positioning.py:472: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed two minor releases later. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap(obj)`` instead.
   colors = cm.get_cmap(&#39;viridis&#39;, 5)(range(5))
 
-&lt;matplotlib.legend.Legend object at 0x7f4b815150f0&gt;
+&lt;matplotlib.legend.Legend object at 0x7f312debfd60&gt;
 </pre></div>
 </div>
 <p>We see that there is sleep stage-related structure in the embedding. A
@@ -1123,8 +1123,8 @@ <h2><a class="toc-backref" href="#id32" role="doc-backlink">References</a><a cla
 (758-769)</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 33.898 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  228 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 20.215 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  165 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-advanced-training-plot-relative-positioning-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/bc6f7fe8a7751868a4ff60828f6634e5/plot_relative_positioning.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_relative_positioning.py</span></code></a></p>
diff --git a/dev/auto_examples/advanced_training/sg_execution_times.html b/dev/auto_examples/advanced_training/sg_execution_times.html
index b96fa202..b07f8399 100644
--- a/dev/auto_examples/advanced_training/sg_execution_times.html
+++ b/dev/auto_examples/advanced_training/sg_execution_times.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Computation times &#8212; Braindecode 0.8 documentation</title>
+    <title>Computation times &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -444,24 +444,24 @@
   
   <section id="computation-times">
 <span id="sphx-glr-auto-examples-advanced-training-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">#</a></h1>
-<p><strong>04:42.470</strong> total execution time for <strong>auto_examples_advanced_training</strong> files:</p>
+<p><strong>04:49.481</strong> total execution time for <strong>auto_examples_advanced_training</strong> files:</p>
 <table class="table">
 <tbody>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_bcic_iv_4_ecog_cropped.html#sphx-glr-auto-examples-advanced-training-plot-bcic-iv-4-ecog-cropped-py"><span class="std std-ref">Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_bcic_iv_4_ecog_cropped.py</span></code>)</p></td>
-<td><p>01:55.097</p></td>
-<td><p>810.1 MB</p></td>
+<td><p>02:41.420</p></td>
+<td><p>777.5 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_relative_positioning.html#sphx-glr-auto-examples-advanced-training-plot-relative-positioning-py"><span class="std std-ref">Self-supervised learning on EEG with relative positioning</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_relative_positioning.py</span></code>)</p></td>
-<td><p>01:33.898</p></td>
-<td><p>228.0 MB</p></td>
+<td><p>01:20.215</p></td>
+<td><p>164.6 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_data_augmentation_search.html#sphx-glr-auto-examples-advanced-training-plot-data-augmentation-search-py"><span class="std std-ref">Searching the best data augmentation on BCIC IV 2a Dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_data_augmentation_search.py</span></code>)</p></td>
-<td><p>00:51.725</p></td>
-<td><p>106.0 MB</p></td>
+<td><p>00:31.663</p></td>
+<td><p>502.8 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_data_augmentation.html#sphx-glr-auto-examples-advanced-training-plot-data-augmentation-py"><span class="std std-ref">Data Augmentation on BCIC IV 2a Dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_data_augmentation.py</span></code>)</p></td>
-<td><p>00:21.750</p></td>
-<td><p>468.1 MB</p></td>
+<td><p>00:16.183</p></td>
+<td><p>517.8 MB</p></td>
 </tr>
 </tbody>
 </table>
diff --git a/dev/auto_examples/applied_examples/index.html b/dev/auto_examples/applied_examples/index.html
index ba1f4d20..993b61df 100644
--- a/dev/auto_examples/applied_examples/index.html
+++ b/dev/auto_examples/applied_examples/index.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Applied examples on real-world datasets &#8212; Braindecode 0.8 documentation</title>
+    <title>Applied examples on real-world datasets &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/auto_examples/applied_examples/plot_bcic_iv_4_ecog_trial.html b/dev/auto_examples/applied_examples/plot_bcic_iv_4_ecog_trial.html
index 8464a9c9..bb675fbd 100644
--- a/dev/auto_examples/applied_examples/plot_bcic_iv_4_ecog_trial.html
+++ b/dev/auto_examples/applied_examples/plot_bcic_iv_4_ecog_trial.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Fingers flexion decoding on BCIC IV 4 ECoG Dataset &#8212; Braindecode 0.8 documentation</title>
+    <title>Fingers flexion decoding on BCIC IV 4 ECoG Dataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -579,7 +579,7 @@ <h3>Preprocessing<a class="headerlink" href="#preprocessing" title="Link to this
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><a href="../../generated/braindecode.preprocessing.preprocess.html#braindecode.preprocessing.preprocess" title="braindecode.preprocessing.preprocess" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-function"><span class="n">preprocess</span></a><span class="p">(</span><a href="../../generated/braindecode.datasets.BCICompetitionIVDataset4.html#braindecode.datasets.BCICompetitionIVDataset4" title="braindecode.datasets.BCICompetitionIVDataset4" class="sphx-glr-backref-module-braindecode-datasets sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">dataset</span></a><span class="p">,</span> <span class="p">[</span><a href="../../generated/braindecode.preprocessing.Preprocessor.html#braindecode.preprocessing.Preprocessor" title="braindecode.preprocessing.Preprocessor" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-class"><span class="n">Preprocessor</span></a><span class="p">(</span><span class="s1">&#39;crop&#39;</span><span class="p">,</span> <span class="n">tmin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">tmax</span><span class="o">=</span><span class="mi">30</span><span class="p">)])</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.bcicomp.BCICompetitionIVDataset4 object at 0x7f4b83924dc0&gt;
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.bcicomp.BCICompetitionIVDataset4 object at 0x7f3130e1ceb0&gt;
 </pre></div>
 </div>
 <p>In time series targets setup, targets variables are stored in mne.Raw object as channels
@@ -774,8 +774,8 @@ <h2>Training<a class="headerlink" href="#training" title="Link to this heading">
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_loss    train_pearson_r    train_r2    valid_loss    valid_pearson_r    valid_r2      lr     dur
 -------  ------------  -----------------  ----------  ------------  -----------------  ----------  ------  ------
-      1        2.5083             0.1251     -0.5570        5.7348            -0.1511     -1.6144  0.0006  9.3855
-      2        1.7986             0.3712     -0.3153        5.2587            -0.1511     -1.3973  0.0000  9.1306
+      1        2.5083             0.1251     -0.5570        5.7337            -0.1507     -1.6139  0.0006  6.3240
+      2        1.7986             0.3712     -0.3153        5.2582            -0.1510     -1.3971  0.0000  6.1032
 </pre></div>
 </div>
 <p>Obtaining predictions and targets for the test, train, and validation dataset</p>
@@ -871,8 +871,8 @@ <h2>Plot Results<a class="headerlink" href="#plot-results" title="Link to this h
 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.tight_layout.html#matplotlib.pyplot.tight_layout" title="matplotlib.pyplot.tight_layout" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span></a><span class="p">()</span>
 </pre></div>
 </div>
-<img src="../../_images/sphx_glr_plot_bcic_iv_4_ecog_trial_002.png" srcset="../../_images/sphx_glr_plot_bcic_iv_4_ecog_trial_002.png" alt="plot bcic iv 4 ecog trial" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 38.083 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  214 MB</p>
+<img src="../../_images/sphx_glr_plot_bcic_iv_4_ecog_trial_002.png" srcset="../../_images/sphx_glr_plot_bcic_iv_4_ecog_trial_002.png" alt="plot bcic iv 4 ecog trial" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 25.154 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  112 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-applied-examples-plot-bcic-iv-4-ecog-trial-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/8fb57f368d675b800d7860057478d781/plot_bcic_iv_4_ecog_trial.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_bcic_iv_4_ecog_trial.py</span></code></a></p>
diff --git a/dev/auto_examples/applied_examples/plot_sleep_staging_chambon2018.html b/dev/auto_examples/applied_examples/plot_sleep_staging_chambon2018.html
index 11fe41ed..c9a2dc63 100644
--- a/dev/auto_examples/applied_examples/plot_sleep_staging_chambon2018.html
+++ b/dev/auto_examples/applied_examples/plot_sleep_staging_chambon2018.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Sleep staging on the Sleep Physionet dataset using Chambon2018 network &#8212; Braindecode 0.8 documentation</title>
+    <title>Sleep staging on the Sleep Physionet dataset using Chambon2018 network &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -557,7 +557,7 @@ <h3>Preprocessing<a class="headerlink" href="#preprocessing" title="Link to this
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.sleep_physionet.SleepPhysionet object at 0x7f4b834ab8e0&gt;
+&lt;braindecode.datasets.sleep_physionet.SleepPhysionet object at 0x7f3130f17040&gt;
 </pre></div>
 </div>
 </section>
@@ -600,7 +600,7 @@ <h3>Window preprocessing<a class="headerlink" href="#window-preprocessing" title
 <a href="../../generated/braindecode.preprocessing.preprocess.html#braindecode.preprocessing.preprocess" title="braindecode.preprocessing.preprocess" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-function"><span class="n">preprocess</span></a><span class="p">(</span><a href="../../generated/braindecode.datasets.BaseConcatDataset.html#braindecode.datasets.BaseConcatDataset" title="braindecode.datasets.BaseConcatDataset" class="sphx-glr-backref-module-braindecode-datasets sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">windows_dataset</span></a><span class="p">,</span> <span class="p">[</span><a href="../../generated/braindecode.preprocessing.Preprocessor.html#braindecode.preprocessing.Preprocessor" title="braindecode.preprocessing.Preprocessor" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-class"><span class="n">Preprocessor</span></a><span class="p">(</span><a href="https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html#sklearn.preprocessing.scale" title="sklearn.preprocessing.scale" class="sphx-glr-backref-module-sklearn-preprocessing sphx-glr-backref-type-py-function"><span class="n">standard_scale</span></a><span class="p">,</span> <span class="n">channel_wise</span><span class="o">=</span><span class="kc">True</span><span class="p">)])</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b836e9cc0&gt;
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f3130e808b0&gt;
 </pre></div>
 </div>
 </section>
@@ -777,16 +777,16 @@ <h2>Training<a class="headerlink" href="#training" title="Link to this heading">
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_bal_acc    train_loss    valid_acc    valid_bal_acc    valid_loss     dur
 -------  ---------------  ------------  -----------  ---------------  ------------  ------
-      1           0.2136        1.5768       0.0888           0.2000        1.6372  2.0938
-      2           0.2036        1.4788       0.0888           0.2000        1.6676  1.9176
-      3           0.2324        1.4033       0.0966           0.2102        1.6337  1.9441
-      4           0.2888        1.3407       0.1149           0.2465        1.6790  1.8773
-      5           0.3993        1.2126       0.4517           0.4013        1.6235  3.4104
-      6           0.5294        1.0967       0.2768           0.4076        1.6179  1.8842
-      7           0.5755        0.9662       0.5927           0.5671        1.3686  1.9107
-      8           0.6251        0.8905       0.7076           0.5786        1.2948  1.9392
-      9           0.6877        0.8148       0.7154           0.5876        1.3442  1.9546
-     10           0.6995        0.7434       0.5274           0.5296        1.6187  1.9716
+      1           0.2136        1.5768       0.0888           0.2000        1.6372  1.6288
+      2           0.2036        1.4788       0.0888           0.2000        1.6676  1.5263
+      3           0.2324        1.4033       0.0966           0.2102        1.6337  1.4958
+      4           0.2888        1.3407       0.1149           0.2465        1.6790  1.4974
+      5           0.3993        1.2126       0.4517           0.4013        1.6235  1.5035
+      6           0.5294        1.0967       0.2768           0.4076        1.6179  1.4931
+      7           0.5755        0.9662       0.5927           0.5671        1.3689  1.5038
+      8           0.6251        0.8904       0.7076           0.5786        1.2952  1.5046
+      9           0.6877        0.8148       0.7154           0.5876        1.3450  1.4988
+     10           0.6860        0.7449       0.5196           0.5269        1.6322  1.5106
 
 &lt;class &#39;braindecode.classifier.EEGClassifier&#39;&gt;[initialized](
   module_=Sequential(
@@ -856,13 +856,13 @@ <h2>Plot results<a class="headerlink" href="#plot-results" title="Link to this h
 
            0       0.14      0.33      0.20        61
            1       0.19      0.14      0.16        21
-           2       0.57      0.35      0.43       194
+           2       0.56      0.34      0.42       194
            3       0.26      0.27      0.26        75
            4       0.03      0.03      0.03        32
 
-    accuracy                           0.29       383
-   macro avg       0.24      0.22      0.22       383
-weighted avg       0.38      0.29      0.32       383
+    accuracy                           0.28       383
+   macro avg       0.24      0.22      0.21       383
+weighted avg       0.37      0.28      0.31       383
 </pre></div>
 </div>
 <p>Finally, we can also visualize the hypnogram of the recording we used for
@@ -920,8 +920,8 @@ <h2>References<a class="headerlink" href="#references" title="Link to this headi
 Circulation 101(23):e215-e220</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (2 minutes 15.335 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  11 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (2 minutes 0.622 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  9 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-applied-examples-plot-sleep-staging-chambon2018-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/d1f211cc350870be312e474c12c8cbcc/plot_sleep_staging_chambon2018.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_sleep_staging_chambon2018.py</span></code></a></p>
diff --git a/dev/auto_examples/applied_examples/plot_sleep_staging_eldele2021.html b/dev/auto_examples/applied_examples/plot_sleep_staging_eldele2021.html
index 2d3d2823..fa53b2ae 100644
--- a/dev/auto_examples/applied_examples/plot_sleep_staging_eldele2021.html
+++ b/dev/auto_examples/applied_examples/plot_sleep_staging_eldele2021.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Sleep staging on the Sleep Physionet dataset using Eldele2021 &#8212; Braindecode 0.8 documentation</title>
+    <title>Sleep staging on the Sleep Physionet dataset using Eldele2021 &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -558,7 +558,7 @@ <h3>Preprocessing<a class="headerlink" href="#preprocessing" title="Link to this
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.sleep_physionet.SleepPhysionet object at 0x7f4b61778850&gt;
+&lt;braindecode.datasets.sleep_physionet.SleepPhysionet object at 0x7f311d82ad70&gt;
 </pre></div>
 </div>
 </section>
@@ -608,7 +608,7 @@ <h3>Window preprocessing<a class="headerlink" href="#window-preprocessing" title
 <a href="../../generated/braindecode.preprocessing.preprocess.html#braindecode.preprocessing.preprocess" title="braindecode.preprocessing.preprocess" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-function"><span class="n">preprocess</span></a><span class="p">(</span><a href="../../generated/braindecode.datasets.BaseConcatDataset.html#braindecode.datasets.BaseConcatDataset" title="braindecode.datasets.BaseConcatDataset" class="sphx-glr-backref-module-braindecode-datasets sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">windows_dataset</span></a><span class="p">,</span> <span class="p">[</span><a href="../../generated/braindecode.preprocessing.Preprocessor.html#braindecode.preprocessing.Preprocessor" title="braindecode.preprocessing.Preprocessor" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-class"><span class="n">Preprocessor</span></a><span class="p">(</span><a href="https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html#sklearn.preprocessing.scale" title="sklearn.preprocessing.scale" class="sphx-glr-backref-module-sklearn-preprocessing sphx-glr-backref-type-py-function"><span class="n">standard_scale</span></a><span class="p">,</span> <span class="n">channel_wise</span><span class="o">=</span><span class="kc">True</span><span class="p">)])</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b83820b80&gt;
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f311dd5d7b0&gt;
 </pre></div>
 </div>
 </section>
@@ -773,9 +773,9 @@ <h2>Training<a class="headerlink" href="#training" title="Link to this heading">
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_bal_acc    train_loss    valid_acc    valid_bal_acc    valid_loss     dur
 -------  ---------------  ------------  -----------  ---------------  ------------  ------
-      1           0.1471        3.1814       0.3459           0.1795        3.4752  2.3149
-      2           0.2712        1.8820       0.1955           0.2186        2.1581  1.8598
-      3           0.4518        1.4974       0.2256           0.2200        4.2246  1.8489
+      1           0.1471        3.1815       0.3459           0.1795        3.4748  2.2672
+      2           0.2712        1.8805       0.1955           0.2186        2.1537  1.9725
+      3           0.4550        1.4941       0.2256           0.2200        4.2159  1.9764
 
 &lt;class &#39;braindecode.classifier.EEGClassifier&#39;&gt;[initialized](
   module_=Sequential(
@@ -1017,8 +1017,8 @@ <h2>References<a class="headerlink" href="#references" title="Link to this headi
 Circulation 101(23):e215-e220</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 14.708 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  15 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 12.868 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  11 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-applied-examples-plot-sleep-staging-eldele2021-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/1f2407fc0459906c808c847bdcd84ccf/plot_sleep_staging_eldele2021.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_sleep_staging_eldele2021.py</span></code></a></p>
diff --git a/dev/auto_examples/applied_examples/plot_sleep_staging_usleep.html b/dev/auto_examples/applied_examples/plot_sleep_staging_usleep.html
index 6d6d2666..e396c0b7 100644
--- a/dev/auto_examples/applied_examples/plot_sleep_staging_usleep.html
+++ b/dev/auto_examples/applied_examples/plot_sleep_staging_usleep.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Sleep staging on the Sleep Physionet dataset using U-Sleep network &#8212; Braindecode 0.8 documentation</title>
+    <title>Sleep staging on the Sleep Physionet dataset using U-Sleep network &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -563,7 +563,7 @@ <h3>Preprocessing<a class="headerlink" href="#preprocessing" title="Link to this
 <a href="../../generated/braindecode.preprocessing.preprocess.html#braindecode.preprocessing.preprocess" title="braindecode.preprocessing.preprocess" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-function"><span class="n">preprocess</span></a><span class="p">(</span><a href="../../generated/braindecode.datasets.SleepPhysionet.html#braindecode.datasets.SleepPhysionet" title="braindecode.datasets.SleepPhysionet" class="sphx-glr-backref-module-braindecode-datasets sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">dataset</span></a><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">preprocessors</span></a><span class="p">)</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.sleep_physionet.SleepPhysionet object at 0x7f4b837f3fa0&gt;
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.sleep_physionet.SleepPhysionet object at 0x7f3130017cd0&gt;
 </pre></div>
 </div>
 </section>
@@ -762,9 +762,9 @@ <h2>Training<a class="headerlink" href="#training" title="Link to this heading">
   return F.conv1d(input, weight, bias, self.stride,
   epoch    train_bal_acc    train_loss    valid_bal_acc    valid_loss     dur
 -------  ---------------  ------------  ---------------  ------------  ------
-      1           0.2040        1.6129           0.1707        1.5807  3.2757
-      2           0.2224        1.5430           0.1594        1.5866  2.6061
-      3           0.3464        1.4928           0.1853        1.6026  2.6227
+      1           0.2040        1.6129           0.1707        1.5807  2.1839
+      2           0.2224        1.5430           0.1594        1.5866  1.7164
+      3           0.3464        1.4928           0.1853        1.6026  1.7267
 
 &lt;class &#39;braindecode.classifier.EEGClassifier&#39;&gt;[initialized](
   module_=======================================================================================================================================================
@@ -973,8 +973,8 @@ <h2>References<a class="headerlink" href="#references" title="Link to this headi
 Circulation 101(23):e215-e220</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 16.129 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  111 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 11.166 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  78 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-applied-examples-plot-sleep-staging-usleep-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/ce2c92ca74396ce848a69d8dcddef743/plot_sleep_staging_usleep.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_sleep_staging_usleep.py</span></code></a></p>
diff --git a/dev/auto_examples/applied_examples/plot_tuh_eeg_corpus.html b/dev/auto_examples/applied_examples/plot_tuh_eeg_corpus.html
index c4847835..43aed40c 100644
--- a/dev/auto_examples/applied_examples/plot_tuh_eeg_corpus.html
+++ b/dev/auto_examples/applied_examples/plot_tuh_eeg_corpus.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Process a big data EEG resource (TUH EEG Corpus) &#8212; Braindecode 0.8 documentation</title>
+    <title>Process a big data EEG resource (TUH EEG Corpus) &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -802,7 +802,7 @@ <h3><a class="toc-backref" href="#id5" role="doc-backlink">Cut Compute Windows</
 <span class="p">)</span>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 7.988 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 6.988 seconds)</p>
 <p><strong>Estimated memory usage:</strong>  10 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-applied-examples-plot-tuh-eeg-corpus-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
diff --git a/dev/auto_examples/applied_examples/sg_execution_times.html b/dev/auto_examples/applied_examples/sg_execution_times.html
index 3b933db8..c8f8d1e7 100644
--- a/dev/auto_examples/applied_examples/sg_execution_times.html
+++ b/dev/auto_examples/applied_examples/sg_execution_times.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Computation times &#8212; Braindecode 0.8 documentation</title>
+    <title>Computation times &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -444,28 +444,28 @@
   
   <section id="computation-times">
 <span id="sphx-glr-auto-examples-applied-examples-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">#</a></h1>
-<p><strong>03:32.242</strong> total execution time for <strong>auto_examples_applied_examples</strong> files:</p>
+<p><strong>02:56.799</strong> total execution time for <strong>auto_examples_applied_examples</strong> files:</p>
 <table class="table">
 <tbody>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_sleep_staging_chambon2018.html#sphx-glr-auto-examples-applied-examples-plot-sleep-staging-chambon2018-py"><span class="std std-ref">Sleep staging on the Sleep Physionet dataset using Chambon2018 network</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_sleep_staging_chambon2018.py</span></code>)</p></td>
-<td><p>02:15.335</p></td>
-<td><p>10.8 MB</p></td>
+<td><p>02:00.622</p></td>
+<td><p>9.4 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_bcic_iv_4_ecog_trial.html#sphx-glr-auto-examples-applied-examples-plot-bcic-iv-4-ecog-trial-py"><span class="std std-ref">Fingers flexion decoding on BCIC IV 4 ECoG Dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_bcic_iv_4_ecog_trial.py</span></code>)</p></td>
-<td><p>00:38.083</p></td>
-<td><p>214.0 MB</p></td>
+<td><p>00:25.154</p></td>
+<td><p>111.7 MB</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="plot_sleep_staging_usleep.html#sphx-glr-auto-examples-applied-examples-plot-sleep-staging-usleep-py"><span class="std std-ref">Sleep staging on the Sleep Physionet dataset using U-Sleep network</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_sleep_staging_usleep.py</span></code>)</p></td>
-<td><p>00:16.129</p></td>
-<td><p>110.8 MB</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="plot_sleep_staging_eldele2021.html#sphx-glr-auto-examples-applied-examples-plot-sleep-staging-eldele2021-py"><span class="std std-ref">Sleep staging on the Sleep Physionet dataset using Eldele2021</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_sleep_staging_eldele2021.py</span></code>)</p></td>
+<td><p>00:12.868</p></td>
+<td><p>11.2 MB</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="plot_sleep_staging_eldele2021.html#sphx-glr-auto-examples-applied-examples-plot-sleep-staging-eldele2021-py"><span class="std std-ref">Sleep staging on the Sleep Physionet dataset using Eldele2021</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_sleep_staging_eldele2021.py</span></code>)</p></td>
-<td><p>00:14.708</p></td>
-<td><p>14.8 MB</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="plot_sleep_staging_usleep.html#sphx-glr-auto-examples-applied-examples-plot-sleep-staging-usleep-py"><span class="std std-ref">Sleep staging on the Sleep Physionet dataset using U-Sleep network</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_sleep_staging_usleep.py</span></code>)</p></td>
+<td><p>00:11.166</p></td>
+<td><p>77.7 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_tuh_eeg_corpus.html#sphx-glr-auto-examples-applied-examples-plot-tuh-eeg-corpus-py"><span class="std std-ref">Process a big data EEG resource (TUH EEG Corpus)</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_tuh_eeg_corpus.py</span></code>)</p></td>
-<td><p>00:07.988</p></td>
-<td><p>9.8 MB</p></td>
+<td><p>00:06.988</p></td>
+<td><p>9.5 MB</p></td>
 </tr>
 </tbody>
 </table>
diff --git a/dev/auto_examples/datasets_io/benchmark_lazy_eager_loading.html b/dev/auto_examples/datasets_io/benchmark_lazy_eager_loading.html
index 93927422..62deec3a 100644
--- a/dev/auto_examples/datasets_io/benchmark_lazy_eager_loading.html
+++ b/dev/auto_examples/datasets_io/benchmark_lazy_eager_loading.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Benchmarking eager and lazy loading &#8212; Braindecode 0.8 documentation</title>
+    <title>Benchmarking eager and lazy loading &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/auto_examples/datasets_io/index.html b/dev/auto_examples/datasets_io/index.html
index 40564aac..8b5c4125 100644
--- a/dev/auto_examples/datasets_io/index.html
+++ b/dev/auto_examples/datasets_io/index.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Loading and organizing data &#8212; Braindecode 0.8 documentation</title>
+    <title>Loading and organizing data &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/auto_examples/datasets_io/plot_benchmark_preprocessing.html b/dev/auto_examples/datasets_io/plot_benchmark_preprocessing.html
index adbe4ef8..2fb75138 100644
--- a/dev/auto_examples/datasets_io/plot_benchmark_preprocessing.html
+++ b/dev/auto_examples/datasets_io/plot_benchmark_preprocessing.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Benchmarking preprocessing with parallelization and serialization &#8212; Braindecode 0.8 documentation</title>
+    <title>Benchmarking preprocessing with parallelization and serialization &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -628,471 +628,444 @@
 </pre></div>
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  0%|                                              | 0.00/51.1M [00:00&lt;?, ?B/s]
-  0%|                                      | 81.9k/51.1M [00:00&lt;01:03, 803kB/s]
-  0%|▏                                      | 183k/51.1M [00:00&lt;00:55, 926kB/s]
-  1%|▏                                      | 295k/51.1M [00:00&lt;00:52, 969kB/s]
-  1%|▎                                      | 410k/51.1M [00:00&lt;00:51, 979kB/s]
-  1%|▍                                      | 508k/51.1M [00:00&lt;00:51, 974kB/s]
-  1%|▍                                      | 606k/51.1M [00:00&lt;00:51, 971kB/s]
-  1%|▌                                      | 721k/51.1M [00:00&lt;00:50, 989kB/s]
-  2%|▋                                      | 836k/51.1M [00:00&lt;00:50, 995kB/s]
-  2%|▋                                      | 950k/51.1M [00:00&lt;00:50, 997kB/s]
-  2%|▊                                     | 1.06M/51.1M [00:01&lt;00:50, 997kB/s]
-  2%|▊                                     | 1.17M/51.1M [00:01&lt;00:50, 986kB/s]
-  3%|▉                                     | 1.28M/51.1M [00:01&lt;00:50, 991kB/s]
-  3%|█                                    | 1.38M/51.1M [00:01&lt;00:49, 1.00MB/s]
-  3%|█                                    | 1.49M/51.1M [00:01&lt;00:48, 1.01MB/s]
-  3%|█▏                                   | 1.61M/51.1M [00:01&lt;00:48, 1.02MB/s]
-  3%|█▏                                   | 1.72M/51.1M [00:01&lt;00:48, 1.01MB/s]
-  4%|█▎                                   | 1.84M/51.1M [00:01&lt;00:48, 1.02MB/s]
-  4%|█▍                                   | 1.95M/51.1M [00:01&lt;00:47, 1.04MB/s]
-  4%|█▍                                   | 2.06M/51.1M [00:02&lt;00:47, 1.03MB/s]
-  4%|█▌                                   | 2.17M/51.1M [00:02&lt;00:48, 1.02MB/s]
-  4%|█▋                                   | 2.27M/51.1M [00:02&lt;00:48, 1.01MB/s]
-  5%|█▋                                   | 2.37M/51.1M [00:02&lt;00:48, 1.01MB/s]
-  5%|█▊                                   | 2.47M/51.1M [00:02&lt;00:48, 1.01MB/s]
-  5%|█▉                                    | 2.57M/51.1M [00:02&lt;00:49, 972kB/s]
-  5%|█▉                                    | 2.69M/51.1M [00:02&lt;00:49, 985kB/s]
-  5%|██                                    | 2.79M/51.1M [00:02&lt;00:48, 987kB/s]
-  6%|██▏                                   | 2.89M/51.1M [00:02&lt;00:48, 988kB/s]
-  6%|██▏                                   | 3.00M/51.1M [00:03&lt;00:48, 987kB/s]
-  6%|██▎                                   | 3.11M/51.1M [00:03&lt;00:48, 990kB/s]
-  6%|██▎                                  | 3.23M/51.1M [00:03&lt;00:47, 1.00MB/s]
-  7%|██▍                                  | 3.34M/51.1M [00:03&lt;00:47, 1.00MB/s]
-  7%|██▌                                  | 3.46M/51.1M [00:03&lt;00:47, 1.00MB/s]
-  7%|██▌                                  | 3.57M/51.1M [00:03&lt;00:47, 1.00MB/s]
-  7%|██▋                                  | 3.69M/51.1M [00:03&lt;00:47, 1.01MB/s]
-  7%|██▋                                  | 3.79M/51.1M [00:03&lt;00:47, 1.00MB/s]
-  8%|██▊                                  | 3.90M/51.1M [00:03&lt;00:46, 1.00MB/s]
-  8%|██▉                                  | 4.01M/51.1M [00:04&lt;00:46, 1.01MB/s]
-  8%|██▉                                  | 4.12M/51.1M [00:04&lt;00:46, 1.01MB/s]
-  8%|███▏                                  | 4.23M/51.1M [00:04&lt;00:47, 993kB/s]
-  8%|███▏                                  | 4.33M/51.1M [00:04&lt;00:47, 982kB/s]
-  9%|███▏                                 | 4.44M/51.1M [00:04&lt;00:46, 1.00MB/s]
-  9%|███▎                                 | 4.55M/51.1M [00:04&lt;00:46, 1.00MB/s]
-  9%|███▍                                 | 4.67M/51.1M [00:04&lt;00:46, 1.01MB/s]
-  9%|███▍                                 | 4.77M/51.1M [00:04&lt;00:46, 1.01MB/s]
- 10%|███▌                                 | 4.87M/51.1M [00:04&lt;00:45, 1.01MB/s]
- 10%|███▋                                  | 4.98M/51.1M [00:04&lt;00:46, 994kB/s]
- 10%|███▊                                  | 5.10M/51.1M [00:05&lt;00:46, 999kB/s]
- 10%|███▊                                 | 5.21M/51.1M [00:05&lt;00:45, 1.00MB/s]
- 10%|███▊                                 | 5.32M/51.1M [00:05&lt;00:45, 1.02MB/s]
- 11%|███▉                                 | 5.44M/51.1M [00:05&lt;00:44, 1.03MB/s]
- 11%|████                                 | 5.55M/51.1M [00:05&lt;00:44, 1.03MB/s]
- 11%|████                                 | 5.67M/51.1M [00:05&lt;00:44, 1.03MB/s]
- 11%|████▏                                | 5.78M/51.1M [00:05&lt;00:43, 1.04MB/s]
- 12%|████▎                                | 5.90M/51.1M [00:05&lt;00:43, 1.04MB/s]
- 12%|████▎                                | 6.01M/51.1M [00:05&lt;00:43, 1.04MB/s]
- 12%|████▍                                | 6.12M/51.1M [00:06&lt;00:43, 1.04MB/s]
- 12%|████▌                                | 6.22M/51.1M [00:06&lt;00:43, 1.04MB/s]
- 12%|████▌                                | 6.33M/51.1M [00:06&lt;00:44, 1.01MB/s]
- 13%|████▋                                | 6.44M/51.1M [00:06&lt;00:44, 1.00MB/s]
- 13%|████▊                                 | 6.54M/51.1M [00:06&lt;00:44, 999kB/s]
- 13%|████▉                                 | 6.65M/51.1M [00:06&lt;00:44, 989kB/s]
- 13%|█████                                 | 6.77M/51.1M [00:06&lt;00:44, 993kB/s]
- 13%|████▉                                | 6.88M/51.1M [00:06&lt;00:43, 1.02MB/s]
- 14%|█████                                | 7.00M/51.1M [00:06&lt;00:42, 1.04MB/s]
- 14%|█████▏                               | 7.11M/51.1M [00:07&lt;00:42, 1.03MB/s]
- 14%|█████▏                               | 7.23M/51.1M [00:07&lt;00:42, 1.02MB/s]
- 14%|█████▎                               | 7.34M/51.1M [00:07&lt;00:42, 1.03MB/s]
- 15%|█████▍                               | 7.45M/51.1M [00:07&lt;00:41, 1.04MB/s]
- 15%|█████▍                               | 7.57M/51.1M [00:07&lt;00:42, 1.04MB/s]
- 15%|█████▌                               | 7.68M/51.1M [00:07&lt;00:42, 1.02MB/s]
- 15%|█████▋                               | 7.80M/51.1M [00:07&lt;00:41, 1.03MB/s]
- 15%|█████▋                               | 7.91M/51.1M [00:07&lt;00:41, 1.04MB/s]
- 16%|█████▊                               | 8.03M/51.1M [00:07&lt;00:41, 1.04MB/s]
- 16%|█████▉                               | 8.14M/51.1M [00:08&lt;00:41, 1.05MB/s]
- 16%|█████▉                               | 8.26M/51.1M [00:08&lt;00:40, 1.05MB/s]
- 16%|██████                               | 8.37M/51.1M [00:08&lt;00:40, 1.04MB/s]
- 17%|██████▏                              | 8.49M/51.1M [00:08&lt;00:40, 1.04MB/s]
- 17%|██████▏                              | 8.60M/51.1M [00:08&lt;00:39, 1.07MB/s]
- 17%|██████▎                              | 8.72M/51.1M [00:08&lt;00:39, 1.07MB/s]
- 17%|██████▍                              | 8.83M/51.1M [00:08&lt;00:40, 1.06MB/s]
- 18%|██████▍                              | 8.95M/51.1M [00:08&lt;00:40, 1.05MB/s]
- 18%|██████▌                              | 9.06M/51.1M [00:08&lt;00:40, 1.04MB/s]
- 18%|██████▋                              | 9.18M/51.1M [00:09&lt;00:40, 1.03MB/s]
- 18%|██████▋                              | 9.29M/51.1M [00:09&lt;00:40, 1.03MB/s]
- 18%|██████▊                              | 9.40M/51.1M [00:09&lt;00:40, 1.03MB/s]
- 19%|██████▉                              | 9.52M/51.1M [00:09&lt;00:40, 1.02MB/s]
- 19%|██████▉                              | 9.63M/51.1M [00:09&lt;00:40, 1.03MB/s]
- 19%|███████                              | 9.75M/51.1M [00:09&lt;00:40, 1.03MB/s]
- 19%|███████▏                             | 9.86M/51.1M [00:09&lt;00:39, 1.04MB/s]
- 20%|███████▏                             | 9.98M/51.1M [00:09&lt;00:39, 1.05MB/s]
- 20%|███████▎                             | 10.1M/51.1M [00:09&lt;00:38, 1.06MB/s]
- 20%|███████▍                             | 10.2M/51.1M [00:10&lt;00:38, 1.07MB/s]
- 20%|███████▍                             | 10.3M/51.1M [00:10&lt;00:38, 1.07MB/s]
- 20%|███████▌                             | 10.4M/51.1M [00:10&lt;00:37, 1.07MB/s]
- 21%|███████▋                             | 10.6M/51.1M [00:10&lt;00:38, 1.06MB/s]
- 21%|███████▋                             | 10.7M/51.1M [00:10&lt;00:38, 1.05MB/s]
- 21%|███████▊                             | 10.8M/51.1M [00:10&lt;00:38, 1.04MB/s]
- 21%|███████▉                             | 10.9M/51.1M [00:10&lt;00:39, 1.02MB/s]
- 22%|███████▉                             | 11.0M/51.1M [00:10&lt;00:39, 1.02MB/s]
- 22%|████████                             | 11.1M/51.1M [00:10&lt;00:39, 1.02MB/s]
- 22%|████████▏                            | 11.2M/51.1M [00:11&lt;00:39, 1.01MB/s]
- 22%|████████▏                            | 11.4M/51.1M [00:11&lt;00:38, 1.03MB/s]
- 22%|████████▎                            | 11.5M/51.1M [00:11&lt;00:37, 1.05MB/s]
- 23%|████████▍                            | 11.6M/51.1M [00:11&lt;00:37, 1.05MB/s]
- 23%|████████▍                            | 11.7M/51.1M [00:11&lt;00:37, 1.04MB/s]
- 23%|████████▌                            | 11.8M/51.1M [00:11&lt;00:36, 1.07MB/s]
- 23%|████████▋                            | 11.9M/51.1M [00:11&lt;00:37, 1.06MB/s]
- 24%|████████▋                            | 12.0M/51.1M [00:11&lt;00:37, 1.05MB/s]
- 24%|████████▊                            | 12.2M/51.1M [00:11&lt;00:36, 1.06MB/s]
- 24%|████████▉                            | 12.3M/51.1M [00:12&lt;00:36, 1.07MB/s]
- 24%|████████▉                            | 12.4M/51.1M [00:12&lt;00:36, 1.06MB/s]
- 24%|█████████                            | 12.5M/51.1M [00:12&lt;00:36, 1.06MB/s]
- 25%|█████████▏                           | 12.6M/51.1M [00:12&lt;00:36, 1.06MB/s]
- 25%|█████████▏                           | 12.7M/51.1M [00:12&lt;00:36, 1.05MB/s]
- 25%|█████████▎                           | 12.8M/51.1M [00:12&lt;00:36, 1.04MB/s]
- 25%|█████████▍                           | 13.0M/51.1M [00:12&lt;00:36, 1.04MB/s]
- 26%|█████████▍                           | 13.1M/51.1M [00:12&lt;00:37, 1.03MB/s]
- 26%|█████████▌                           | 13.2M/51.1M [00:12&lt;00:37, 1.02MB/s]
- 26%|█████████▋                           | 13.3M/51.1M [00:13&lt;00:36, 1.04MB/s]
- 26%|█████████▋                           | 13.4M/51.1M [00:13&lt;00:36, 1.04MB/s]
- 26%|█████████▊                           | 13.5M/51.1M [00:13&lt;00:36, 1.04MB/s]
- 27%|█████████▉                           | 13.6M/51.1M [00:13&lt;00:35, 1.04MB/s]
- 27%|█████████▉                           | 13.8M/51.1M [00:13&lt;00:35, 1.05MB/s]
- 27%|██████████                           | 13.9M/51.1M [00:13&lt;00:35, 1.05MB/s]
- 27%|██████████                           | 14.0M/51.1M [00:13&lt;00:35, 1.04MB/s]
- 28%|██████████▏                          | 14.1M/51.1M [00:13&lt;00:36, 1.02MB/s]
- 28%|██████████▎                          | 14.2M/51.1M [00:13&lt;00:35, 1.03MB/s]
- 28%|██████████▎                          | 14.3M/51.1M [00:13&lt;00:35, 1.04MB/s]
- 28%|██████████▍                          | 14.4M/51.1M [00:14&lt;00:34, 1.07MB/s]
- 28%|██████████▌                          | 14.5M/51.1M [00:14&lt;00:33, 1.08MB/s]
- 29%|██████████▌                          | 14.7M/51.1M [00:14&lt;00:33, 1.08MB/s]
- 29%|██████████▋                          | 14.8M/51.1M [00:14&lt;00:34, 1.06MB/s]
- 29%|██████████▊                          | 14.9M/51.1M [00:14&lt;00:34, 1.05MB/s]
- 29%|██████████▊                          | 15.0M/51.1M [00:14&lt;00:34, 1.06MB/s]
- 30%|██████████▉                          | 15.1M/51.1M [00:14&lt;00:34, 1.05MB/s]
- 30%|███████████                          | 15.2M/51.1M [00:14&lt;00:34, 1.04MB/s]
- 30%|███████████                          | 15.4M/51.1M [00:14&lt;00:34, 1.05MB/s]
- 30%|███████████▏                         | 15.5M/51.1M [00:15&lt;00:34, 1.05MB/s]
- 30%|███████████▎                         | 15.6M/51.1M [00:15&lt;00:33, 1.05MB/s]
- 31%|███████████▎                         | 15.7M/51.1M [00:15&lt;00:33, 1.06MB/s]
- 31%|███████████▍                         | 15.8M/51.1M [00:15&lt;00:33, 1.06MB/s]
- 31%|███████████▌                         | 15.9M/51.1M [00:15&lt;00:33, 1.05MB/s]
- 31%|███████████▌                         | 16.0M/51.1M [00:15&lt;00:33, 1.05MB/s]
- 32%|███████████▋                         | 16.2M/51.1M [00:15&lt;00:33, 1.04MB/s]
- 32%|███████████▊                         | 16.3M/51.1M [00:15&lt;00:33, 1.03MB/s]
- 32%|███████████▊                         | 16.4M/51.1M [00:15&lt;00:33, 1.03MB/s]
- 32%|███████████▉                         | 16.5M/51.1M [00:16&lt;00:33, 1.04MB/s]
- 32%|████████████                         | 16.6M/51.1M [00:16&lt;00:33, 1.03MB/s]
- 33%|████████████                         | 16.7M/51.1M [00:16&lt;00:34, 1.01MB/s]
- 33%|████████████▏                        | 16.8M/51.1M [00:16&lt;00:33, 1.03MB/s]
- 33%|████████████▎                        | 16.9M/51.1M [00:16&lt;00:33, 1.03MB/s]
- 33%|████████████▎                        | 17.1M/51.1M [00:16&lt;00:32, 1.06MB/s]
- 34%|████████████▍                        | 17.2M/51.1M [00:16&lt;00:31, 1.07MB/s]
- 34%|████████████▌                        | 17.3M/51.1M [00:16&lt;00:31, 1.08MB/s]
- 34%|████████████▌                        | 17.4M/51.1M [00:16&lt;00:31, 1.08MB/s]
- 34%|████████████▋                        | 17.5M/51.1M [00:17&lt;00:31, 1.05MB/s]
- 34%|████████████▊                        | 17.6M/51.1M [00:17&lt;00:31, 1.06MB/s]
- 35%|████████████▊                        | 17.7M/51.1M [00:17&lt;00:31, 1.06MB/s]
- 35%|████████████▉                        | 17.9M/51.1M [00:17&lt;00:31, 1.05MB/s]
- 35%|█████████████                        | 18.0M/51.1M [00:17&lt;00:32, 1.03MB/s]
- 35%|█████████████                        | 18.1M/51.1M [00:17&lt;00:32, 1.03MB/s]
- 36%|█████████████▏                       | 18.2M/51.1M [00:17&lt;00:32, 1.03MB/s]
- 36%|█████████████▎                       | 18.3M/51.1M [00:17&lt;00:32, 1.01MB/s]
- 36%|█████████████▎                       | 18.4M/51.1M [00:17&lt;00:32, 1.01MB/s]
- 36%|█████████████▍                       | 18.5M/51.1M [00:18&lt;00:31, 1.02MB/s]
- 36%|█████████████▍                       | 18.6M/51.1M [00:18&lt;00:31, 1.02MB/s]
- 37%|█████████████▌                       | 18.7M/51.1M [00:18&lt;00:31, 1.02MB/s]
- 37%|█████████████▋                       | 18.9M/51.1M [00:18&lt;00:32, 1.00MB/s]
- 37%|█████████████▋                       | 19.0M/51.1M [00:18&lt;00:31, 1.01MB/s]
- 37%|█████████████▊                       | 19.1M/51.1M [00:18&lt;00:31, 1.02MB/s]
- 38%|█████████████▉                       | 19.2M/51.1M [00:18&lt;00:31, 1.01MB/s]
- 38%|█████████████▉                       | 19.3M/51.1M [00:18&lt;00:31, 1.02MB/s]
- 38%|██████████████                       | 19.4M/51.1M [00:18&lt;00:30, 1.03MB/s]
- 38%|██████████████▏                      | 19.5M/51.1M [00:19&lt;00:30, 1.04MB/s]
- 38%|██████████████▏                      | 19.7M/51.1M [00:19&lt;00:30, 1.05MB/s]
- 39%|██████████████▎                      | 19.8M/51.1M [00:19&lt;00:28, 1.08MB/s]
- 39%|██████████████▍                      | 19.9M/51.1M [00:19&lt;00:29, 1.06MB/s]
- 39%|██████████████▍                      | 20.0M/51.1M [00:19&lt;00:29, 1.06MB/s]
- 39%|██████████████▌                      | 20.1M/51.1M [00:19&lt;00:30, 1.02MB/s]
- 40%|██████████████▋                      | 20.2M/51.1M [00:19&lt;00:30, 1.01MB/s]
- 40%|██████████████▋                      | 20.3M/51.1M [00:19&lt;00:30, 1.01MB/s]
- 40%|██████████████▊                      | 20.5M/51.1M [00:19&lt;00:30, 1.00MB/s]
- 40%|███████████████▎                      | 20.6M/51.1M [00:19&lt;00:30, 992kB/s]
- 40%|██████████████▉                      | 20.7M/51.1M [00:20&lt;00:30, 1.00MB/s]
- 41%|███████████████▍                      | 20.8M/51.1M [00:20&lt;00:30, 998kB/s]
- 41%|███████████████▌                      | 20.9M/51.1M [00:20&lt;00:30, 993kB/s]
- 41%|███████████████▌                      | 21.0M/51.1M [00:20&lt;00:30, 987kB/s]
- 41%|███████████████▋                      | 21.1M/51.1M [00:20&lt;00:30, 997kB/s]
- 42%|███████████████▎                     | 21.2M/51.1M [00:20&lt;00:29, 1.01MB/s]
- 42%|███████████████▍                     | 21.3M/51.1M [00:20&lt;00:29, 1.02MB/s]
- 42%|███████████████▌                     | 21.5M/51.1M [00:20&lt;00:28, 1.03MB/s]
- 42%|███████████████▌                     | 21.6M/51.1M [00:20&lt;00:28, 1.03MB/s]
- 42%|███████████████▋                     | 21.7M/51.1M [00:21&lt;00:29, 1.00MB/s]
- 43%|████████████████▏                     | 21.8M/51.1M [00:21&lt;00:29, 988kB/s]
- 43%|████████████████▎                     | 21.9M/51.1M [00:21&lt;00:29, 981kB/s]
- 43%|████████████████▎                     | 22.0M/51.1M [00:21&lt;00:29, 974kB/s]
- 43%|████████████████▍                     | 22.1M/51.1M [00:21&lt;00:29, 974kB/s]
- 43%|████████████████▍                     | 22.2M/51.1M [00:21&lt;00:29, 971kB/s]
- 44%|████████████████▌                     | 22.3M/51.1M [00:21&lt;00:30, 952kB/s]
- 44%|████████████████▋                     | 22.4M/51.1M [00:21&lt;00:30, 954kB/s]
- 44%|████████████████▋                     | 22.5M/51.1M [00:21&lt;00:29, 965kB/s]
- 44%|████████████████▊                     | 22.6M/51.1M [00:22&lt;00:29, 960kB/s]
- 44%|████████████████▉                     | 22.7M/51.1M [00:22&lt;00:29, 975kB/s]
- 45%|████████████████▌                    | 22.8M/51.1M [00:22&lt;00:28, 1.01MB/s]
- 45%|█████████████████                     | 22.9M/51.1M [00:22&lt;00:28, 981kB/s]
- 45%|█████████████████                     | 23.0M/51.1M [00:22&lt;00:28, 979kB/s]
- 45%|█████████████████▏                    | 23.1M/51.1M [00:22&lt;00:28, 978kB/s]
- 45%|█████████████████▎                    | 23.2M/51.1M [00:22&lt;00:28, 988kB/s]
- 46%|█████████████████▎                    | 23.3M/51.1M [00:22&lt;00:27, 995kB/s]
- 46%|████████████████▉                    | 23.5M/51.1M [00:22&lt;00:27, 1.01MB/s]
- 46%|█████████████████                    | 23.6M/51.1M [00:23&lt;00:26, 1.03MB/s]
- 46%|█████████████████▏                   | 23.7M/51.1M [00:23&lt;00:26, 1.02MB/s]
- 47%|█████████████████▏                   | 23.8M/51.1M [00:23&lt;00:26, 1.02MB/s]
- 47%|█████████████████▎                   | 23.9M/51.1M [00:23&lt;00:26, 1.02MB/s]
- 47%|█████████████████▍                   | 24.0M/51.1M [00:23&lt;00:26, 1.01MB/s]
- 47%|█████████████████▍                   | 24.1M/51.1M [00:23&lt;00:26, 1.01MB/s]
- 47%|█████████████████▌                   | 24.2M/51.1M [00:23&lt;00:26, 1.01MB/s]
- 48%|█████████████████▋                   | 24.4M/51.1M [00:23&lt;00:26, 1.01MB/s]
- 48%|█████████████████▋                   | 24.5M/51.1M [00:23&lt;00:26, 1.01MB/s]
- 48%|█████████████████▊                   | 24.6M/51.1M [00:24&lt;00:26, 1.01MB/s]
- 48%|█████████████████▉                   | 24.7M/51.1M [00:24&lt;00:25, 1.02MB/s]
- 49%|█████████████████▉                   | 24.8M/51.1M [00:24&lt;00:25, 1.02MB/s]
- 49%|██████████████████                   | 24.9M/51.1M [00:24&lt;00:25, 1.03MB/s]
- 49%|██████████████████▏                  | 25.1M/51.1M [00:24&lt;00:25, 1.03MB/s]
- 49%|██████████████████▏                  | 25.2M/51.1M [00:24&lt;00:24, 1.06MB/s]
- 49%|██████████████████▎                  | 25.3M/51.1M [00:24&lt;00:23, 1.08MB/s]
- 50%|██████████████████▍                  | 25.4M/51.1M [00:24&lt;00:23, 1.08MB/s]
- 50%|██████████████████▍                  | 25.5M/51.1M [00:24&lt;00:24, 1.06MB/s]
- 50%|██████████████████▌                  | 25.6M/51.1M [00:25&lt;00:24, 1.04MB/s]
- 50%|██████████████████▋                  | 25.7M/51.1M [00:25&lt;00:24, 1.04MB/s]
- 51%|██████████████████▋                  | 25.9M/51.1M [00:25&lt;00:24, 1.03MB/s]
- 51%|██████████████████▊                  | 26.0M/51.1M [00:25&lt;00:24, 1.02MB/s]
- 51%|██████████████████▉                  | 26.1M/51.1M [00:25&lt;00:24, 1.04MB/s]
- 51%|██████████████████▉                  | 26.2M/51.1M [00:25&lt;00:24, 1.04MB/s]
- 51%|███████████████████                  | 26.3M/51.1M [00:25&lt;00:23, 1.04MB/s]
- 52%|███████████████████                  | 26.4M/51.1M [00:25&lt;00:23, 1.04MB/s]
- 52%|███████████████████▏                 | 26.5M/51.1M [00:25&lt;00:24, 1.01MB/s]
- 52%|███████████████████▎                 | 26.6M/51.1M [00:25&lt;00:24, 1.01MB/s]
- 52%|███████████████████▉                  | 26.7M/51.1M [00:26&lt;00:24, 999kB/s]
- 53%|███████████████████▍                 | 26.9M/51.1M [00:26&lt;00:24, 1.00MB/s]
- 53%|███████████████████▌                 | 27.0M/51.1M [00:26&lt;00:24, 1.00MB/s]
- 53%|███████████████████▌                 | 27.1M/51.1M [00:26&lt;00:23, 1.01MB/s]
- 53%|███████████████████▋                 | 27.2M/51.1M [00:26&lt;00:23, 1.01MB/s]
- 53%|███████████████████▊                 | 27.3M/51.1M [00:26&lt;00:23, 1.01MB/s]
- 54%|████████████████████▍                 | 27.4M/51.1M [00:26&lt;00:23, 999kB/s]
- 54%|███████████████████▉                 | 27.5M/51.1M [00:26&lt;00:23, 1.01MB/s]
- 54%|████████████████████                 | 27.6M/51.1M [00:26&lt;00:22, 1.03MB/s]
- 54%|████████████████████                 | 27.8M/51.1M [00:27&lt;00:22, 1.02MB/s]
- 55%|████████████████████▏                | 27.9M/51.1M [00:27&lt;00:22, 1.02MB/s]
- 55%|████████████████████▎                | 28.0M/51.1M [00:27&lt;00:22, 1.02MB/s]
- 55%|████████████████████▎                | 28.1M/51.1M [00:27&lt;00:22, 1.02MB/s]
- 55%|████████████████████▍                | 28.2M/51.1M [00:27&lt;00:22, 1.02MB/s]
- 55%|████████████████████▌                | 28.3M/51.1M [00:27&lt;00:22, 1.02MB/s]
- 56%|████████████████████▌                | 28.4M/51.1M [00:27&lt;00:22, 1.01MB/s]
- 56%|████████████████████▋                | 28.5M/51.1M [00:27&lt;00:22, 1.01MB/s]
- 56%|█████████████████████▎                | 28.6M/51.1M [00:27&lt;00:22, 985kB/s]
- 56%|█████████████████████▍                | 28.8M/51.1M [00:28&lt;00:22, 986kB/s]
- 56%|█████████████████████▍                | 28.9M/51.1M [00:28&lt;00:22, 979kB/s]
- 57%|█████████████████████▌                | 29.0M/51.1M [00:28&lt;00:22, 976kB/s]
- 57%|█████████████████████▌                | 29.1M/51.1M [00:28&lt;00:22, 990kB/s]
- 57%|█████████████████████                | 29.2M/51.1M [00:28&lt;00:21, 1.02MB/s]
- 57%|█████████████████████▏               | 29.3M/51.1M [00:28&lt;00:21, 1.04MB/s]
- 58%|█████████████████████▎               | 29.4M/51.1M [00:28&lt;00:20, 1.04MB/s]
- 58%|█████████████████████▎               | 29.5M/51.1M [00:28&lt;00:20, 1.03MB/s]
- 58%|█████████████████████▍               | 29.6M/51.1M [00:28&lt;00:21, 1.02MB/s]
- 58%|█████████████████████▌               | 29.7M/51.1M [00:29&lt;00:21, 1.02MB/s]
- 58%|██████████████████████▏               | 29.9M/51.1M [00:29&lt;00:21, 996kB/s]
- 59%|██████████████████████▎               | 30.0M/51.1M [00:29&lt;00:21, 988kB/s]
- 59%|██████████████████████▎               | 30.1M/51.1M [00:29&lt;00:21, 984kB/s]
- 59%|██████████████████████▍               | 30.2M/51.1M [00:29&lt;00:21, 986kB/s]
- 59%|██████████████████████▍               | 30.3M/51.1M [00:29&lt;00:20, 994kB/s]
- 59%|██████████████████████▌               | 30.4M/51.1M [00:29&lt;00:20, 989kB/s]
- 60%|██████████████████████▋               | 30.5M/51.1M [00:29&lt;00:20, 989kB/s]
- 60%|██████████████████████▏              | 30.6M/51.1M [00:29&lt;00:20, 1.01MB/s]
- 60%|██████████████████████▏              | 30.7M/51.1M [00:30&lt;00:20, 1.01MB/s]
- 60%|██████████████████████▎              | 30.8M/51.1M [00:30&lt;00:20, 1.01MB/s]
- 60%|██████████████████████▎              | 30.9M/51.1M [00:30&lt;00:20, 1.01MB/s]
- 61%|███████████████████████               | 31.0M/51.1M [00:30&lt;00:20, 979kB/s]
- 61%|███████████████████████               | 31.1M/51.1M [00:30&lt;00:20, 989kB/s]
- 61%|███████████████████████▏              | 31.2M/51.1M [00:30&lt;00:20, 978kB/s]
- 61%|███████████████████████▎              | 31.3M/51.1M [00:30&lt;00:20, 981kB/s]
- 61%|██████████████████████▋              | 31.4M/51.1M [00:30&lt;00:19, 1.00MB/s]
- 62%|██████████████████████▊              | 31.5M/51.1M [00:30&lt;00:19, 1.01MB/s]
- 62%|██████████████████████▉              | 31.7M/51.1M [00:31&lt;00:19, 1.01MB/s]
- 62%|██████████████████████▉              | 31.8M/51.1M [00:31&lt;00:19, 1.00MB/s]
- 62%|███████████████████████▋              | 31.9M/51.1M [00:31&lt;00:19, 997kB/s]
- 63%|███████████████████████▊              | 32.0M/51.1M [00:31&lt;00:19, 997kB/s]
- 63%|███████████████████████▏             | 32.1M/51.1M [00:31&lt;00:19, 1.00MB/s]
- 63%|███████████████████████▎             | 32.2M/51.1M [00:31&lt;00:18, 1.01MB/s]
- 63%|███████████████████████▍             | 32.3M/51.1M [00:31&lt;00:18, 1.00MB/s]
- 63%|███████████████████████▍             | 32.4M/51.1M [00:31&lt;00:18, 1.00MB/s]
- 64%|████████████████████████▏             | 32.5M/51.1M [00:31&lt;00:18, 987kB/s]
- 64%|████████████████████████▎             | 32.6M/51.1M [00:31&lt;00:18, 982kB/s]
- 64%|████████████████████████▎             | 32.7M/51.1M [00:32&lt;00:18, 974kB/s]
- 64%|████████████████████████▍             | 32.8M/51.1M [00:32&lt;00:18, 974kB/s]
- 64%|████████████████████████▍             | 32.9M/51.1M [00:32&lt;00:18, 998kB/s]
- 65%|███████████████████████▉             | 33.0M/51.1M [00:32&lt;00:17, 1.04MB/s]
- 65%|████████████████████████             | 33.2M/51.1M [00:32&lt;00:16, 1.06MB/s]
- 65%|████████████████████████             | 33.3M/51.1M [00:32&lt;00:16, 1.05MB/s]
- 65%|████████████████████████▏            | 33.4M/51.1M [00:32&lt;00:17, 1.04MB/s]
- 66%|████████████████████████▎            | 33.5M/51.1M [00:32&lt;00:16, 1.05MB/s]
- 66%|████████████████████████▎            | 33.6M/51.1M [00:32&lt;00:16, 1.03MB/s]
- 66%|████████████████████████▍            | 33.7M/51.1M [00:33&lt;00:16, 1.03MB/s]
- 66%|████████████████████████▌            | 33.8M/51.1M [00:33&lt;00:16, 1.03MB/s]
- 66%|████████████████████████▌            | 34.0M/51.1M [00:33&lt;00:16, 1.04MB/s]
- 67%|████████████████████████▋            | 34.1M/51.1M [00:33&lt;00:16, 1.04MB/s]
- 67%|████████████████████████▊            | 34.2M/51.1M [00:33&lt;00:16, 1.02MB/s]
- 67%|████████████████████████▊            | 34.3M/51.1M [00:33&lt;00:16, 1.02MB/s]
- 67%|████████████████████████▉            | 34.4M/51.1M [00:33&lt;00:16, 1.01MB/s]
- 68%|████████████████████████▉            | 34.5M/51.1M [00:33&lt;00:16, 1.00MB/s]
- 68%|█████████████████████████            | 34.6M/51.1M [00:33&lt;00:16, 1.02MB/s]
- 68%|█████████████████████████▏           | 34.8M/51.1M [00:34&lt;00:16, 1.02MB/s]
- 68%|█████████████████████████▏           | 34.9M/51.1M [00:34&lt;00:15, 1.03MB/s]
- 68%|█████████████████████████▎           | 35.0M/51.1M [00:34&lt;00:15, 1.02MB/s]
- 69%|█████████████████████████▍           | 35.1M/51.1M [00:34&lt;00:15, 1.01MB/s]
- 69%|█████████████████████████▍           | 35.2M/51.1M [00:34&lt;00:15, 1.01MB/s]
- 69%|█████████████████████████▌           | 35.3M/51.1M [00:34&lt;00:15, 1.01MB/s]
- 69%|██████████████████████████▎           | 35.4M/51.1M [00:34&lt;00:15, 987kB/s]
- 69%|██████████████████████████▍           | 35.5M/51.1M [00:34&lt;00:15, 991kB/s]
- 70%|██████████████████████████▍           | 35.6M/51.1M [00:34&lt;00:15, 994kB/s]
- 70%|██████████████████████████▌           | 35.7M/51.1M [00:35&lt;00:15, 996kB/s]
- 70%|█████████████████████████▉           | 35.8M/51.1M [00:35&lt;00:15, 1.00MB/s]
- 70%|██████████████████████████           | 36.0M/51.1M [00:35&lt;00:15, 1.00MB/s]
- 71%|██████████████████████████▊           | 36.1M/51.1M [00:35&lt;00:15, 999kB/s]
- 71%|██████████████████████████▉           | 36.2M/51.1M [00:35&lt;00:15, 988kB/s]
- 71%|██████████████████████████▉           | 36.3M/51.1M [00:35&lt;00:15, 981kB/s]
- 71%|███████████████████████████           | 36.4M/51.1M [00:35&lt;00:14, 991kB/s]
- 71%|███████████████████████████▏          | 36.5M/51.1M [00:35&lt;00:14, 993kB/s]
- 72%|██████████████████████████▌          | 36.6M/51.1M [00:35&lt;00:14, 1.02MB/s]
- 72%|███████████████████████████▎          | 36.7M/51.1M [00:36&lt;00:14, 981kB/s]
- 72%|███████████████████████████▍          | 36.8M/51.1M [00:36&lt;00:14, 985kB/s]
- 72%|███████████████████████████▍          | 36.9M/51.1M [00:36&lt;00:14, 983kB/s]
- 72%|███████████████████████████▌          | 37.0M/51.1M [00:36&lt;00:14, 994kB/s]
- 73%|███████████████████████████▋          | 37.2M/51.1M [00:36&lt;00:14, 994kB/s]
- 73%|██████████████████████████▉          | 37.3M/51.1M [00:36&lt;00:13, 1.01MB/s]
- 73%|███████████████████████████          | 37.4M/51.1M [00:36&lt;00:13, 1.02MB/s]
- 73%|███████████████████████████▏         | 37.5M/51.1M [00:36&lt;00:13, 1.02MB/s]
- 74%|███████████████████████████▏         | 37.6M/51.1M [00:36&lt;00:13, 1.02MB/s]
- 74%|███████████████████████████▎         | 37.7M/51.1M [00:37&lt;00:13, 1.00MB/s]
- 74%|███████████████████████████▍         | 37.8M/51.1M [00:37&lt;00:13, 1.02MB/s]
- 74%|███████████████████████████▍         | 37.9M/51.1M [00:37&lt;00:12, 1.03MB/s]
- 74%|███████████████████████████▌         | 38.1M/51.1M [00:37&lt;00:12, 1.04MB/s]
- 75%|███████████████████████████▋         | 38.2M/51.1M [00:37&lt;00:12, 1.03MB/s]
- 75%|███████████████████████████▋         | 38.3M/51.1M [00:37&lt;00:12, 1.02MB/s]
- 75%|███████████████████████████▊         | 38.4M/51.1M [00:37&lt;00:12, 1.03MB/s]
- 75%|███████████████████████████▉         | 38.5M/51.1M [00:37&lt;00:12, 1.02MB/s]
- 76%|███████████████████████████▉         | 38.6M/51.1M [00:37&lt;00:12, 1.02MB/s]
- 76%|████████████████████████████         | 38.7M/51.1M [00:38&lt;00:11, 1.03MB/s]
- 76%|████████████████████████████▏        | 38.9M/51.1M [00:38&lt;00:11, 1.03MB/s]
- 76%|████████████████████████████▏        | 39.0M/51.1M [00:38&lt;00:11, 1.03MB/s]
- 76%|████████████████████████████▎        | 39.1M/51.1M [00:38&lt;00:11, 1.01MB/s]
- 77%|████████████████████████████▍        | 39.2M/51.1M [00:38&lt;00:11, 1.01MB/s]
- 77%|████████████████████████████▍        | 39.3M/51.1M [00:38&lt;00:11, 1.00MB/s]
- 77%|█████████████████████████████▎        | 39.4M/51.1M [00:38&lt;00:11, 999kB/s]
- 77%|████████████████████████████▌        | 39.5M/51.1M [00:38&lt;00:11, 1.00MB/s]
- 78%|█████████████████████████████▍        | 39.6M/51.1M [00:38&lt;00:11, 994kB/s]
- 78%|█████████████████████████████▌        | 39.7M/51.1M [00:39&lt;00:11, 996kB/s]
- 78%|█████████████████████████████▌        | 39.8M/51.1M [00:39&lt;00:11, 994kB/s]
- 78%|█████████████████████████████▋        | 39.9M/51.1M [00:39&lt;00:11, 986kB/s]
- 78%|█████████████████████████████▊        | 40.1M/51.1M [00:39&lt;00:11, 985kB/s]
- 79%|█████████████████████████████▊        | 40.2M/51.1M [00:39&lt;00:11, 990kB/s]
- 79%|█████████████████████████████▏       | 40.3M/51.1M [00:39&lt;00:10, 1.00MB/s]
- 79%|█████████████████████████████▏       | 40.4M/51.1M [00:39&lt;00:10, 1.01MB/s]
- 79%|█████████████████████████████▎       | 40.5M/51.1M [00:39&lt;00:10, 1.01MB/s]
- 79%|█████████████████████████████▍       | 40.6M/51.1M [00:39&lt;00:10, 1.03MB/s]
- 80%|█████████████████████████████▍       | 40.7M/51.1M [00:40&lt;00:10, 1.03MB/s]
- 80%|█████████████████████████████▌       | 40.9M/51.1M [00:40&lt;00:09, 1.06MB/s]
- 80%|█████████████████████████████▋       | 41.0M/51.1M [00:40&lt;00:09, 1.05MB/s]
- 80%|█████████████████████████████▋       | 41.1M/51.1M [00:40&lt;00:09, 1.04MB/s]
- 81%|█████████████████████████████▊       | 41.2M/51.1M [00:40&lt;00:09, 1.05MB/s]
- 81%|█████████████████████████████▉       | 41.3M/51.1M [00:40&lt;00:09, 1.04MB/s]
- 81%|██████████████████████████████▊       | 41.4M/51.1M [00:40&lt;00:09, 984kB/s]
- 81%|██████████████████████████████▊       | 41.5M/51.1M [00:40&lt;00:09, 984kB/s]
- 81%|██████████████████████████████▉       | 41.6M/51.1M [00:40&lt;00:09, 977kB/s]
- 82%|███████████████████████████████       | 41.7M/51.1M [00:40&lt;00:09, 991kB/s]
- 82%|██████████████████████████████▎      | 41.8M/51.1M [00:41&lt;00:09, 1.02MB/s]
- 82%|██████████████████████████████▎      | 41.9M/51.1M [00:41&lt;00:09, 1.02MB/s]
- 82%|██████████████████████████████▍      | 42.1M/51.1M [00:41&lt;00:08, 1.01MB/s]
- 83%|██████████████████████████████▌      | 42.2M/51.1M [00:41&lt;00:08, 1.02MB/s]
- 83%|██████████████████████████████▌      | 42.3M/51.1M [00:41&lt;00:08, 1.02MB/s]
- 83%|██████████████████████████████▋      | 42.4M/51.1M [00:41&lt;00:08, 1.01MB/s]
- 83%|██████████████████████████████▊      | 42.5M/51.1M [00:41&lt;00:08, 1.00MB/s]
- 83%|██████████████████████████████▊      | 42.6M/51.1M [00:41&lt;00:08, 1.00MB/s]
- 84%|██████████████████████████████▉      | 42.7M/51.1M [00:41&lt;00:08, 1.02MB/s]
- 84%|███████████████████████████████      | 42.8M/51.1M [00:42&lt;00:08, 1.02MB/s]
- 84%|███████████████████████████████      | 42.9M/51.1M [00:42&lt;00:07, 1.02MB/s]
- 84%|███████████████████████████████▏     | 43.0M/51.1M [00:42&lt;00:07, 1.02MB/s]
- 84%|███████████████████████████████▏     | 43.1M/51.1M [00:42&lt;00:07, 1.02MB/s]
- 85%|███████████████████████████████▎     | 43.3M/51.1M [00:42&lt;00:07, 1.01MB/s]
- 85%|████████████████████████████████▏     | 43.4M/51.1M [00:42&lt;00:07, 982kB/s]
- 85%|████████████████████████████████▎     | 43.5M/51.1M [00:42&lt;00:07, 991kB/s]
- 85%|████████████████████████████████▍     | 43.6M/51.1M [00:42&lt;00:07, 997kB/s]
- 85%|███████████████████████████████▋     | 43.7M/51.1M [00:42&lt;00:07, 1.03MB/s]
- 86%|███████████████████████████████▋     | 43.8M/51.1M [00:43&lt;00:06, 1.05MB/s]
- 86%|███████████████████████████████▊     | 43.9M/51.1M [00:43&lt;00:06, 1.04MB/s]
- 86%|███████████████████████████████▉     | 44.0M/51.1M [00:43&lt;00:06, 1.04MB/s]
- 86%|███████████████████████████████▉     | 44.2M/51.1M [00:43&lt;00:06, 1.05MB/s]
- 87%|████████████████████████████████     | 44.3M/51.1M [00:43&lt;00:06, 1.04MB/s]
- 87%|████████████████████████████████▏    | 44.4M/51.1M [00:43&lt;00:06, 1.04MB/s]
- 87%|████████████████████████████████▏    | 44.5M/51.1M [00:43&lt;00:06, 1.02MB/s]
- 87%|████████████████████████████████▎    | 44.6M/51.1M [00:43&lt;00:06, 1.02MB/s]
- 88%|████████████████████████████████▍    | 44.7M/51.1M [00:43&lt;00:06, 1.01MB/s]
- 88%|████████████████████████████████▍    | 44.8M/51.1M [00:44&lt;00:06, 1.03MB/s]
- 88%|████████████████████████████████▌    | 45.0M/51.1M [00:44&lt;00:05, 1.05MB/s]
- 88%|████████████████████████████████▋    | 45.1M/51.1M [00:44&lt;00:05, 1.04MB/s]
- 88%|████████████████████████████████▋    | 45.2M/51.1M [00:44&lt;00:05, 1.03MB/s]
- 89%|████████████████████████████████▊    | 45.3M/51.1M [00:44&lt;00:05, 1.03MB/s]
- 89%|████████████████████████████████▉    | 45.4M/51.1M [00:44&lt;00:05, 1.04MB/s]
- 89%|████████████████████████████████▉    | 45.5M/51.1M [00:44&lt;00:05, 1.03MB/s]
- 89%|█████████████████████████████████    | 45.6M/51.1M [00:44&lt;00:05, 1.01MB/s]
- 90%|█████████████████████████████████    | 45.7M/51.1M [00:44&lt;00:05, 1.02MB/s]
- 90%|█████████████████████████████████▏   | 45.9M/51.1M [00:45&lt;00:05, 1.03MB/s]
- 90%|█████████████████████████████████▎   | 46.0M/51.1M [00:45&lt;00:05, 1.03MB/s]
- 90%|█████████████████████████████████▎   | 46.1M/51.1M [00:45&lt;00:04, 1.02MB/s]
- 90%|█████████████████████████████████▍   | 46.2M/51.1M [00:45&lt;00:04, 1.03MB/s]
- 91%|█████████████████████████████████▌   | 46.3M/51.1M [00:45&lt;00:04, 1.03MB/s]
- 91%|█████████████████████████████████▌   | 46.4M/51.1M [00:45&lt;00:04, 1.02MB/s]
- 91%|█████████████████████████████████▋   | 46.5M/51.1M [00:45&lt;00:04, 1.01MB/s]
- 91%|█████████████████████████████████▊   | 46.6M/51.1M [00:45&lt;00:04, 1.03MB/s]
- 91%|█████████████████████████████████▊   | 46.7M/51.1M [00:45&lt;00:04, 1.05MB/s]
- 92%|█████████████████████████████████▉   | 46.9M/51.1M [00:45&lt;00:04, 1.05MB/s]
- 92%|██████████████████████████████████   | 47.0M/51.1M [00:46&lt;00:04, 1.03MB/s]
- 92%|██████████████████████████████████   | 47.1M/51.1M [00:46&lt;00:03, 1.03MB/s]
- 92%|██████████████████████████████████▏  | 47.2M/51.1M [00:46&lt;00:03, 1.03MB/s]
- 93%|██████████████████████████████████▏  | 47.3M/51.1M [00:46&lt;00:03, 1.03MB/s]
- 93%|██████████████████████████████████▎  | 47.4M/51.1M [00:46&lt;00:03, 1.03MB/s]
- 93%|██████████████████████████████████▍  | 47.5M/51.1M [00:46&lt;00:03, 1.02MB/s]
- 93%|██████████████████████████████████▍  | 47.6M/51.1M [00:46&lt;00:03, 1.01MB/s]
- 93%|██████████████████████████████████▌  | 47.7M/51.1M [00:46&lt;00:03, 1.01MB/s]
- 94%|██████████████████████████████████▋  | 47.9M/51.1M [00:46&lt;00:03, 1.02MB/s]
- 94%|██████████████████████████████████▋  | 48.0M/51.1M [00:47&lt;00:03, 1.02MB/s]
- 94%|██████████████████████████████████▊  | 48.1M/51.1M [00:47&lt;00:02, 1.03MB/s]
- 94%|██████████████████████████████████▉  | 48.2M/51.1M [00:47&lt;00:02, 1.03MB/s]
- 95%|██████████████████████████████████▉  | 48.3M/51.1M [00:47&lt;00:02, 1.04MB/s]
- 95%|███████████████████████████████████  | 48.4M/51.1M [00:47&lt;00:02, 1.03MB/s]
- 95%|███████████████████████████████████▏ | 48.5M/51.1M [00:47&lt;00:02, 1.03MB/s]
- 95%|███████████████████████████████████▏ | 48.7M/51.1M [00:47&lt;00:02, 1.03MB/s]
- 95%|███████████████████████████████████▎ | 48.8M/51.1M [00:47&lt;00:02, 1.05MB/s]
- 96%|███████████████████████████████████▍ | 48.9M/51.1M [00:47&lt;00:02, 1.08MB/s]
- 96%|███████████████████████████████████▍ | 49.0M/51.1M [00:48&lt;00:01, 1.08MB/s]
- 96%|███████████████████████████████████▌ | 49.1M/51.1M [00:48&lt;00:01, 1.06MB/s]
- 96%|███████████████████████████████████▋ | 49.2M/51.1M [00:48&lt;00:01, 1.05MB/s]
- 97%|███████████████████████████████████▋ | 49.3M/51.1M [00:48&lt;00:01, 1.04MB/s]
- 97%|███████████████████████████████████▊ | 49.5M/51.1M [00:48&lt;00:01, 1.03MB/s]
- 97%|███████████████████████████████████▉ | 49.6M/51.1M [00:48&lt;00:01, 1.04MB/s]
- 97%|███████████████████████████████████▉ | 49.7M/51.1M [00:48&lt;00:01, 1.03MB/s]
- 97%|████████████████████████████████████ | 49.8M/51.1M [00:48&lt;00:01, 1.03MB/s]
- 98%|████████████████████████████████████ | 49.9M/51.1M [00:48&lt;00:01, 1.03MB/s]
- 98%|████████████████████████████████████▏| 50.0M/51.1M [00:49&lt;00:01, 1.01MB/s]
- 98%|████████████████████████████████████▎| 50.1M/51.1M [00:49&lt;00:00, 1.03MB/s]
- 98%|████████████████████████████████████▎| 50.2M/51.1M [00:49&lt;00:00, 1.04MB/s]
- 99%|████████████████████████████████████▍| 50.3M/51.1M [00:49&lt;00:00, 1.06MB/s]
- 99%|████████████████████████████████████▌| 50.5M/51.1M [00:49&lt;00:00, 1.05MB/s]
- 99%|████████████████████████████████████▌| 50.6M/51.1M [00:49&lt;00:00, 1.06MB/s]
- 99%|████████████████████████████████████▋| 50.7M/51.1M [00:49&lt;00:00, 1.07MB/s]
- 99%|████████████████████████████████████▊| 50.8M/51.1M [00:49&lt;00:00, 1.05MB/s]
-100%|████████████████████████████████████▊| 50.9M/51.1M [00:49&lt;00:00, 1.03MB/s]
-100%|████████████████████████████████████▉| 51.0M/51.1M [00:49&lt;00:00, 1.02MB/s]
+  0%|                                      | 115k/51.1M [00:00&lt;00:45, 1.11MB/s]
+  0%|▏                                     | 229k/51.1M [00:00&lt;00:46, 1.10MB/s]
+  1%|▎                                     | 344k/51.1M [00:00&lt;00:46, 1.10MB/s]
+  1%|▎                                     | 459k/51.1M [00:00&lt;00:46, 1.10MB/s]
+  1%|▍                                     | 573k/51.1M [00:00&lt;00:46, 1.09MB/s]
+  1%|▌                                     | 688k/51.1M [00:00&lt;00:45, 1.10MB/s]
+  2%|▌                                     | 803k/51.1M [00:00&lt;00:45, 1.10MB/s]
+  2%|▋                                     | 918k/51.1M [00:00&lt;00:46, 1.09MB/s]
+  2%|▋                                    | 1.03M/51.1M [00:00&lt;00:46, 1.09MB/s]
+  2%|▊                                    | 1.15M/51.1M [00:01&lt;00:45, 1.09MB/s]
+  2%|▉                                    | 1.26M/51.1M [00:01&lt;00:45, 1.09MB/s]
+  3%|▉                                    | 1.38M/51.1M [00:01&lt;00:45, 1.10MB/s]
+  3%|█                                    | 1.49M/51.1M [00:01&lt;00:44, 1.11MB/s]
+  3%|█▏                                   | 1.61M/51.1M [00:01&lt;00:44, 1.12MB/s]
+  3%|█▏                                   | 1.72M/51.1M [00:01&lt;00:44, 1.11MB/s]
+  4%|█▎                                   | 1.84M/51.1M [00:01&lt;00:45, 1.08MB/s]
+  4%|█▍                                   | 1.95M/51.1M [00:01&lt;00:45, 1.08MB/s]
+  4%|█▍                                   | 2.06M/51.1M [00:01&lt;00:44, 1.10MB/s]
+  4%|█▌                                   | 2.18M/51.1M [00:01&lt;00:44, 1.10MB/s]
+  4%|█▋                                   | 2.29M/51.1M [00:02&lt;00:43, 1.11MB/s]
+  5%|█▋                                   | 2.41M/51.1M [00:02&lt;00:43, 1.11MB/s]
+  5%|█▊                                   | 2.54M/51.1M [00:02&lt;00:42, 1.14MB/s]
+  5%|█▉                                   | 2.65M/51.1M [00:02&lt;00:42, 1.13MB/s]
+  5%|██                                   | 2.79M/51.1M [00:02&lt;00:42, 1.14MB/s]
+  6%|██                                   | 2.90M/51.1M [00:02&lt;00:42, 1.14MB/s]
+  6%|██▏                                  | 3.01M/51.1M [00:02&lt;00:43, 1.11MB/s]
+  6%|██▎                                  | 3.13M/51.1M [00:02&lt;00:43, 1.09MB/s]
+  6%|██▎                                  | 3.24M/51.1M [00:02&lt;00:43, 1.09MB/s]
+  7%|██▍                                  | 3.36M/51.1M [00:03&lt;00:43, 1.10MB/s]
+  7%|██▌                                  | 3.47M/51.1M [00:03&lt;00:43, 1.10MB/s]
+  7%|██▌                                  | 3.59M/51.1M [00:03&lt;00:43, 1.10MB/s]
+  7%|██▋                                  | 3.70M/51.1M [00:03&lt;00:43, 1.09MB/s]
+  7%|██▊                                  | 3.82M/51.1M [00:03&lt;00:43, 1.09MB/s]
+  8%|██▊                                  | 3.93M/51.1M [00:03&lt;00:44, 1.07MB/s]
+  8%|██▉                                  | 4.05M/51.1M [00:03&lt;00:44, 1.06MB/s]
+  8%|███                                  | 4.16M/51.1M [00:03&lt;00:44, 1.06MB/s]
+  8%|███                                  | 4.28M/51.1M [00:03&lt;00:44, 1.05MB/s]
+  9%|███▏                                 | 4.39M/51.1M [00:04&lt;00:44, 1.05MB/s]
+  9%|███▎                                 | 4.51M/51.1M [00:04&lt;00:44, 1.06MB/s]
+  9%|███▎                                 | 4.62M/51.1M [00:04&lt;00:44, 1.05MB/s]
+  9%|███▍                                 | 4.73M/51.1M [00:04&lt;00:44, 1.04MB/s]
+  9%|███▌                                 | 4.85M/51.1M [00:04&lt;00:44, 1.04MB/s]
+ 10%|███▌                                 | 4.96M/51.1M [00:04&lt;00:44, 1.04MB/s]
+ 10%|███▋                                 | 5.08M/51.1M [00:04&lt;00:43, 1.06MB/s]
+ 10%|███▊                                 | 5.19M/51.1M [00:04&lt;00:43, 1.06MB/s]
+ 10%|███▊                                 | 5.31M/51.1M [00:04&lt;00:42, 1.08MB/s]
+ 11%|███▉                                 | 5.42M/51.1M [00:04&lt;00:42, 1.07MB/s]
+ 11%|████                                 | 5.54M/51.1M [00:05&lt;00:41, 1.09MB/s]
+ 11%|████                                 | 5.67M/51.1M [00:05&lt;00:40, 1.12MB/s]
+ 11%|████▏                                | 5.80M/51.1M [00:05&lt;00:40, 1.12MB/s]
+ 12%|████▎                                | 5.91M/51.1M [00:05&lt;00:40, 1.12MB/s]
+ 12%|████▎                                | 6.03M/51.1M [00:05&lt;00:40, 1.11MB/s]
+ 12%|████▍                                | 6.14M/51.1M [00:05&lt;00:40, 1.10MB/s]
+ 12%|████▌                                | 6.26M/51.1M [00:05&lt;00:40, 1.10MB/s]
+ 12%|████▌                                | 6.37M/51.1M [00:05&lt;00:40, 1.11MB/s]
+ 13%|████▋                                | 6.50M/51.1M [00:05&lt;00:39, 1.12MB/s]
+ 13%|████▊                                | 6.62M/51.1M [00:06&lt;00:39, 1.11MB/s]
+ 13%|████▊                                | 6.73M/51.1M [00:06&lt;00:40, 1.10MB/s]
+ 13%|████▉                                | 6.85M/51.1M [00:06&lt;00:40, 1.09MB/s]
+ 14%|█████                                | 6.96M/51.1M [00:06&lt;00:40, 1.09MB/s]
+ 14%|█████                                | 7.08M/51.1M [00:06&lt;00:40, 1.08MB/s]
+ 14%|█████▏                               | 7.19M/51.1M [00:06&lt;00:40, 1.08MB/s]
+ 14%|█████▎                               | 7.31M/51.1M [00:06&lt;00:40, 1.08MB/s]
+ 15%|█████▎                               | 7.42M/51.1M [00:06&lt;00:40, 1.08MB/s]
+ 15%|█████▍                               | 7.54M/51.1M [00:06&lt;00:40, 1.07MB/s]
+ 15%|█████▌                               | 7.65M/51.1M [00:07&lt;00:40, 1.07MB/s]
+ 15%|█████▌                               | 7.77M/51.1M [00:07&lt;00:40, 1.07MB/s]
+ 15%|█████▋                               | 7.88M/51.1M [00:07&lt;00:40, 1.06MB/s]
+ 16%|█████▊                               | 8.00M/51.1M [00:07&lt;00:40, 1.07MB/s]
+ 16%|█████▊                               | 8.11M/51.1M [00:07&lt;00:40, 1.07MB/s]
+ 16%|█████▉                               | 8.22M/51.1M [00:07&lt;00:39, 1.09MB/s]
+ 16%|██████                               | 8.34M/51.1M [00:07&lt;00:38, 1.10MB/s]
+ 17%|██████▏                              | 8.47M/51.1M [00:07&lt;00:36, 1.15MB/s]
+ 17%|██████▏                              | 8.59M/51.1M [00:07&lt;00:37, 1.14MB/s]
+ 17%|██████▎                              | 8.70M/51.1M [00:07&lt;00:37, 1.12MB/s]
+ 17%|██████▍                              | 8.81M/51.1M [00:08&lt;00:38, 1.11MB/s]
+ 17%|██████▍                              | 8.93M/51.1M [00:08&lt;00:38, 1.10MB/s]
+ 18%|██████▌                              | 9.04M/51.1M [00:08&lt;00:38, 1.10MB/s]
+ 18%|██████▋                              | 9.16M/51.1M [00:08&lt;00:38, 1.09MB/s]
+ 18%|██████▋                              | 9.27M/51.1M [00:08&lt;00:38, 1.10MB/s]
+ 18%|██████▊                              | 9.40M/51.1M [00:08&lt;00:37, 1.12MB/s]
+ 19%|██████▉                              | 9.52M/51.1M [00:08&lt;00:37, 1.12MB/s]
+ 19%|██████▉                              | 9.63M/51.1M [00:08&lt;00:37, 1.11MB/s]
+ 19%|███████                              | 9.76M/51.1M [00:08&lt;00:36, 1.13MB/s]
+ 19%|███████▏                             | 9.88M/51.1M [00:09&lt;00:37, 1.11MB/s]
+ 20%|███████▏                             | 9.99M/51.1M [00:09&lt;00:36, 1.11MB/s]
+ 20%|███████▎                             | 10.1M/51.1M [00:09&lt;00:37, 1.10MB/s]
+ 20%|███████▍                             | 10.2M/51.1M [00:09&lt;00:37, 1.10MB/s]
+ 20%|███████▍                             | 10.4M/51.1M [00:09&lt;00:36, 1.12MB/s]
+ 21%|███████▌                             | 10.5M/51.1M [00:09&lt;00:35, 1.14MB/s]
+ 21%|███████▋                             | 10.6M/51.1M [00:09&lt;00:35, 1.13MB/s]
+ 21%|███████▊                             | 10.7M/51.1M [00:09&lt;00:36, 1.12MB/s]
+ 21%|███████▊                             | 10.8M/51.1M [00:09&lt;00:36, 1.11MB/s]
+ 21%|███████▉                             | 10.9M/51.1M [00:09&lt;00:35, 1.12MB/s]
+ 22%|████████                             | 11.1M/51.1M [00:10&lt;00:35, 1.12MB/s]
+ 22%|████████                             | 11.2M/51.1M [00:10&lt;00:35, 1.11MB/s]
+ 22%|████████▏                            | 11.3M/51.1M [00:10&lt;00:35, 1.11MB/s]
+ 22%|████████▎                            | 11.4M/51.1M [00:10&lt;00:36, 1.10MB/s]
+ 23%|████████▎                            | 11.5M/51.1M [00:10&lt;00:35, 1.11MB/s]
+ 23%|████████▍                            | 11.6M/51.1M [00:10&lt;00:35, 1.12MB/s]
+ 23%|████████▌                            | 11.7M/51.1M [00:10&lt;00:35, 1.12MB/s]
+ 23%|████████▌                            | 11.9M/51.1M [00:10&lt;00:35, 1.12MB/s]
+ 23%|████████▋                            | 12.0M/51.1M [00:10&lt;00:34, 1.14MB/s]
+ 24%|████████▊                            | 12.1M/51.1M [00:11&lt;00:34, 1.14MB/s]
+ 24%|████████▊                            | 12.2M/51.1M [00:11&lt;00:33, 1.15MB/s]
+ 24%|████████▉                            | 12.4M/51.1M [00:11&lt;00:33, 1.16MB/s]
+ 24%|█████████                            | 12.5M/51.1M [00:11&lt;00:33, 1.17MB/s]
+ 25%|█████████▏                           | 12.6M/51.1M [00:11&lt;00:33, 1.15MB/s]
+ 25%|█████████▏                           | 12.7M/51.1M [00:11&lt;00:33, 1.15MB/s]
+ 25%|█████████▎                           | 12.8M/51.1M [00:11&lt;00:33, 1.13MB/s]
+ 25%|█████████▍                           | 13.0M/51.1M [00:11&lt;00:33, 1.13MB/s]
+ 26%|█████████▍                           | 13.1M/51.1M [00:11&lt;00:33, 1.12MB/s]
+ 26%|█████████▌                           | 13.2M/51.1M [00:11&lt;00:33, 1.12MB/s]
+ 26%|█████████▋                           | 13.3M/51.1M [00:12&lt;00:33, 1.13MB/s]
+ 26%|█████████▋                           | 13.4M/51.1M [00:12&lt;00:33, 1.13MB/s]
+ 27%|█████████▊                           | 13.5M/51.1M [00:12&lt;00:33, 1.13MB/s]
+ 27%|█████████▉                           | 13.7M/51.1M [00:12&lt;00:33, 1.12MB/s]
+ 27%|█████████▉                           | 13.8M/51.1M [00:12&lt;00:33, 1.11MB/s]
+ 27%|██████████                           | 13.9M/51.1M [00:12&lt;00:33, 1.11MB/s]
+ 27%|██████████▏                          | 14.0M/51.1M [00:12&lt;00:33, 1.12MB/s]
+ 28%|██████████▏                          | 14.1M/51.1M [00:12&lt;00:33, 1.11MB/s]
+ 28%|██████████▎                          | 14.3M/51.1M [00:12&lt;00:33, 1.11MB/s]
+ 28%|██████████▍                          | 14.4M/51.1M [00:13&lt;00:33, 1.10MB/s]
+ 28%|██████████▍                          | 14.5M/51.1M [00:13&lt;00:33, 1.10MB/s]
+ 29%|██████████▌                          | 14.6M/51.1M [00:13&lt;00:33, 1.08MB/s]
+ 29%|██████████▋                          | 14.7M/51.1M [00:13&lt;00:33, 1.07MB/s]
+ 29%|██████████▋                          | 14.8M/51.1M [00:13&lt;00:33, 1.07MB/s]
+ 29%|██████████▊                          | 14.9M/51.1M [00:13&lt;00:33, 1.06MB/s]
+ 29%|██████████▉                          | 15.1M/51.1M [00:13&lt;00:33, 1.07MB/s]
+ 30%|██████████▉                          | 15.2M/51.1M [00:13&lt;00:33, 1.09MB/s]
+ 30%|███████████                          | 15.3M/51.1M [00:13&lt;00:32, 1.10MB/s]
+ 30%|███████████▏                         | 15.4M/51.1M [00:13&lt;00:32, 1.09MB/s]
+ 30%|███████████▏                         | 15.5M/51.1M [00:14&lt;00:32, 1.10MB/s]
+ 31%|███████████▎                         | 15.6M/51.1M [00:14&lt;00:32, 1.09MB/s]
+ 31%|███████████▍                         | 15.7M/51.1M [00:14&lt;00:32, 1.10MB/s]
+ 31%|███████████▍                         | 15.9M/51.1M [00:14&lt;00:31, 1.11MB/s]
+ 31%|███████████▌                         | 16.0M/51.1M [00:14&lt;00:31, 1.11MB/s]
+ 31%|███████████▋                         | 16.1M/51.1M [00:14&lt;00:31, 1.10MB/s]
+ 32%|███████████▋                         | 16.2M/51.1M [00:14&lt;00:32, 1.09MB/s]
+ 32%|███████████▊                         | 16.3M/51.1M [00:14&lt;00:32, 1.08MB/s]
+ 32%|███████████▉                         | 16.4M/51.1M [00:14&lt;00:31, 1.09MB/s]
+ 32%|███████████▉                         | 16.5M/51.1M [00:15&lt;00:31, 1.10MB/s]
+ 33%|████████████                         | 16.7M/51.1M [00:15&lt;00:31, 1.10MB/s]
+ 33%|████████████▏                        | 16.8M/51.1M [00:15&lt;00:31, 1.10MB/s]
+ 33%|████████████▏                        | 16.9M/51.1M [00:15&lt;00:31, 1.09MB/s]
+ 33%|████████████▎                        | 17.0M/51.1M [00:15&lt;00:30, 1.12MB/s]
+ 34%|████████████▍                        | 17.1M/51.1M [00:15&lt;00:30, 1.11MB/s]
+ 34%|████████████▍                        | 17.3M/51.1M [00:15&lt;00:30, 1.12MB/s]
+ 34%|████████████▌                        | 17.4M/51.1M [00:15&lt;00:30, 1.12MB/s]
+ 34%|████████████▋                        | 17.5M/51.1M [00:15&lt;00:29, 1.14MB/s]
+ 34%|████████████▊                        | 17.6M/51.1M [00:15&lt;00:28, 1.16MB/s]
+ 35%|████████████▊                        | 17.8M/51.1M [00:16&lt;00:28, 1.17MB/s]
+ 35%|████████████▉                        | 17.9M/51.1M [00:16&lt;00:28, 1.16MB/s]
+ 35%|█████████████                        | 18.0M/51.1M [00:16&lt;00:28, 1.16MB/s]
+ 35%|█████████████                        | 18.1M/51.1M [00:16&lt;00:28, 1.15MB/s]
+ 36%|█████████████▏                       | 18.3M/51.1M [00:16&lt;00:28, 1.14MB/s]
+ 36%|█████████████▎                       | 18.4M/51.1M [00:16&lt;00:28, 1.16MB/s]
+ 36%|█████████████▍                       | 18.5M/51.1M [00:16&lt;00:27, 1.17MB/s]
+ 36%|█████████████▍                       | 18.6M/51.1M [00:16&lt;00:27, 1.20MB/s]
+ 37%|█████████████▌                       | 18.8M/51.1M [00:16&lt;00:26, 1.20MB/s]
+ 37%|█████████████▋                       | 18.9M/51.1M [00:17&lt;00:26, 1.21MB/s]
+ 37%|█████████████▊                       | 19.0M/51.1M [00:17&lt;00:26, 1.19MB/s]
+ 38%|█████████████▉                       | 19.2M/51.1M [00:17&lt;00:26, 1.20MB/s]
+ 38%|█████████████▉                       | 19.3M/51.1M [00:17&lt;00:26, 1.19MB/s]
+ 38%|██████████████                       | 19.4M/51.1M [00:17&lt;00:26, 1.18MB/s]
+ 38%|██████████████▏                      | 19.6M/51.1M [00:17&lt;00:26, 1.17MB/s]
+ 39%|██████████████▏                      | 19.7M/51.1M [00:17&lt;00:26, 1.17MB/s]
+ 39%|██████████████▎                      | 19.8M/51.1M [00:17&lt;00:27, 1.15MB/s]
+ 39%|██████████████▍                      | 19.9M/51.1M [00:17&lt;00:27, 1.14MB/s]
+ 39%|██████████████▌                      | 20.0M/51.1M [00:18&lt;00:27, 1.14MB/s]
+ 39%|██████████████▌                      | 20.2M/51.1M [00:18&lt;00:27, 1.14MB/s]
+ 40%|██████████████▋                      | 20.3M/51.1M [00:18&lt;00:26, 1.17MB/s]
+ 40%|██████████████▊                      | 20.4M/51.1M [00:18&lt;00:26, 1.18MB/s]
+ 40%|██████████████▊                      | 20.5M/51.1M [00:18&lt;00:25, 1.18MB/s]
+ 40%|██████████████▉                      | 20.7M/51.1M [00:18&lt;00:25, 1.17MB/s]
+ 41%|███████████████                      | 20.8M/51.1M [00:18&lt;00:25, 1.17MB/s]
+ 41%|███████████████▏                     | 20.9M/51.1M [00:18&lt;00:25, 1.16MB/s]
+ 41%|███████████████▏                     | 21.0M/51.1M [00:18&lt;00:26, 1.15MB/s]
+ 41%|███████████████▎                     | 21.2M/51.1M [00:18&lt;00:25, 1.16MB/s]
+ 42%|███████████████▍                     | 21.3M/51.1M [00:19&lt;00:25, 1.19MB/s]
+ 42%|███████████████▌                     | 21.4M/51.1M [00:19&lt;00:24, 1.20MB/s]
+ 42%|███████████████▌                     | 21.5M/51.1M [00:19&lt;00:24, 1.21MB/s]
+ 42%|███████████████▋                     | 21.7M/51.1M [00:19&lt;00:24, 1.19MB/s]
+ 43%|███████████████▊                     | 21.8M/51.1M [00:19&lt;00:24, 1.18MB/s]
+ 43%|███████████████▊                     | 21.9M/51.1M [00:19&lt;00:25, 1.13MB/s]
+ 43%|███████████████▉                     | 22.0M/51.1M [00:19&lt;00:25, 1.12MB/s]
+ 43%|████████████████                     | 22.1M/51.1M [00:19&lt;00:25, 1.12MB/s]
+ 44%|████████████████                     | 22.3M/51.1M [00:19&lt;00:25, 1.15MB/s]
+ 44%|████████████████▏                    | 22.4M/51.1M [00:20&lt;00:25, 1.14MB/s]
+ 44%|████████████████▎                    | 22.5M/51.1M [00:20&lt;00:24, 1.15MB/s]
+ 44%|████████████████▎                    | 22.6M/51.1M [00:20&lt;00:24, 1.14MB/s]
+ 44%|████████████████▍                    | 22.7M/51.1M [00:20&lt;00:24, 1.14MB/s]
+ 45%|████████████████▌                    | 22.9M/51.1M [00:20&lt;00:24, 1.15MB/s]
+ 45%|████████████████▋                    | 23.0M/51.1M [00:20&lt;00:24, 1.13MB/s]
+ 45%|████████████████▋                    | 23.1M/51.1M [00:20&lt;00:24, 1.16MB/s]
+ 45%|████████████████▊                    | 23.2M/51.1M [00:20&lt;00:23, 1.17MB/s]
+ 46%|████████████████▉                    | 23.4M/51.1M [00:20&lt;00:23, 1.19MB/s]
+ 46%|█████████████████                    | 23.5M/51.1M [00:21&lt;00:23, 1.20MB/s]
+ 46%|█████████████████                    | 23.6M/51.1M [00:21&lt;00:23, 1.19MB/s]
+ 47%|█████████████████▏                   | 23.8M/51.1M [00:21&lt;00:23, 1.18MB/s]
+ 47%|█████████████████▎                   | 23.9M/51.1M [00:21&lt;00:23, 1.18MB/s]
+ 47%|█████████████████▍                   | 24.0M/51.1M [00:21&lt;00:23, 1.16MB/s]
+ 47%|█████████████████▍                   | 24.2M/51.1M [00:21&lt;00:23, 1.16MB/s]
+ 47%|█████████████████▌                   | 24.3M/51.1M [00:21&lt;00:23, 1.16MB/s]
+ 48%|█████████████████▋                   | 24.4M/51.1M [00:21&lt;00:23, 1.13MB/s]
+ 48%|█████████████████▋                   | 24.5M/51.1M [00:21&lt;00:23, 1.11MB/s]
+ 48%|█████████████████▊                   | 24.6M/51.1M [00:21&lt;00:23, 1.11MB/s]
+ 48%|█████████████████▉                   | 24.7M/51.1M [00:22&lt;00:23, 1.11MB/s]
+ 49%|█████████████████▉                   | 24.8M/51.1M [00:22&lt;00:23, 1.10MB/s]
+ 49%|██████████████████                   | 25.0M/51.1M [00:22&lt;00:23, 1.12MB/s]
+ 49%|██████████████████▏                  | 25.1M/51.1M [00:22&lt;00:22, 1.16MB/s]
+ 49%|██████████████████▎                  | 25.2M/51.1M [00:22&lt;00:22, 1.16MB/s]
+ 50%|██████████████████▎                  | 25.3M/51.1M [00:22&lt;00:23, 1.09MB/s]
+ 50%|██████████████████▍                  | 25.4M/51.1M [00:22&lt;00:23, 1.08MB/s]
+ 50%|██████████████████▌                  | 25.6M/51.1M [00:22&lt;00:23, 1.09MB/s]
+ 50%|██████████████████▌                  | 25.7M/51.1M [00:22&lt;00:22, 1.11MB/s]
+ 50%|██████████████████▋                  | 25.8M/51.1M [00:23&lt;00:22, 1.11MB/s]
+ 51%|██████████████████▊                  | 25.9M/51.1M [00:23&lt;00:22, 1.11MB/s]
+ 51%|██████████████████▊                  | 26.0M/51.1M [00:23&lt;00:22, 1.10MB/s]
+ 51%|██████████████████▉                  | 26.1M/51.1M [00:23&lt;00:22, 1.11MB/s]
+ 51%|███████████████████                  | 26.2M/51.1M [00:23&lt;00:22, 1.10MB/s]
+ 52%|███████████████████                  | 26.4M/51.1M [00:23&lt;00:22, 1.11MB/s]
+ 52%|███████████████████▏                 | 26.5M/51.1M [00:23&lt;00:21, 1.13MB/s]
+ 52%|███████████████████▏                 | 26.6M/51.1M [00:23&lt;00:21, 1.12MB/s]
+ 52%|███████████████████▎                 | 26.7M/51.1M [00:23&lt;00:21, 1.14MB/s]
+ 53%|███████████████████▍                 | 26.9M/51.1M [00:24&lt;00:21, 1.14MB/s]
+ 53%|███████████████████▌                 | 27.0M/51.1M [00:24&lt;00:20, 1.16MB/s]
+ 53%|███████████████████▌                 | 27.1M/51.1M [00:24&lt;00:21, 1.14MB/s]
+ 53%|███████████████████▋                 | 27.2M/51.1M [00:24&lt;00:21, 1.13MB/s]
+ 53%|███████████████████▊                 | 27.3M/51.1M [00:24&lt;00:21, 1.13MB/s]
+ 54%|███████████████████▊                 | 27.4M/51.1M [00:24&lt;00:21, 1.12MB/s]
+ 54%|███████████████████▉                 | 27.6M/51.1M [00:24&lt;00:20, 1.13MB/s]
+ 54%|████████████████████                 | 27.7M/51.1M [00:24&lt;00:20, 1.14MB/s]
+ 54%|████████████████████▏                | 27.8M/51.1M [00:24&lt;00:20, 1.15MB/s]
+ 55%|████████████████████▏                | 27.9M/51.1M [00:24&lt;00:20, 1.15MB/s]
+ 55%|████████████████████▎                | 28.1M/51.1M [00:25&lt;00:19, 1.19MB/s]
+ 55%|████████████████████▍                | 28.2M/51.1M [00:25&lt;00:19, 1.19MB/s]
+ 55%|████████████████████▍                | 28.3M/51.1M [00:25&lt;00:19, 1.18MB/s]
+ 56%|████████████████████▌                | 28.4M/51.1M [00:25&lt;00:19, 1.18MB/s]
+ 56%|████████████████████▋                | 28.5M/51.1M [00:25&lt;00:19, 1.17MB/s]
+ 56%|████████████████████▊                | 28.7M/51.1M [00:25&lt;00:19, 1.15MB/s]
+ 56%|████████████████████▊                | 28.8M/51.1M [00:25&lt;00:19, 1.13MB/s]
+ 57%|████████████████████▉                | 28.9M/51.1M [00:25&lt;00:19, 1.12MB/s]
+ 57%|█████████████████████                | 29.0M/51.1M [00:25&lt;00:19, 1.11MB/s]
+ 57%|█████████████████████                | 29.1M/51.1M [00:25&lt;00:19, 1.10MB/s]
+ 57%|█████████████████████▏               | 29.2M/51.1M [00:26&lt;00:19, 1.10MB/s]
+ 57%|█████████████████████▎               | 29.4M/51.1M [00:26&lt;00:19, 1.13MB/s]
+ 58%|█████████████████████▎               | 29.5M/51.1M [00:26&lt;00:19, 1.13MB/s]
+ 58%|█████████████████████▍               | 29.6M/51.1M [00:26&lt;00:18, 1.14MB/s]
+ 58%|█████████████████████▌               | 29.7M/51.1M [00:26&lt;00:19, 1.11MB/s]
+ 58%|█████████████████████▌               | 29.9M/51.1M [00:26&lt;00:18, 1.12MB/s]
+ 59%|█████████████████████▋               | 30.0M/51.1M [00:26&lt;00:18, 1.13MB/s]
+ 59%|█████████████████████▊               | 30.1M/51.1M [00:26&lt;00:18, 1.13MB/s]
+ 59%|█████████████████████▉               | 30.2M/51.1M [00:26&lt;00:18, 1.13MB/s]
+ 59%|█████████████████████▉               | 30.4M/51.1M [00:27&lt;00:18, 1.14MB/s]
+ 60%|██████████████████████               | 30.5M/51.1M [00:27&lt;00:17, 1.15MB/s]
+ 60%|██████████████████████▏              | 30.6M/51.1M [00:27&lt;00:17, 1.15MB/s]
+ 60%|██████████████████████▎              | 30.7M/51.1M [00:27&lt;00:17, 1.15MB/s]
+ 60%|██████████████████████▎              | 30.9M/51.1M [00:27&lt;00:17, 1.13MB/s]
+ 61%|██████████████████████▍              | 31.0M/51.1M [00:27&lt;00:17, 1.12MB/s]
+ 61%|██████████████████████▍              | 31.1M/51.1M [00:27&lt;00:18, 1.09MB/s]
+ 61%|██████████████████████▌              | 31.2M/51.1M [00:27&lt;00:18, 1.08MB/s]
+ 61%|██████████████████████▋              | 31.3M/51.1M [00:27&lt;00:18, 1.06MB/s]
+ 61%|██████████████████████▋              | 31.4M/51.1M [00:28&lt;00:18, 1.06MB/s]
+ 62%|██████████████████████▊              | 31.5M/51.1M [00:28&lt;00:18, 1.06MB/s]
+ 62%|██████████████████████▉              | 31.7M/51.1M [00:28&lt;00:18, 1.07MB/s]
+ 62%|███████████████████████              | 31.8M/51.1M [00:28&lt;00:17, 1.10MB/s]
+ 62%|███████████████████████              | 31.9M/51.1M [00:28&lt;00:17, 1.11MB/s]
+ 63%|███████████████████████▏             | 32.0M/51.1M [00:28&lt;00:17, 1.12MB/s]
+ 63%|███████████████████████▎             | 32.1M/51.1M [00:28&lt;00:16, 1.13MB/s]
+ 63%|███████████████████████▎             | 32.2M/51.1M [00:28&lt;00:16, 1.13MB/s]
+ 63%|███████████████████████▍             | 32.4M/51.1M [00:28&lt;00:16, 1.12MB/s]
+ 64%|███████████████████████▌             | 32.5M/51.1M [00:28&lt;00:16, 1.11MB/s]
+ 64%|███████████████████████▌             | 32.6M/51.1M [00:29&lt;00:16, 1.11MB/s]
+ 64%|███████████████████████▋             | 32.7M/51.1M [00:29&lt;00:16, 1.11MB/s]
+ 64%|███████████████████████▊             | 32.8M/51.1M [00:29&lt;00:16, 1.10MB/s]
+ 64%|███████████████████████▊             | 32.9M/51.1M [00:29&lt;00:16, 1.09MB/s]
+ 65%|███████████████████████▉             | 33.0M/51.1M [00:29&lt;00:16, 1.07MB/s]
+ 65%|████████████████████████             | 33.2M/51.1M [00:29&lt;00:16, 1.08MB/s]
+ 65%|████████████████████████             | 33.3M/51.1M [00:29&lt;00:16, 1.08MB/s]
+ 65%|████████████████████████▏            | 33.4M/51.1M [00:29&lt;00:16, 1.09MB/s]
+ 66%|████████████████████████▎            | 33.5M/51.1M [00:29&lt;00:15, 1.11MB/s]
+ 66%|████████████████████████▎            | 33.6M/51.1M [00:30&lt;00:15, 1.12MB/s]
+ 66%|████████████████████████▍            | 33.8M/51.1M [00:30&lt;00:15, 1.12MB/s]
+ 66%|████████████████████████▌            | 33.9M/51.1M [00:30&lt;00:15, 1.10MB/s]
+ 66%|████████████████████████▌            | 34.0M/51.1M [00:30&lt;00:15, 1.10MB/s]
+ 67%|████████████████████████▋            | 34.1M/51.1M [00:30&lt;00:15, 1.12MB/s]
+ 67%|████████████████████████▊            | 34.2M/51.1M [00:30&lt;00:14, 1.13MB/s]
+ 67%|████████████████████████▊            | 34.4M/51.1M [00:30&lt;00:14, 1.13MB/s]
+ 67%|████████████████████████▉            | 34.5M/51.1M [00:30&lt;00:14, 1.13MB/s]
+ 68%|█████████████████████████            | 34.6M/51.1M [00:30&lt;00:14, 1.14MB/s]
+ 68%|█████████████████████████▏           | 34.7M/51.1M [00:31&lt;00:14, 1.15MB/s]
+ 68%|█████████████████████████▏           | 34.8M/51.1M [00:31&lt;00:14, 1.14MB/s]
+ 68%|█████████████████████████▎           | 35.0M/51.1M [00:31&lt;00:14, 1.13MB/s]
+ 69%|█████████████████████████▍           | 35.1M/51.1M [00:31&lt;00:14, 1.10MB/s]
+ 69%|█████████████████████████▍           | 35.2M/51.1M [00:31&lt;00:14, 1.08MB/s]
+ 69%|█████████████████████████▌           | 35.3M/51.1M [00:31&lt;00:14, 1.06MB/s]
+ 69%|█████████████████████████▋           | 35.4M/51.1M [00:31&lt;00:14, 1.08MB/s]
+ 70%|█████████████████████████▋           | 35.5M/51.1M [00:31&lt;00:14, 1.08MB/s]
+ 70%|█████████████████████████▊           | 35.7M/51.1M [00:31&lt;00:14, 1.08MB/s]
+ 70%|█████████████████████████▉           | 35.8M/51.1M [00:31&lt;00:14, 1.09MB/s]
+ 70%|█████████████████████████▉           | 35.9M/51.1M [00:32&lt;00:14, 1.09MB/s]
+ 70%|██████████████████████████           | 36.0M/51.1M [00:32&lt;00:13, 1.09MB/s]
+ 71%|██████████████████████████▏          | 36.1M/51.1M [00:32&lt;00:13, 1.13MB/s]
+ 71%|██████████████████████████▏          | 36.2M/51.1M [00:32&lt;00:13, 1.12MB/s]
+ 71%|██████████████████████████▎          | 36.4M/51.1M [00:32&lt;00:13, 1.11MB/s]
+ 71%|██████████████████████████▍          | 36.5M/51.1M [00:32&lt;00:13, 1.11MB/s]
+ 72%|██████████████████████████▍          | 36.6M/51.1M [00:32&lt;00:13, 1.10MB/s]
+ 72%|██████████████████████████▌          | 36.7M/51.1M [00:32&lt;00:13, 1.10MB/s]
+ 72%|██████████████████████████▋          | 36.8M/51.1M [00:32&lt;00:13, 1.09MB/s]
+ 72%|██████████████████████████▋          | 36.9M/51.1M [00:33&lt;00:12, 1.10MB/s]
+ 72%|██████████████████████████▊          | 37.0M/51.1M [00:33&lt;00:12, 1.10MB/s]
+ 73%|██████████████████████████▉          | 37.2M/51.1M [00:33&lt;00:12, 1.10MB/s]
+ 73%|██████████████████████████▉          | 37.3M/51.1M [00:33&lt;00:12, 1.10MB/s]
+ 73%|███████████████████████████          | 37.4M/51.1M [00:33&lt;00:12, 1.12MB/s]
+ 73%|███████████████████████████▏         | 37.5M/51.1M [00:33&lt;00:12, 1.11MB/s]
+ 74%|███████████████████████████▏         | 37.6M/51.1M [00:33&lt;00:12, 1.11MB/s]
+ 74%|███████████████████████████▎         | 37.7M/51.1M [00:33&lt;00:12, 1.10MB/s]
+ 74%|███████████████████████████▍         | 37.9M/51.1M [00:33&lt;00:12, 1.10MB/s]
+ 74%|███████████████████████████▍         | 38.0M/51.1M [00:33&lt;00:11, 1.10MB/s]
+ 75%|███████████████████████████▌         | 38.1M/51.1M [00:34&lt;00:11, 1.09MB/s]
+ 75%|███████████████████████████▋         | 38.2M/51.1M [00:34&lt;00:11, 1.11MB/s]
+ 75%|███████████████████████████▊         | 38.3M/51.1M [00:34&lt;00:11, 1.11MB/s]
+ 75%|███████████████████████████▊         | 38.5M/51.1M [00:34&lt;00:11, 1.10MB/s]
+ 75%|███████████████████████████▉         | 38.6M/51.1M [00:34&lt;00:11, 1.09MB/s]
+ 76%|████████████████████████████         | 38.7M/51.1M [00:34&lt;00:11, 1.09MB/s]
+ 76%|████████████████████████████         | 38.8M/51.1M [00:34&lt;00:11, 1.10MB/s]
+ 76%|████████████████████████████▏        | 38.9M/51.1M [00:34&lt;00:11, 1.10MB/s]
+ 76%|████████████████████████████▎        | 39.0M/51.1M [00:34&lt;00:11, 1.09MB/s]
+ 77%|████████████████████████████▎        | 39.2M/51.1M [00:35&lt;00:10, 1.10MB/s]
+ 77%|████████████████████████████▍        | 39.3M/51.1M [00:35&lt;00:10, 1.10MB/s]
+ 77%|████████████████████████████▌        | 39.4M/51.1M [00:35&lt;00:10, 1.09MB/s]
+ 77%|████████████████████████████▌        | 39.5M/51.1M [00:35&lt;00:10, 1.09MB/s]
+ 78%|████████████████████████████▋        | 39.6M/51.1M [00:35&lt;00:10, 1.09MB/s]
+ 78%|████████████████████████████▊        | 39.7M/51.1M [00:35&lt;00:10, 1.09MB/s]
+ 78%|████████████████████████████▊        | 39.8M/51.1M [00:35&lt;00:10, 1.10MB/s]
+ 78%|████████████████████████████▉        | 40.0M/51.1M [00:35&lt;00:09, 1.12MB/s]
+ 78%|█████████████████████████████        | 40.1M/51.1M [00:35&lt;00:09, 1.12MB/s]
+ 79%|█████████████████████████████        | 40.2M/51.1M [00:36&lt;00:09, 1.14MB/s]
+ 79%|█████████████████████████████▏       | 40.3M/51.1M [00:36&lt;00:09, 1.13MB/s]
+ 79%|█████████████████████████████▎       | 40.5M/51.1M [00:36&lt;00:09, 1.11MB/s]
+ 79%|█████████████████████████████▎       | 40.6M/51.1M [00:36&lt;00:09, 1.08MB/s]
+ 80%|█████████████████████████████▍       | 40.7M/51.1M [00:36&lt;00:09, 1.08MB/s]
+ 80%|█████████████████████████████▌       | 40.8M/51.1M [00:36&lt;00:09, 1.06MB/s]
+ 80%|█████████████████████████████▌       | 40.9M/51.1M [00:36&lt;00:09, 1.06MB/s]
+ 80%|█████████████████████████████▋       | 41.0M/51.1M [00:36&lt;00:09, 1.04MB/s]
+ 80%|█████████████████████████████▊       | 41.1M/51.1M [00:36&lt;00:09, 1.03MB/s]
+ 81%|█████████████████████████████▊       | 41.3M/51.1M [00:37&lt;00:09, 1.03MB/s]
+ 81%|█████████████████████████████▉       | 41.4M/51.1M [00:37&lt;00:09, 1.06MB/s]
+ 81%|██████████████████████████████       | 41.5M/51.1M [00:37&lt;00:09, 1.07MB/s]
+ 81%|██████████████████████████████       | 41.6M/51.1M [00:37&lt;00:08, 1.07MB/s]
+ 82%|██████████████████████████████▏      | 41.7M/51.1M [00:37&lt;00:08, 1.06MB/s]
+ 82%|██████████████████████████████▎      | 41.8M/51.1M [00:37&lt;00:08, 1.05MB/s]
+ 82%|██████████████████████████████▎      | 41.9M/51.1M [00:37&lt;00:08, 1.03MB/s]
+ 82%|██████████████████████████████▍      | 42.1M/51.1M [00:37&lt;00:08, 1.04MB/s]
+ 83%|██████████████████████████████▌      | 42.2M/51.1M [00:37&lt;00:08, 1.04MB/s]
+ 83%|██████████████████████████████▌      | 42.3M/51.1M [00:37&lt;00:08, 1.03MB/s]
+ 83%|██████████████████████████████▋      | 42.4M/51.1M [00:38&lt;00:08, 1.03MB/s]
+ 83%|██████████████████████████████▊      | 42.5M/51.1M [00:38&lt;00:08, 1.03MB/s]
+ 83%|██████████████████████████████▊      | 42.6M/51.1M [00:38&lt;00:08, 1.03MB/s]
+ 84%|██████████████████████████████▉      | 42.7M/51.1M [00:38&lt;00:08, 1.04MB/s]
+ 84%|███████████████████████████████      | 42.9M/51.1M [00:38&lt;00:07, 1.06MB/s]
+ 84%|███████████████████████████████      | 43.0M/51.1M [00:38&lt;00:07, 1.08MB/s]
+ 84%|███████████████████████████████▏     | 43.1M/51.1M [00:38&lt;00:07, 1.09MB/s]
+ 85%|███████████████████████████████▎     | 43.2M/51.1M [00:38&lt;00:07, 1.10MB/s]
+ 85%|███████████████████████████████▎     | 43.3M/51.1M [00:38&lt;00:07, 1.08MB/s]
+ 85%|███████████████████████████████▍     | 43.4M/51.1M [00:39&lt;00:07, 1.09MB/s]
+ 85%|███████████████████████████████▌     | 43.5M/51.1M [00:39&lt;00:06, 1.11MB/s]
+ 85%|███████████████████████████████▌     | 43.7M/51.1M [00:39&lt;00:06, 1.11MB/s]
+ 86%|███████████████████████████████▋     | 43.8M/51.1M [00:39&lt;00:06, 1.11MB/s]
+ 86%|███████████████████████████████▊     | 43.9M/51.1M [00:39&lt;00:06, 1.12MB/s]
+ 86%|███████████████████████████████▊     | 44.0M/51.1M [00:39&lt;00:06, 1.14MB/s]
+ 86%|███████████████████████████████▉     | 44.1M/51.1M [00:39&lt;00:06, 1.13MB/s]
+ 87%|████████████████████████████████     | 44.3M/51.1M [00:39&lt;00:06, 1.14MB/s]
+ 87%|████████████████████████████████▏    | 44.4M/51.1M [00:39&lt;00:05, 1.13MB/s]
+ 87%|████████████████████████████████▏    | 44.5M/51.1M [00:40&lt;00:05, 1.11MB/s]
+ 87%|████████████████████████████████▎    | 44.6M/51.1M [00:40&lt;00:05, 1.12MB/s]
+ 88%|████████████████████████████████▍    | 44.7M/51.1M [00:40&lt;00:05, 1.12MB/s]
+ 88%|████████████████████████████████▍    | 44.8M/51.1M [00:40&lt;00:05, 1.11MB/s]
+ 88%|████████████████████████████████▌    | 45.0M/51.1M [00:40&lt;00:05, 1.11MB/s]
+ 88%|████████████████████████████████▋    | 45.1M/51.1M [00:40&lt;00:05, 1.10MB/s]
+ 88%|████████████████████████████████▋    | 45.2M/51.1M [00:40&lt;00:05, 1.11MB/s]
+ 89%|████████████████████████████████▊    | 45.3M/51.1M [00:40&lt;00:05, 1.11MB/s]
+ 89%|████████████████████████████████▉    | 45.4M/51.1M [00:40&lt;00:05, 1.11MB/s]
+ 89%|████████████████████████████████▉    | 45.5M/51.1M [00:40&lt;00:04, 1.13MB/s]
+ 89%|█████████████████████████████████    | 45.7M/51.1M [00:41&lt;00:04, 1.13MB/s]
+ 90%|█████████████████████████████████▏   | 45.8M/51.1M [00:41&lt;00:04, 1.12MB/s]
+ 90%|█████████████████████████████████▏   | 45.9M/51.1M [00:41&lt;00:04, 1.12MB/s]
+ 90%|█████████████████████████████████▎   | 46.0M/51.1M [00:41&lt;00:04, 1.11MB/s]
+ 90%|█████████████████████████████████▍   | 46.1M/51.1M [00:41&lt;00:04, 1.14MB/s]
+ 90%|█████████████████████████████████▍   | 46.3M/51.1M [00:41&lt;00:04, 1.12MB/s]
+ 91%|█████████████████████████████████▌   | 46.4M/51.1M [00:41&lt;00:04, 1.12MB/s]
+ 91%|█████████████████████████████████▋   | 46.5M/51.1M [00:41&lt;00:04, 1.14MB/s]
+ 91%|█████████████████████████████████▊   | 46.6M/51.1M [00:41&lt;00:03, 1.16MB/s]
+ 91%|█████████████████████████████████▊   | 46.8M/51.1M [00:42&lt;00:03, 1.16MB/s]
+ 92%|█████████████████████████████████▉   | 46.9M/51.1M [00:42&lt;00:03, 1.15MB/s]
+ 92%|██████████████████████████████████   | 47.0M/51.1M [00:42&lt;00:03, 1.14MB/s]
+ 92%|██████████████████████████████████   | 47.1M/51.1M [00:42&lt;00:03, 1.14MB/s]
+ 92%|██████████████████████████████████▏  | 47.2M/51.1M [00:42&lt;00:03, 1.13MB/s]
+ 93%|██████████████████████████████████▎  | 47.3M/51.1M [00:42&lt;00:03, 1.14MB/s]
+ 93%|██████████████████████████████████▎  | 47.5M/51.1M [00:42&lt;00:03, 1.14MB/s]
+ 93%|██████████████████████████████████▍  | 47.6M/51.1M [00:42&lt;00:03, 1.13MB/s]
+ 93%|██████████████████████████████████▌  | 47.7M/51.1M [00:42&lt;00:02, 1.15MB/s]
+ 94%|██████████████████████████████████▋  | 47.8M/51.1M [00:42&lt;00:02, 1.15MB/s]
+ 94%|██████████████████████████████████▋  | 48.0M/51.1M [00:43&lt;00:02, 1.14MB/s]
+ 94%|██████████████████████████████████▊  | 48.1M/51.1M [00:43&lt;00:02, 1.14MB/s]
+ 94%|██████████████████████████████████▉  | 48.2M/51.1M [00:43&lt;00:02, 1.13MB/s]
+ 95%|██████████████████████████████████▉  | 48.3M/51.1M [00:43&lt;00:02, 1.11MB/s]
+ 95%|███████████████████████████████████  | 48.4M/51.1M [00:43&lt;00:02, 1.11MB/s]
+ 95%|███████████████████████████████████▏ | 48.5M/51.1M [00:43&lt;00:02, 1.09MB/s]
+ 95%|███████████████████████████████████▏ | 48.6M/51.1M [00:43&lt;00:02, 1.09MB/s]
+ 95%|███████████████████████████████████▎ | 48.8M/51.1M [00:43&lt;00:02, 1.08MB/s]
+ 96%|███████████████████████████████████▍ | 48.9M/51.1M [00:43&lt;00:01, 1.11MB/s]
+ 96%|███████████████████████████████████▍ | 49.0M/51.1M [00:44&lt;00:01, 1.11MB/s]
+ 96%|███████████████████████████████████▌ | 49.1M/51.1M [00:44&lt;00:01, 1.13MB/s]
+ 96%|███████████████████████████████████▋ | 49.3M/51.1M [00:44&lt;00:01, 1.13MB/s]
+ 97%|███████████████████████████████████▋ | 49.4M/51.1M [00:44&lt;00:01, 1.12MB/s]
+ 97%|███████████████████████████████████▊ | 49.5M/51.1M [00:44&lt;00:01, 1.12MB/s]
+ 97%|███████████████████████████████████▉ | 49.6M/51.1M [00:44&lt;00:01, 1.12MB/s]
+ 97%|███████████████████████████████████▉ | 49.7M/51.1M [00:44&lt;00:01, 1.12MB/s]
+ 97%|████████████████████████████████████ | 49.8M/51.1M [00:44&lt;00:01, 1.12MB/s]
+ 98%|████████████████████████████████████▏| 49.9M/51.1M [00:44&lt;00:01, 1.11MB/s]
+ 98%|████████████████████████████████████▏| 50.1M/51.1M [00:44&lt;00:00, 1.14MB/s]
+ 98%|████████████████████████████████████▎| 50.2M/51.1M [00:45&lt;00:00, 1.14MB/s]
+ 98%|████████████████████████████████████▍| 50.3M/51.1M [00:45&lt;00:00, 1.14MB/s]
+ 99%|████████████████████████████████████▌| 50.4M/51.1M [00:45&lt;00:00, 1.13MB/s]
+ 99%|████████████████████████████████████▌| 50.5M/51.1M [00:45&lt;00:00, 1.13MB/s]
+ 99%|████████████████████████████████████▋| 50.7M/51.1M [00:45&lt;00:00, 1.12MB/s]
+ 99%|████████████████████████████████████▊| 50.8M/51.1M [00:45&lt;00:00, 1.11MB/s]
+100%|████████████████████████████████████▊| 50.9M/51.1M [00:45&lt;00:00, 1.12MB/s]
+100%|████████████████████████████████████▉| 51.0M/51.1M [00:45&lt;00:00, 1.11MB/s]
   0%|                                              | 0.00/51.1M [00:00&lt;?, ?B/s]
-100%|██████████████████████████████████████| 51.1M/51.1M [00:00&lt;00:00, 130GB/s]
+100%|██████████████████████████████████████| 51.1M/51.1M [00:00&lt;00:00, 276GB/s]
 
   0%|                                              | 0.00/3.90k [00:00&lt;?, ?B/s]
   0%|                                              | 0.00/3.90k [00:00&lt;?, ?B/s]
-100%|█████████████████████████████████████| 3.90k/3.90k [00:00&lt;00:00, 22.4MB/s]
-Download complete in 51s (48.7 MB)
+100%|█████████████████████████████████████| 3.90k/3.90k [00:00&lt;00:00, 23.4MB/s]
+Download complete in 46s (48.7 MB)
 Extracting EDF parameters from /home/runner/mne_data/physionet-sleep-data/SC4001E0-PSG.edf...
 EDF file detected
 Setting channel info structure...
@@ -1114,8 +1087,8 @@
 - Upper transition bandwidth: 7.50 Hz (-6 dB cutoff frequency: 33.75 Hz)
 - Filter length: 45 samples (0.450 s)
 
-Writing /tmp/tmprkujhpaz/0/0-raw.fif
-Closing /tmp/tmprkujhpaz/0/0-raw.fif
+Writing /tmp/tmprqo1r57a/0/0-raw.fif
+Closing /tmp/tmprqo1r57a/0/0-raw.fif
 [done]
 Reading 0 ... 3260000  =      0.000 ... 32600.000 secs...
 Filtering raw data in 1 contiguous segment
@@ -1130,38 +1103,38 @@
 - Upper transition bandwidth: 7.50 Hz (-6 dB cutoff frequency: 33.75 Hz)
 - Filter length: 45 samples (0.450 s)
 
-Writing /tmp/tmprkujhpaz/1/1-raw.fif
-Closing /tmp/tmprkujhpaz/1/1-raw.fif
+Writing /tmp/tmprqo1r57a/1/1-raw.fif
+Closing /tmp/tmprqo1r57a/1/1-raw.fif
 [done]
-/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmprkujhpaz contains other subdirectories or files [&#39;0&#39;].
+/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmprqo1r57a contains other subdirectories or files [&#39;0&#39;].
   warnings.warn(f&#39;Chosen directory {path} contains other &#39;
-Opening raw data file /tmp/tmprkujhpaz/0/0-raw.fif...
+Opening raw data file /tmp/tmprqo1r57a/0/0-raw.fif...
 Isotrak not found
     Range : 2884000 ... 5391000 =  28840.000 ... 53910.000 secs
 Ready.
-Opening raw data file /tmp/tmprkujhpaz/1/1-raw.fif...
+Opening raw data file /tmp/tmprqo1r57a/1/1-raw.fif...
 Isotrak not found
     Range : 1975000 ... 5235000 =  19750.000 ... 52350.000 secs
 Ready.
 Reading 0 ... 2507000  =      0.000 ... 25070.000 secs...
-Writing /tmp/tmprkujhpaz/0/0-raw.fif
-Closing /tmp/tmprkujhpaz/0/0-raw.fif
+Writing /tmp/tmprqo1r57a/0/0-raw.fif
+Closing /tmp/tmprqo1r57a/0/0-raw.fif
 [done]
 /home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:700: UserWarning: The number of saved datasets (1) does not match the number of existing subdirectories (2). You may now encounter a mix of differently preprocessed datasets!
   warnings.warn(f&quot;The number of saved datasets ({i_ds+1+offset}) &quot;
-/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmprkujhpaz contains other subdirectories or files [&#39;1&#39;].
+/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmprqo1r57a contains other subdirectories or files [&#39;1&#39;].
   warnings.warn(f&#39;Chosen directory {path} contains other &#39;
 Reading 0 ... 3260000  =      0.000 ... 32600.000 secs...
-Writing /tmp/tmprkujhpaz/1/1-raw.fif
-Closing /tmp/tmprkujhpaz/1/1-raw.fif
+Writing /tmp/tmprqo1r57a/1/1-raw.fif
+Closing /tmp/tmprqo1r57a/1/1-raw.fif
 [done]
-/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmprkujhpaz contains other subdirectories or files [&#39;0&#39;].
+/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmprqo1r57a contains other subdirectories or files [&#39;0&#39;].
   warnings.warn(f&#39;Chosen directory {path} contains other &#39;
-Opening raw data file /tmp/tmprkujhpaz/0/0-raw.fif...
+Opening raw data file /tmp/tmprqo1r57a/0/0-raw.fif...
 Isotrak not found
     Range : 2884000 ... 5391000 =  28840.000 ... 53910.000 secs
 Ready.
-Opening raw data file /tmp/tmprkujhpaz/1/1-raw.fif...
+Opening raw data file /tmp/tmprqo1r57a/1/1-raw.fif...
 Isotrak not found
     Range : 1975000 ... 5235000 =  19750.000 ... 52350.000 secs
 Ready.
@@ -1173,19 +1146,19 @@
 EDF file detected
 Setting channel info structure...
 Creating raw.info structure...
-Opening raw data file /tmp/tmp0g57aua5/0/0-raw.fif...
+Opening raw data file /tmp/tmp8bd4vm1l/0/0-raw.fif...
 Isotrak not found
     Range : 2884000 ... 5391000 =  28840.000 ... 53910.000 secs
 Ready.
-Opening raw data file /tmp/tmp0g57aua5/1/1-raw.fif...
+Opening raw data file /tmp/tmp8bd4vm1l/1/1-raw.fif...
 Isotrak not found
     Range : 1975000 ... 5235000 =  19750.000 ... 52350.000 secs
 Ready.
-Opening raw data file /tmp/tmp0g57aua5/0/0-raw.fif...
+Opening raw data file /tmp/tmp8bd4vm1l/0/0-raw.fif...
 Isotrak not found
     Range : 2884000 ... 5391000 =  28840.000 ... 53910.000 secs
 Ready.
-Opening raw data file /tmp/tmp0g57aua5/1/1-raw.fif...
+Opening raw data file /tmp/tmp8bd4vm1l/1/1-raw.fif...
 Isotrak not found
     Range : 1975000 ... 5235000 =  19750.000 ... 52350.000 secs
 Ready.
@@ -1252,8 +1225,8 @@
 - Upper transition bandwidth: 7.50 Hz (-6 dB cutoff frequency: 33.75 Hz)
 - Filter length: 45 samples (0.450 s)
 
-Writing /tmp/tmpej2cwuxz/0/0-raw.fif
-Closing /tmp/tmpej2cwuxz/0/0-raw.fif
+Writing /tmp/tmpmhmgkrsv/0/0-raw.fif
+Closing /tmp/tmpmhmgkrsv/0/0-raw.fif
 [done]
 Reading 0 ... 3260000  =      0.000 ... 32600.000 secs...
 Filtering raw data in 1 contiguous segment
@@ -1268,38 +1241,38 @@
 - Upper transition bandwidth: 7.50 Hz (-6 dB cutoff frequency: 33.75 Hz)
 - Filter length: 45 samples (0.450 s)
 
-Writing /tmp/tmpej2cwuxz/1/1-raw.fif
-Closing /tmp/tmpej2cwuxz/1/1-raw.fif
+Writing /tmp/tmpmhmgkrsv/1/1-raw.fif
+Closing /tmp/tmpmhmgkrsv/1/1-raw.fif
 [done]
-/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmpej2cwuxz contains other subdirectories or files [&#39;0&#39;].
+/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmpmhmgkrsv contains other subdirectories or files [&#39;0&#39;].
   warnings.warn(f&#39;Chosen directory {path} contains other &#39;
-Opening raw data file /tmp/tmpej2cwuxz/0/0-raw.fif...
+Opening raw data file /tmp/tmpmhmgkrsv/0/0-raw.fif...
 Isotrak not found
     Range : 2884000 ... 5391000 =  28840.000 ... 53910.000 secs
 Ready.
-Opening raw data file /tmp/tmpej2cwuxz/1/1-raw.fif...
+Opening raw data file /tmp/tmpmhmgkrsv/1/1-raw.fif...
 Isotrak not found
     Range : 1975000 ... 5235000 =  19750.000 ... 52350.000 secs
 Ready.
 Reading 0 ... 2507000  =      0.000 ... 25070.000 secs...
-Writing /tmp/tmpej2cwuxz/0/0-raw.fif
-Closing /tmp/tmpej2cwuxz/0/0-raw.fif
+Writing /tmp/tmpmhmgkrsv/0/0-raw.fif
+Closing /tmp/tmpmhmgkrsv/0/0-raw.fif
 [done]
 /home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:700: UserWarning: The number of saved datasets (1) does not match the number of existing subdirectories (2). You may now encounter a mix of differently preprocessed datasets!
   warnings.warn(f&quot;The number of saved datasets ({i_ds+1+offset}) &quot;
-/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmpej2cwuxz contains other subdirectories or files [&#39;1&#39;].
+/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmpmhmgkrsv contains other subdirectories or files [&#39;1&#39;].
   warnings.warn(f&#39;Chosen directory {path} contains other &#39;
 Reading 0 ... 3260000  =      0.000 ... 32600.000 secs...
-Writing /tmp/tmpej2cwuxz/1/1-raw.fif
-Closing /tmp/tmpej2cwuxz/1/1-raw.fif
+Writing /tmp/tmpmhmgkrsv/1/1-raw.fif
+Closing /tmp/tmpmhmgkrsv/1/1-raw.fif
 [done]
-/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmpej2cwuxz contains other subdirectories or files [&#39;0&#39;].
+/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmpmhmgkrsv contains other subdirectories or files [&#39;0&#39;].
   warnings.warn(f&#39;Chosen directory {path} contains other &#39;
-Opening raw data file /tmp/tmpej2cwuxz/0/0-raw.fif...
+Opening raw data file /tmp/tmpmhmgkrsv/0/0-raw.fif...
 Isotrak not found
     Range : 2884000 ... 5391000 =  28840.000 ... 53910.000 secs
 Ready.
-Opening raw data file /tmp/tmpej2cwuxz/1/1-raw.fif...
+Opening raw data file /tmp/tmpmhmgkrsv/1/1-raw.fif...
 Isotrak not found
     Range : 1975000 ... 5235000 =  19750.000 ... 52350.000 secs
 Ready.
@@ -1311,19 +1284,19 @@
 EDF file detected
 Setting channel info structure...
 Creating raw.info structure...
-Opening raw data file /tmp/tmpjf9zhor8/0/0-raw.fif...
+Opening raw data file /tmp/tmp5_t3lhz9/0/0-raw.fif...
 Isotrak not found
     Range : 2884000 ... 5391000 =  28840.000 ... 53910.000 secs
 Ready.
-Opening raw data file /tmp/tmpjf9zhor8/1/1-raw.fif...
+Opening raw data file /tmp/tmp5_t3lhz9/1/1-raw.fif...
 Isotrak not found
     Range : 1975000 ... 5235000 =  19750.000 ... 52350.000 secs
 Ready.
-Opening raw data file /tmp/tmpjf9zhor8/0/0-raw.fif...
+Opening raw data file /tmp/tmp5_t3lhz9/0/0-raw.fif...
 Isotrak not found
     Range : 2884000 ... 5391000 =  28840.000 ... 53910.000 secs
 Ready.
-Opening raw data file /tmp/tmpjf9zhor8/1/1-raw.fif...
+Opening raw data file /tmp/tmp5_t3lhz9/1/1-raw.fif...
 Isotrak not found
     Range : 1975000 ... 5235000 =  19750.000 ... 52350.000 secs
 Ready.
@@ -1396,8 +1369,8 @@
 Depending on available resources (e.g. in limited memory settings), it might
 therefore be more advantageous to use both parallelization and serialization
 together.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 43.430 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  156 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 27.521 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  240 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-datasets-io-plot-benchmark-preprocessing-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/60d8dafd5347638108915bae984c26bd/plot_benchmark_preprocessing.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_benchmark_preprocessing.py</span></code></a></p>
diff --git a/dev/auto_examples/datasets_io/plot_custom_dataset_example.html b/dev/auto_examples/datasets_io/plot_custom_dataset_example.html
index 2f02ce55..c71f6ff0 100644
--- a/dev/auto_examples/datasets_io/plot_custom_dataset_example.html
+++ b/dev/auto_examples/datasets_io/plot_custom_dataset_example.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Custom Dataset Example &#8212; Braindecode 0.8 documentation</title>
+    <title>Custom Dataset Example &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -673,8 +673,8 @@
 start_ind=0 -- stop_ind=500
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 2.871 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  10 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 2.209 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  9 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-datasets-io-plot-custom-dataset-example-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/b3d02314404fffecf4e64263b47762f1/plot_custom_dataset_example.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_custom_dataset_example.py</span></code></a></p>
diff --git a/dev/auto_examples/datasets_io/plot_load_save_datasets.html b/dev/auto_examples/datasets_io/plot_load_save_datasets.html
index bb68c173..b7a3d4bb 100644
--- a/dev/auto_examples/datasets_io/plot_load_save_datasets.html
+++ b/dev/auto_examples/datasets_io/plot_load_save_datasets.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Load and save dataset example &#8212; Braindecode 0.8 documentation</title>
+    <title>Load and save dataset example &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -584,7 +584,7 @@
 48 events found
 Event IDs: [1 2 3 4]
 
-&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f4b813bc280&gt;
+&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f313110b610&gt;
 </pre></div>
 </div>
 <p>We save the dataset to a an existing directory. It will create a ‘.fif’ file
@@ -600,41 +600,41 @@
 <span class="p">)</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Writing /tmp/tmpl8p_rszc/0/0-raw.fif
-Closing /tmp/tmpl8p_rszc/0/0-raw.fif
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Writing /tmp/tmpvkqehedo/0/0-raw.fif
+Closing /tmp/tmpvkqehedo/0/0-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/1/1-raw.fif
-Closing /tmp/tmpl8p_rszc/1/1-raw.fif
+Writing /tmp/tmpvkqehedo/1/1-raw.fif
+Closing /tmp/tmpvkqehedo/1/1-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/2/2-raw.fif
-Closing /tmp/tmpl8p_rszc/2/2-raw.fif
+Writing /tmp/tmpvkqehedo/2/2-raw.fif
+Closing /tmp/tmpvkqehedo/2/2-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/3/3-raw.fif
-Closing /tmp/tmpl8p_rszc/3/3-raw.fif
+Writing /tmp/tmpvkqehedo/3/3-raw.fif
+Closing /tmp/tmpvkqehedo/3/3-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/4/4-raw.fif
-Closing /tmp/tmpl8p_rszc/4/4-raw.fif
+Writing /tmp/tmpvkqehedo/4/4-raw.fif
+Closing /tmp/tmpvkqehedo/4/4-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/5/5-raw.fif
-Closing /tmp/tmpl8p_rszc/5/5-raw.fif
+Writing /tmp/tmpvkqehedo/5/5-raw.fif
+Closing /tmp/tmpvkqehedo/5/5-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/6/6-raw.fif
-Closing /tmp/tmpl8p_rszc/6/6-raw.fif
+Writing /tmp/tmpvkqehedo/6/6-raw.fif
+Closing /tmp/tmpvkqehedo/6/6-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/7/7-raw.fif
-Closing /tmp/tmpl8p_rszc/7/7-raw.fif
+Writing /tmp/tmpvkqehedo/7/7-raw.fif
+Closing /tmp/tmpvkqehedo/7/7-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/8/8-raw.fif
-Closing /tmp/tmpl8p_rszc/8/8-raw.fif
+Writing /tmp/tmpvkqehedo/8/8-raw.fif
+Closing /tmp/tmpvkqehedo/8/8-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/9/9-raw.fif
-Closing /tmp/tmpl8p_rszc/9/9-raw.fif
+Writing /tmp/tmpvkqehedo/9/9-raw.fif
+Closing /tmp/tmpvkqehedo/9/9-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/10/10-raw.fif
-Closing /tmp/tmpl8p_rszc/10/10-raw.fif
+Writing /tmp/tmpvkqehedo/10/10-raw.fif
+Closing /tmp/tmpvkqehedo/10/10-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/11/11-raw.fif
-Closing /tmp/tmpl8p_rszc/11/11-raw.fif
+Writing /tmp/tmpvkqehedo/11/11-raw.fif
+Closing /tmp/tmpvkqehedo/11/11-raw.fif
 [done]
 </pre></div>
 </div>
@@ -652,11 +652,11 @@
 <span class="p">)</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opening raw data file /tmp/tmpl8p_rszc/1/1-raw.fif...
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opening raw data file /tmp/tmpvkqehedo/1/1-raw.fif...
     Range : 0 ... 3868 =      0.000 ...   386.800 secs
 Ready.
 Reading 0 ... 3868  =      0.000 ...   386.800 secs...
-Opening raw data file /tmp/tmpl8p_rszc/3/3-raw.fif...
+Opening raw data file /tmp/tmpvkqehedo/3/3-raw.fif...
     Range : 0 ... 3868 =      0.000 ...   386.800 secs
 Ready.
 Reading 0 ... 3868  =      0.000 ...   386.800 secs...
@@ -731,15 +731,15 @@
 <span class="p">)</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Writing /tmp/tmpl8p_rszc/0/0-raw.fif
-Closing /tmp/tmpl8p_rszc/0/0-raw.fif
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Writing /tmp/tmpvkqehedo/0/0-raw.fif
+Closing /tmp/tmpvkqehedo/0/0-raw.fif
 [done]
-Writing /tmp/tmpl8p_rszc/1/1-raw.fif
-Closing /tmp/tmpl8p_rszc/1/1-raw.fif
+Writing /tmp/tmpvkqehedo/1/1-raw.fif
+Closing /tmp/tmpvkqehedo/1/1-raw.fif
 [done]
 /home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:700: UserWarning: The number of saved datasets (2) does not match the number of existing subdirectories (12). You may now encounter a mix of differently preprocessed datasets!
   warnings.warn(f&quot;The number of saved datasets ({i_ds+1+offset}) &quot;
-/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmpl8p_rszc contains other subdirectories or files [&#39;8&#39;, &#39;7&#39;, &#39;10&#39;, &#39;5&#39;, &#39;4&#39;, &#39;9&#39;, &#39;3&#39;, &#39;2&#39;, &#39;6&#39;, &#39;11&#39;].
+/home/runner/work/braindecode/braindecode/braindecode/datasets/base.py:708: UserWarning: Chosen directory /tmp/tmpvkqehedo contains other subdirectories or files [&#39;8&#39;, &#39;7&#39;, &#39;10&#39;, &#39;5&#39;, &#39;4&#39;, &#39;9&#39;, &#39;3&#39;, &#39;2&#39;, &#39;6&#39;, &#39;11&#39;].
   warnings.warn(f&#39;Chosen directory {path} contains other &#39;
 </pre></div>
 </div>
@@ -756,7 +756,7 @@
 <a href="../../generated/braindecode.datasets.BaseConcatDataset.html#braindecode.datasets.BaseConcatDataset" title="braindecode.datasets.BaseConcatDataset" class="sphx-glr-backref-module-braindecode-datasets sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">windows_dataset_loaded</span></a><span class="o">.</span><span class="n">description</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opening raw data file /tmp/tmpl8p_rszc/0/0-raw.fif...
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opening raw data file /tmp/tmpvkqehedo/0/0-raw.fif...
     Range : 0 ... 3868 =      0.000 ...   386.800 secs
 Ready.
 </pre></div>
@@ -797,8 +797,8 @@
 </div>
 </div>
 <br />
-<br /><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 6.845 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  269 MB</p>
+<br /><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 5.025 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  10 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-datasets-io-plot-load-save-datasets-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/76b6af988880f614494e6948dcfe4128/plot_load_save_datasets.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_load_save_datasets.py</span></code></a></p>
diff --git a/dev/auto_examples/datasets_io/plot_mne_dataset_example.html b/dev/auto_examples/datasets_io/plot_mne_dataset_example.html
index 310f63ec..fb26dd30 100644
--- a/dev/auto_examples/datasets_io/plot_mne_dataset_example.html
+++ b/dev/auto_examples/datasets_io/plot_mne_dataset_example.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>MNE Dataset Example &#8212; Braindecode 0.8 documentation</title>
+    <title>MNE Dataset Example &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -746,8 +746,8 @@
 </div>
 </div>
 <br />
-<br /><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.938 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  10 MB</p>
+<br /><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.455 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  9 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-datasets-io-plot-mne-dataset-example-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/885d9ee3c77215b539444b199aa0fd1b/plot_mne_dataset_example.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_mne_dataset_example.py</span></code></a></p>
diff --git a/dev/auto_examples/datasets_io/plot_moabb_dataset_example.html b/dev/auto_examples/datasets_io/plot_moabb_dataset_example.html
index b69a8521..dd5e602b 100644
--- a/dev/auto_examples/datasets_io/plot_moabb_dataset_example.html
+++ b/dev/auto_examples/datasets_io/plot_moabb_dataset_example.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>MOABB Dataset Example &#8212; Braindecode 0.8 documentation</title>
+    <title>MOABB Dataset Example &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -728,8 +728,8 @@
 <p>See our <a class="reference external" href="../model_building/plot_bcic_iv_2a_moabb_trial.html">Trialwise Decoding</a> and
 <a class="reference external" href="../model_building/plot_bcic_iv_2a_moabb_cropped.html">Cropped Decoding</a> examples for
 training with this dataset.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 6.793 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  294 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 4.790 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  9 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-datasets-io-plot-moabb-dataset-example-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/fea70b19933793ddf91e286b398628af/plot_moabb_dataset_example.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_moabb_dataset_example.py</span></code></a></p>
diff --git a/dev/auto_examples/datasets_io/plot_split_dataset.html b/dev/auto_examples/datasets_io/plot_split_dataset.html
index 0fe60400..c65c5703 100644
--- a/dev/auto_examples/datasets_io/plot_split_dataset.html
+++ b/dev/auto_examples/datasets_io/plot_split_dataset.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Split Dataset Example &#8212; Braindecode 0.8 documentation</title>
+    <title>Split Dataset Example &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -663,7 +663,7 @@ <h3><a class="toc-backref" href="#id3" role="doc-backlink">By description inform
 <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">splits</span></a><span class="p">[</span><span class="s2">&quot;4&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">description</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b71546b00&gt;, &#39;1&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d55d0&gt;, &#39;2&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d6380&gt;, &#39;3&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d61d0&gt;, &#39;4&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d75e0&gt;, &#39;5&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d54e0&gt;}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312dda4e20&gt;, &#39;1&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312dda6fb0&gt;, &#39;2&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312dda68f0&gt;, &#39;3&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312dda6b60&gt;, &#39;4&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb0e50&gt;, &#39;5&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb0dc0&gt;}
 </pre></div>
 </div>
 <div class="output_subarea output_html rendered_html output_result">
@@ -719,7 +719,7 @@ <h3><a class="toc-backref" href="#id4" role="doc-backlink">By row index</a><a cl
 <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">splits</span></a><span class="p">[</span><span class="s2">&quot;0&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">description</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b715463b0&gt;}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f3130eed3c0&gt;}
 </pre></div>
 </div>
 <div class="output_subarea output_html rendered_html output_result">
@@ -779,7 +779,7 @@ <h3><a class="toc-backref" href="#id4" role="doc-backlink">By row index</a><a cl
 <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">splits</span></a><span class="p">[</span><span class="s2">&quot;2&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">description</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d6410&gt;, &#39;1&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d5bd0&gt;, &#39;2&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d7880&gt;}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f3130eee6b0&gt;, &#39;1&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f3130eed4e0&gt;, &#39;2&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb22f0&gt;}
 </pre></div>
 </div>
 <div class="output_subarea output_html rendered_html output_result">
@@ -857,7 +857,7 @@ <h3><a class="toc-backref" href="#id4" role="doc-backlink">By row index</a><a cl
 <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">splits</span></a><span class="p">[</span><span class="s2">&quot;test&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">description</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;train&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d5c90&gt;, &#39;valid&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d5090&gt;, &#39;test&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b714d4580&gt;}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;train&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f3130eed3c0&gt;, &#39;valid&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb0a90&gt;, &#39;test&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb3340&gt;}
 </pre></div>
 </div>
 <div class="output_subarea output_html rendered_html output_result">
@@ -973,20 +973,20 @@ <h2><a class="toc-backref" href="#id5" role="doc-backlink">Observation</a><a cla
 </pre></div>
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Using description info
-{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153e050&gt;, &#39;1&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153c730&gt;, &#39;2&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153ef80&gt;, &#39;3&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153c760&gt;, &#39;4&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153f9a0&gt;, &#39;5&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153d270&gt;}
+{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb19c0&gt;, &#39;1&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb1090&gt;, &#39;2&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb1e40&gt;, &#39;3&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb3a00&gt;, &#39;4&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb0af0&gt;, &#39;5&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb2680&gt;}
 
 Splitting by row index
-{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153e3e0&gt;}
+{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f3130eef9d0&gt;}
 
 Multiple row index split
-{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153f4f0&gt;, &#39;1&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153f760&gt;}
+{&#39;0&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb2680&gt;, &#39;1&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb0af0&gt;}
 
 Specifying keys
-{&#39;train&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153efb0&gt;, &#39;test&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f4b8153e7a0&gt;}
+{&#39;train&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f3130eed3c0&gt;, &#39;test&#39;: &lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f312ddb3a00&gt;}
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 6.562 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  295 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 4.817 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  9 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-datasets-io-plot-split-dataset-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/8cc351cf606ecc565831d11752d2d9a2/plot_split_dataset.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_split_dataset.py</span></code></a></p>
diff --git a/dev/auto_examples/datasets_io/plot_tuh_discrete_multitarget.html b/dev/auto_examples/datasets_io/plot_tuh_discrete_multitarget.html
index 516597cc..83674a88 100644
--- a/dev/auto_examples/datasets_io/plot_tuh_discrete_multitarget.html
+++ b/dev/auto_examples/datasets_io/plot_tuh_discrete_multitarget.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Multiple discrete targets with the TUH EEG Corpus &#8212; Braindecode 0.8 documentation</title>
+    <title>Multiple discrete targets with the TUH EEG Corpus &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -707,7 +707,7 @@ <h2>Exploring DataLoader<a class="headerlink" href="#exploring-dataloader" title
 batch_ind=[tensor([0, 1, 2, 3]), tensor([   0, 1000, 2000, 2600]), tensor([1000, 2000, 3000, 3600])]
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 4.127 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 3.176 seconds)</p>
 <p><strong>Estimated memory usage:</strong>  10 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-datasets-io-plot-tuh-discrete-multitarget-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
diff --git a/dev/auto_examples/datasets_io/sg_execution_times.html b/dev/auto_examples/datasets_io/sg_execution_times.html
index 93c8e73f..07f1d61b 100644
--- a/dev/auto_examples/datasets_io/sg_execution_times.html
+++ b/dev/auto_examples/datasets_io/sg_execution_times.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Computation times &#8212; Braindecode 0.8 documentation</title>
+    <title>Computation times &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -444,36 +444,36 @@
   
   <section id="computation-times">
 <span id="sphx-glr-auto-examples-datasets-io-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">#</a></h1>
-<p><strong>02:12.565</strong> total execution time for <strong>auto_examples_datasets_io</strong> files:</p>
+<p><strong>01:48.993</strong> total execution time for <strong>auto_examples_datasets_io</strong> files:</p>
 <table class="table">
 <tbody>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_benchmark_preprocessing.html#sphx-glr-auto-examples-datasets-io-plot-benchmark-preprocessing-py"><span class="std std-ref">Benchmarking preprocessing with parallelization and serialization</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_benchmark_preprocessing.py</span></code>)</p></td>
-<td><p>01:43.430</p></td>
-<td><p>156.5 MB</p></td>
+<td><p>01:27.521</p></td>
+<td><p>239.8 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_load_save_datasets.html#sphx-glr-auto-examples-datasets-io-plot-load-save-datasets-py"><span class="std std-ref">Load and save dataset example</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_load_save_datasets.py</span></code>)</p></td>
-<td><p>00:06.845</p></td>
-<td><p>269.2 MB</p></td>
+<td><p>00:05.025</p></td>
+<td><p>10.4 MB</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="plot_moabb_dataset_example.html#sphx-glr-auto-examples-datasets-io-plot-moabb-dataset-example-py"><span class="std std-ref">MOABB Dataset Example</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_moabb_dataset_example.py</span></code>)</p></td>
-<td><p>00:06.793</p></td>
-<td><p>294.0 MB</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="plot_split_dataset.html#sphx-glr-auto-examples-datasets-io-plot-split-dataset-py"><span class="std std-ref">Split Dataset Example</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_split_dataset.py</span></code>)</p></td>
+<td><p>00:04.817</p></td>
+<td><p>9.4 MB</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="plot_split_dataset.html#sphx-glr-auto-examples-datasets-io-plot-split-dataset-py"><span class="std std-ref">Split Dataset Example</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_split_dataset.py</span></code>)</p></td>
-<td><p>00:06.562</p></td>
-<td><p>295.0 MB</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="plot_moabb_dataset_example.html#sphx-glr-auto-examples-datasets-io-plot-moabb-dataset-example-py"><span class="std std-ref">MOABB Dataset Example</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_moabb_dataset_example.py</span></code>)</p></td>
+<td><p>00:04.790</p></td>
+<td><p>9.4 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_tuh_discrete_multitarget.html#sphx-glr-auto-examples-datasets-io-plot-tuh-discrete-multitarget-py"><span class="std std-ref">Multiple discrete targets with the TUH EEG Corpus</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_tuh_discrete_multitarget.py</span></code>)</p></td>
-<td><p>00:04.127</p></td>
-<td><p>10.2 MB</p></td>
+<td><p>00:03.176</p></td>
+<td><p>10.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_custom_dataset_example.html#sphx-glr-auto-examples-datasets-io-plot-custom-dataset-example-py"><span class="std std-ref">Custom Dataset Example</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_custom_dataset_example.py</span></code>)</p></td>
-<td><p>00:02.871</p></td>
-<td><p>9.5 MB</p></td>
+<td><p>00:02.209</p></td>
+<td><p>9.4 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_mne_dataset_example.html#sphx-glr-auto-examples-datasets-io-plot-mne-dataset-example-py"><span class="std std-ref">MNE Dataset Example</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_mne_dataset_example.py</span></code>)</p></td>
-<td><p>00:01.938</p></td>
-<td><p>9.5 MB</p></td>
+<td><p>00:01.455</p></td>
+<td><p>9.4 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="benchmark_lazy_eager_loading.html#sphx-glr-auto-examples-datasets-io-benchmark-lazy-eager-loading-py"><span class="std std-ref">Benchmarking eager and lazy loading</span></a> (<code class="docutils literal notranslate"><span class="pre">benchmark_lazy_eager_loading.py</span></code>)</p></td>
 <td><p>00:00.000</p></td>
diff --git a/dev/auto_examples/index.html b/dev/auto_examples/index.html
index 868b8c9d..d9bc03a9 100644
--- a/dev/auto_examples/index.html
+++ b/dev/auto_examples/index.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Examples &#8212; Braindecode 0.8 documentation</title>
+    <title>Examples &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/auto_examples/model_building/index.html b/dev/auto_examples/model_building/index.html
index 0a2ae88c..c26aefeb 100644
--- a/dev/auto_examples/model_building/index.html
+++ b/dev/auto_examples/model_building/index.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Basic model building and training &#8212; Braindecode 0.8 documentation</title>
+    <title>Basic model building and training &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/auto_examples/model_building/plot_basic_training_epochs.html b/dev/auto_examples/model_building/plot_basic_training_epochs.html
index 10b0bda6..f45ab313 100644
--- a/dev/auto_examples/model_building/plot_basic_training_epochs.html
+++ b/dev/auto_examples/model_building/plot_basic_training_epochs.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Simple training on MNE epochs &#8212; Braindecode 0.8 documentation</title>
+    <title>Simple training on MNE epochs &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -775,16 +775,16 @@ <h2><a class="toc-backref" href="#id7" role="doc-backlink">Training your model (
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    valid_acc    valid_loss     dur
 -------  -----------  ------------  ------
-      1       0.2000       40.6926  0.0767
-      2       0.2000       40.6926  0.0114
-      3       0.2000       40.6926  0.0099
-      4       0.2000       40.6926  0.0099
-      5       0.2000       40.6926  0.0100
-      6       0.2000       40.6926  0.0099
-      7       0.2000       40.6926  0.0101
-      8       0.2000       40.6926  0.0102
-      9       0.2000       40.6926  0.0102
-     10       0.2000       40.6926  0.0104
+      1       0.3000       44.8816  0.0141
+      2       0.3000       44.8816  0.0085
+      3       0.3000       44.8816  0.0071
+      4       0.3000       44.8816  0.0070
+      5       0.3000       44.8816  0.0078
+      6       0.3000       44.8816  0.0082
+      7       0.3000       44.8816  0.0068
+      8       0.3000       44.8816  0.0067
+      9       0.3000       44.8816  0.0067
+     10       0.3000       44.8816  0.0067
 
 &lt;class &#39;braindecode.classifier.EEGClassifier&#39;&gt;[initialized](
   module_=============================================================================================================================================
@@ -886,8 +886,8 @@ <h2><a class="toc-backref" href="#id8" role="doc-backlink">References</a><a clas
 Online: <a class="reference external" href="http://dx.doi.org/10.1002/hbm.23730">http://dx.doi.org/10.1002/hbm.23730</a></p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 2.716 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  46 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.974 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  44 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-model-building-plot-basic-training-epochs-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/e619a6cc8a167ef21aec010c22e3d8c3/plot_basic_training_epochs.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_basic_training_epochs.py</span></code></a></p>
diff --git a/dev/auto_examples/model_building/plot_bcic_iv_2a_moabb_cropped.html b/dev/auto_examples/model_building/plot_bcic_iv_2a_moabb_cropped.html
index bac1edb8..8aab129e 100644
--- a/dev/auto_examples/model_building/plot_bcic_iv_2a_moabb_cropped.html
+++ b/dev/auto_examples/model_building/plot_bcic_iv_2a_moabb_cropped.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Cropped Decoding on BCIC IV 2a Dataset &#8212; Braindecode 0.8 documentation</title>
+    <title>Cropped Decoding on BCIC IV 2a Dataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -630,60 +630,60 @@ <h2><a class="toc-backref" href="#id6" role="doc-backlink">Loading and preproces
   warnings.warn(
 
   0%|                                              | 0.00/44.1M [00:00&lt;?, ?B/s]
-  0%|                                     | 8.19k/44.1M [00:00&lt;10:51, 67.6kB/s]
-  0%|                                      | 32.8k/44.1M [00:00&lt;05:07, 143kB/s]
-  0%|                                      | 96.3k/44.1M [00:00&lt;02:22, 309kB/s]
-  0%|▏                                      | 209k/44.1M [00:00&lt;01:21, 539kB/s]
-  1%|▍                                      | 432k/44.1M [00:00&lt;00:44, 982kB/s]
-  2%|▊                                     | 889k/44.1M [00:00&lt;00:23, 1.87MB/s]
-  4%|█▌                                   | 1.80M/44.1M [00:00&lt;00:11, 3.61MB/s]
-  8%|███                                  | 3.62M/44.1M [00:01&lt;00:05, 7.04MB/s]
- 15%|█████▌                               | 6.63M/44.1M [00:01&lt;00:03, 12.3MB/s]
- 22%|████████                             | 9.62M/44.1M [00:01&lt;00:02, 15.7MB/s]
- 28%|██████████▌                          | 12.5M/44.1M [00:01&lt;00:01, 17.9MB/s]
- 35%|████████████▉                        | 15.3M/44.1M [00:01&lt;00:01, 19.2MB/s]
- 42%|███████████████▎                     | 18.3M/44.1M [00:01&lt;00:01, 20.5MB/s]
- 48%|█████████████████▋                   | 21.1M/44.1M [00:01&lt;00:01, 20.9MB/s]
- 55%|████████████████████▏                | 24.1M/44.1M [00:01&lt;00:00, 21.7MB/s]
- 61%|██████████████████████▍              | 26.8M/44.1M [00:02&lt;00:00, 21.6MB/s]
- 67%|████████████████████████▉            | 29.6M/44.1M [00:02&lt;00:00, 21.9MB/s]
- 74%|███████████████████████████▎         | 32.6M/44.1M [00:02&lt;00:00, 22.2MB/s]
- 80%|█████████████████████████████▋       | 35.4M/44.1M [00:02&lt;00:00, 22.3MB/s]
- 87%|████████████████████████████████▏    | 38.3M/44.1M [00:02&lt;00:00, 22.5MB/s]
- 94%|██████████████████████████████████▌  | 41.2M/44.1M [00:02&lt;00:00, 22.6MB/s]
+  0%|                                      | 32.8k/44.1M [00:00&lt;04:20, 169kB/s]
+  0%|                                       | 121k/44.1M [00:00&lt;01:33, 470kB/s]
+  1%|▎                                      | 289k/44.1M [00:00&lt;00:47, 925kB/s]
+  2%|▌                                     | 665k/44.1M [00:00&lt;00:22, 1.92MB/s]
+  3%|▉                                    | 1.16M/44.1M [00:00&lt;00:14, 2.93MB/s]
+  5%|█▊                                   | 2.17M/44.1M [00:00&lt;00:07, 5.24MB/s]
+  9%|███▏                                 | 3.83M/44.1M [00:00&lt;00:04, 8.83MB/s]
+ 15%|█████▍                               | 6.49M/44.1M [00:00&lt;00:02, 14.3MB/s]
+ 20%|███████▌                             | 8.96M/44.1M [00:00&lt;00:02, 17.5MB/s]
+ 26%|█████████▋                           | 11.6M/44.1M [00:01&lt;00:01, 20.2MB/s]
+ 32%|███████████▊                         | 14.0M/44.1M [00:01&lt;00:01, 21.5MB/s]
+ 38%|██████████████                       | 16.7M/44.1M [00:01&lt;00:01, 23.1MB/s]
+ 44%|████████████████▏                    | 19.3M/44.1M [00:01&lt;00:01, 23.8MB/s]
+ 50%|██████████████████▌                  | 22.0M/44.1M [00:01&lt;00:00, 25.0MB/s]
+ 56%|████████████████████▌                | 24.6M/44.1M [00:01&lt;00:00, 25.0MB/s]
+ 62%|███████████████████████              | 27.4M/44.1M [00:01&lt;00:00, 26.0MB/s]
+ 68%|█████████████████████████▏           | 30.0M/44.1M [00:01&lt;00:00, 26.0MB/s]
+ 75%|███████████████████████████▌         | 32.9M/44.1M [00:01&lt;00:00, 26.7MB/s]
+ 81%|█████████████████████████████▊       | 35.5M/44.1M [00:01&lt;00:00, 26.7MB/s]
+ 87%|████████████████████████████████▏    | 38.3M/44.1M [00:02&lt;00:00, 26.9MB/s]
+ 93%|██████████████████████████████████▍  | 41.0M/44.1M [00:02&lt;00:00, 26.9MB/s]
+ 99%|████████████████████████████████████▊| 43.8M/44.1M [00:02&lt;00:00, 27.4MB/s]
   0%|                                              | 0.00/44.1M [00:00&lt;?, ?B/s]
-100%|██████████████████████████████████████| 44.1M/44.1M [00:00&lt;00:00, 111GB/s]
+100%|██████████████████████████████████████| 44.1M/44.1M [00:00&lt;00:00, 267GB/s]
 /home/runner/.local/lib/python3.10/site-packages/urllib3/connectionpool.py:1061: InsecureRequestWarning: Unverified HTTPS request is being made to host &#39;lampx.tugraz.at&#39;. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advanced-usage.html#ssl-warnings
   warnings.warn(
 
   0%|                                              | 0.00/42.3M [00:00&lt;?, ?B/s]
-  0%|                                     | 8.19k/42.3M [00:00&lt;10:37, 66.3kB/s]
-  0%|                                      | 32.8k/42.3M [00:00&lt;04:55, 143kB/s]
-  0%|                                      | 88.1k/42.3M [00:00&lt;02:30, 280kB/s]
-  0%|▏                                      | 193k/42.3M [00:00&lt;01:24, 499kB/s]
-  1%|▍                                      | 409k/42.3M [00:00&lt;00:44, 943kB/s]
-  2%|▊                                     | 841k/42.3M [00:00&lt;00:23, 1.80MB/s]
-  4%|█▍                                   | 1.71M/42.3M [00:00&lt;00:11, 3.49MB/s]
-  8%|███                                  | 3.44M/42.3M [00:00&lt;00:05, 6.77MB/s]
- 15%|█████▋                               | 6.53M/42.3M [00:01&lt;00:02, 12.4MB/s]
- 22%|████████▏                            | 9.39M/42.3M [00:01&lt;00:02, 15.6MB/s]
- 28%|██████████▍                          | 12.0M/42.3M [00:01&lt;00:01, 17.1MB/s]
- 35%|████████████▉                        | 14.8M/42.3M [00:01&lt;00:01, 18.9MB/s]
- 42%|███████████████▍                     | 17.7M/42.3M [00:01&lt;00:01, 19.9MB/s]
- 48%|█████████████████▉                   | 20.5M/42.3M [00:01&lt;00:00, 22.1MB/s]
- 55%|████████████████████▎                | 23.2M/42.3M [00:01&lt;00:00, 22.0MB/s]
- 62%|██████████████████████▊              | 26.1M/42.3M [00:01&lt;00:00, 22.5MB/s]
- 69%|█████████████████████████▍           | 29.1M/42.3M [00:02&lt;00:00, 22.9MB/s]
- 76%|████████████████████████████         | 32.2M/42.3M [00:02&lt;00:00, 23.3MB/s]
- 83%|██████████████████████████████▋      | 35.1M/42.3M [00:02&lt;00:00, 23.5MB/s]
- 90%|█████████████████████████████████▏   | 37.9M/42.3M [00:02&lt;00:00, 23.0MB/s]
- 97%|███████████████████████████████████▊ | 40.9M/42.3M [00:02&lt;00:00, 23.3MB/s]
+  0%|                                      | 32.8k/42.3M [00:00&lt;04:06, 172kB/s]
+  0%|                                       | 113k/42.3M [00:00&lt;01:37, 432kB/s]
+  1%|▎                                      | 296k/42.3M [00:00&lt;00:43, 957kB/s]
+  2%|▌                                     | 681k/42.3M [00:00&lt;00:21, 1.97MB/s]
+  3%|█                                    | 1.28M/42.3M [00:00&lt;00:12, 3.31MB/s]
+  6%|██                                   | 2.41M/42.3M [00:00&lt;00:06, 5.89MB/s]
+ 11%|███▉                                 | 4.49M/42.3M [00:00&lt;00:03, 10.6MB/s]
+ 17%|██████▏                              | 7.11M/42.3M [00:00&lt;00:02, 15.4MB/s]
+ 23%|████████▍                            | 9.62M/42.3M [00:00&lt;00:01, 18.4MB/s]
+ 29%|██████████▊                          | 12.3M/42.3M [00:01&lt;00:01, 21.0MB/s]
+ 35%|█████████████                        | 14.9M/42.3M [00:01&lt;00:01, 22.4MB/s]
+ 41%|███████████████▎                     | 17.5M/42.3M [00:01&lt;00:01, 23.7MB/s]
+ 48%|█████████████████▌                   | 20.1M/42.3M [00:01&lt;00:00, 24.4MB/s]
+ 54%|████████████████████                 | 23.0M/42.3M [00:01&lt;00:00, 25.6MB/s]
+ 60%|██████████████████████▎              | 25.6M/42.3M [00:01&lt;00:00, 25.6MB/s]
+ 67%|████████████████████████▊            | 28.4M/42.3M [00:01&lt;00:00, 26.4MB/s]
+ 73%|███████████████████████████▏         | 31.1M/42.3M [00:01&lt;00:00, 26.4MB/s]
+ 80%|█████████████████████████████▋       | 33.9M/42.3M [00:01&lt;00:00, 27.1MB/s]
+ 87%|████████████████████████████████▏    | 36.7M/42.3M [00:01&lt;00:00, 27.4MB/s]
+ 93%|██████████████████████████████████▌  | 39.5M/42.3M [00:02&lt;00:00, 27.5MB/s]
   0%|                                              | 0.00/42.3M [00:00&lt;?, ?B/s]
-100%|██████████████████████████████████████| 42.3M/42.3M [00:00&lt;00:00, 112GB/s]
+100%|██████████████████████████████████████| 42.3M/42.3M [00:00&lt;00:00, 177GB/s]
 /home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f4b834a3730&gt;
+&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f3130efbeb0&gt;
 </pre></div>
 </div>
 </section>
@@ -896,8 +896,8 @@ <h2><a class="toc-backref" href="#id10" role="doc-backlink">Training</a><a class
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_accuracy    train_loss    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  ----------------  ------------  ------  ------
-      1            0.2778        1.5658            0.2535        1.5302  0.0006  9.0047
-      2            0.3090        1.4417            0.2604        1.4977  0.0000  8.8131
+      1            0.2778        1.5658            0.2535        1.5302  0.0006  6.9096
+      2            0.3090        1.4417            0.2604        1.4977  0.0000  6.6676
 </pre></div>
 </div>
 </section>
@@ -998,8 +998,8 @@ <h2><a class="toc-backref" href="#id13" role="doc-backlink">References</a><a cla
 Hum. Brain Mapping, 38: 5391-5420. <a class="reference external" href="https://doi.org/10.1002/hbm.23730">https://doi.org/10.1002/hbm.23730</a>.</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 44.670 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  774 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 33.913 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  747 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-model-building-plot-bcic-iv-2a-moabb-cropped-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/cebe93e1c1784efb2204e0309d1cc9a8/plot_bcic_iv_2a_moabb_cropped.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_bcic_iv_2a_moabb_cropped.py</span></code></a></p>
diff --git a/dev/auto_examples/model_building/plot_bcic_iv_2a_moabb_trial.html b/dev/auto_examples/model_building/plot_bcic_iv_2a_moabb_trial.html
index d58e7d0e..e6e72e79 100644
--- a/dev/auto_examples/model_building/plot_bcic_iv_2a_moabb_trial.html
+++ b/dev/auto_examples/model_building/plot_bcic_iv_2a_moabb_trial.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Basic Brain Decoding on EEG Data &#8212; Braindecode 0.8 documentation</title>
+    <title>Basic Brain Decoding on EEG Data &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -593,7 +593,7 @@ <h3><a class="toc-backref" href="#id10" role="doc-backlink">Preprocessing</a><a
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f4b83820b80&gt;
+&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f3131388eb0&gt;
 </pre></div>
 </div>
 </section>
@@ -781,10 +781,10 @@ <h2><a class="toc-backref" href="#id14" role="doc-backlink">Model Training</a><a
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2500        1.5950       0.2535            0.2535        4.6092  0.0006  2.2852
-      2            0.2708        1.2975       0.2535            0.2535        3.4424  0.0005  2.1554
-      3            0.3333        1.2141       0.2674            0.2674        2.7939  0.0002  2.1438
-      4            0.3438        1.1842       0.2778            0.2778        2.4346  0.0000  2.1380
+      1            0.2500        1.5950       0.2535            0.2535        4.6093  0.0006  1.5148
+      2            0.2708        1.2975       0.2535            0.2535        3.4426  0.0005  1.4172
+      3            0.3333        1.2141       0.2674            0.2674        2.7940  0.0002  1.4043
+      4            0.3438        1.1842       0.2778            0.2778        2.4347  0.0000  1.4155
 </pre></div>
 </div>
 </section>
@@ -884,8 +884,8 @@ <h2><a class="toc-backref" href="#id17" role="doc-backlink">References</a><a cla
 Hum. Brain Mapping, 38: 5391-5420. <a class="reference external" href="https://doi.org/10.1002/hbm.23730">https://doi.org/10.1002/hbm.23730</a>.</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 19.207 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  461 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 12.274 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  502 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-model-building-plot-bcic-iv-2a-moabb-trial-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/0a8b8bc2f1b933515b7b4101626dd179/plot_bcic_iv_2a_moabb_trial.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_bcic_iv_2a_moabb_trial.py</span></code></a></p>
diff --git a/dev/auto_examples/model_building/plot_how_train_test_and_tune.html b/dev/auto_examples/model_building/plot_how_train_test_and_tune.html
index a83df76a..ea5272e9 100644
--- a/dev/auto_examples/model_building/plot_how_train_test_and_tune.html
+++ b/dev/auto_examples/model_building/plot_how_train_test_and_tune.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>How to train, test and tune your model? &#8212; Braindecode 0.8 documentation</title>
+    <title>How to train, test and tune your model? &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -654,7 +654,7 @@ <h3><a class="toc-backref" href="#id11" role="doc-backlink">Preprocessing data</
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f4b8671df00&gt;
+&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f31310d3a90&gt;
 </pre></div>
 </div>
 </section>
@@ -852,8 +852,8 @@ <h3><a class="toc-backref" href="#id16" role="doc-backlink">Option 1: Simple Tra
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_accuracy    train_loss      lr     dur
 -------  ----------------  ------------  ------  ------
-      1            0.2500        1.5950  0.0006  1.8074
-      2            0.2500        1.3661  0.0000  1.6473
+      1            0.2500        1.5950  0.0006  1.2071
+      2            0.2500        1.3661  0.0000  1.0997
 Test acc: 25.35%
 </pre></div>
 </div>
@@ -963,8 +963,8 @@ <h3><a class="toc-backref" href="#id18" role="doc-backlink">Option 2: Train-Val-
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.3435        1.3505       0.2759            0.2759        2.2667  0.0006  1.4574
-      2            0.3478        1.1789       0.2759            0.2759        2.0686  0.0000  1.3389
+      1            0.3435        1.3505       0.2759            0.2759        2.2666  0.0006  0.9983
+      2            0.3478        1.1789       0.2759            0.2759        2.0685  0.0000  0.9464
 Test acc: 27.43%
 </pre></div>
 </div>
@@ -1065,24 +1065,24 @@ <h3><a class="toc-backref" href="#id20" role="doc-backlink">Option 3: k-Fold Cro
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_accuracy    train_loss      lr     dur
 -------  ----------------  ------------  ------  ------
-      1            0.3870        1.2082  0.0006  1.4359
-      2            0.3957        1.1560  0.0000  1.2123
+      1            0.3870        1.2082  0.0006  0.9267
+      2            0.3957        1.1560  0.0000  0.8368
   epoch    train_accuracy    train_loss      lr     dur
 -------  ----------------  ------------  ------  ------
-      1            0.2870        1.2641  0.0006  1.2249
-      2            0.2870        1.2266  0.0000  1.2685
+      1            0.2870        1.2641  0.0006  0.8924
+      2            0.2870        1.2266  0.0000  0.8351
   epoch    train_accuracy    train_loss      lr     dur
 -------  ----------------  ------------  ------  ------
-      1            0.4000        1.3003  0.0006  1.2485
-      2            0.4087        1.1477  0.0000  1.2331
+      1            0.4000        1.3003  0.0006  0.8402
+      2            0.4087        1.1477  0.0000  0.8295
   epoch    train_accuracy    train_loss      lr     dur
 -------  ----------------  ------------  ------  ------
-      1            0.2727        1.2076  0.0006  1.2101
-      2            0.2900        1.1233  0.0000  1.2207
+      1            0.2727        1.2076  0.0006  0.8570
+      2            0.2900        1.1233  0.0000  0.8363
   epoch    train_accuracy    train_loss      lr     dur
 -------  ----------------  ------------  ------  ------
-      1            0.4242        1.1577  0.0006  1.2315
-      2            0.4286        1.0504  0.0000  1.2528
+      1            0.4242        1.1577  0.0006  0.8342
+      2            0.4286        1.0504  0.0000  0.8276
 Validation accuracy: 31.94+-5.59%
 </pre></div>
 </div>
@@ -1182,16 +1182,16 @@ <h3><a class="toc-backref" href="#id23" role="doc-backlink">Option 1: Train-Val-
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Fitting 1 folds for each of 2 candidates, totalling 2 fits
   epoch    train_accuracy    train_loss      lr     dur
 -------  ----------------  ------------  ------  ------
-      1            0.2826        1.5258  0.0063  1.3872
-      2            0.4000        1.4053  0.0000  1.2698
+      1            0.2826        1.5258  0.0063  0.9264
+      2            0.4000        1.4053  0.0000  0.8297
   epoch    train_accuracy    train_loss      lr     dur
 -------  ----------------  ------------  ------  ------
-      1            0.4826        1.2205  0.0006  1.2474
-      2            0.5130        1.1218  0.0000  1.2898
+      1            0.4826        1.2205  0.0006  0.8301
+      2            0.5130        1.1218  0.0000  0.8310
   epoch    train_accuracy    train_loss      lr     dur
 -------  ----------------  ------------  ------  ------
-      1            0.4375        1.2991  0.0006  1.5982
-      2            0.4688        1.1161  0.0000  1.6150
+      1            0.4375        1.2991  0.0006  1.1621
+      2            0.4688        1.1161  0.0000  1.1008
 </pre></div>
 </div>
 </section>
@@ -1229,8 +1229,8 @@ <h2><a class="toc-backref" href="#id25" role="doc-backlink">References</a><a cla
 Hum. Brain Mapping, 38: 5391-5420. <a class="reference external" href="https://doi.org/10.1002/hbm.23730">https://doi.org/10.1002/hbm.23730</a>.</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 48.227 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  536 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 32.571 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  395 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-model-building-plot-how-train-test-and-tune-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/71d05f0d0d0121cf9eb0a58dd5404e6e/plot_how_train_test_and_tune.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_how_train_test_and_tune.py</span></code></a></p>
diff --git a/dev/auto_examples/model_building/plot_hyperparameter_tuning_with_scikit-learn.html b/dev/auto_examples/model_building/plot_hyperparameter_tuning_with_scikit-learn.html
index 185af540..a61bae1b 100644
--- a/dev/auto_examples/model_building/plot_hyperparameter_tuning_with_scikit-learn.html
+++ b/dev/auto_examples/model_building/plot_hyperparameter_tuning_with_scikit-learn.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Hyperparameter tuning with scikit-learn &#8212; Braindecode 0.8 documentation</title>
+    <title>Hyperparameter tuning with scikit-learn &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -625,7 +625,7 @@ <h3><a class="toc-backref" href="#id11" role="doc-backlink">Preprocessing</a><a
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f4b813d4550&gt;
+&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f31312d2b30&gt;
 </pre></div>
 </div>
 </section>
@@ -828,8 +828,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.5304        2.0774       0.1724            0.1724        3.1025  0.0063  0.8791
-      2            0.6174        1.1537       0.2069            0.2069        2.8708  0.0000  0.8253
+      1            0.5304        2.0774       0.1724            0.1724        3.0998  0.0063  0.5723
+      2            0.6174        1.1537       0.2069            0.2069        2.8704  0.0000  0.5342
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -837,8 +837,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.3565        2.5936       0.3103            0.3103        2.3167  0.0063  0.8444
-      2            0.5130        1.1784       0.3448            0.3448        1.8563  0.0000  0.8485
+      1            0.3565        2.5936       0.3448            0.3448        2.3154  0.0063  0.5297
+      2            0.5130        1.1784       0.3448            0.3448        1.8569  0.0000  0.5363
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -846,8 +846,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2348        1.5185       0.2759            0.2759        3.0333  0.0001  0.8203
-      2            0.2348        1.4272       0.2759            0.2759        2.3804  0.0000  0.8199
+      1            0.2348        1.5185       0.2759            0.2759        3.0333  0.0001  0.5407
+      2            0.2348        1.4272       0.2759            0.2759        2.3804  0.0000  0.5287
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -855,8 +855,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2000        1.6046       0.3103            0.3103        4.8912  0.0001  0.8471
-      2            0.2000        1.3911       0.3103            0.3103        3.7741  0.0000  0.8443
+      1            0.2000        1.6046       0.3103            0.3103        4.8912  0.0001  0.5303
+      2            0.2000        1.3911       0.3103            0.3103        3.7741  0.0000  0.5316
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -864,8 +864,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.5304        1.7828       0.1724            0.1724        2.9762  0.0063  0.8749
-      2            0.5826        1.1250       0.1724            0.1724        2.5760  0.0000  0.8846
+      1            0.5304        1.7828       0.1724            0.1724        2.9789  0.0063  0.5350
+      2            0.5826        1.1250       0.1724            0.1724        2.5773  0.0000  0.5400
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -873,8 +873,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2609        2.5664       0.3793            0.3793        3.1116  0.0063  0.8640
-      2            0.4696        1.4854       0.4483            0.4483        1.7445  0.0000  0.8790
+      1            0.2609        2.5664       0.3793            0.3793        3.1215  0.0063  0.5364
+      2            0.4696        1.4854       0.4483            0.4483        1.7465  0.0000  0.5313
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -882,8 +882,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2261        1.7070       0.3103            0.3103        2.1473  0.0001  0.8548
-      2            0.2435        1.6492       0.3103            0.3103        1.8568  0.0000  0.8457
+      1            0.2261        1.7070       0.3103            0.3103        2.1473  0.0001  0.5297
+      2            0.2435        1.6492       0.3103            0.3103        1.8568  0.0000  0.5394
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -891,8 +891,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2783        1.5837       0.2069            0.2069        2.4035  0.0001  0.8156
-      2            0.2696        1.5464       0.2069            0.2069        2.1272  0.0000  0.8200
+      1            0.2783        1.5837       0.2069            0.2069        2.4035  0.0001  0.5385
+      2            0.2696        1.5464       0.2069            0.2069        2.1272  0.0000  0.5362
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -900,8 +900,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2609        2.1099       0.3103            0.3103        3.2198  0.0063  0.8494
-      2            0.4783        1.8860       0.3103            0.3103        1.9008  0.0000  0.8582
+      1            0.2609        2.1099       0.3103            0.3103        3.2171  0.0063  0.5305
+      2            0.4696        1.8860       0.3448            0.3448        1.9000  0.0000  0.5303
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -909,8 +909,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.4087        2.1420       0.4138            0.4138        1.5099  0.0063  0.8220
-      2            0.5130        1.5210       0.3793            0.3793        1.3903  0.0000  0.8248
+      1            0.4087        2.1420       0.4138            0.4138        1.5093  0.0063  0.5308
+      2            0.5130        1.5210       0.3793            0.3793        1.3900  0.0000  0.5370
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -918,8 +918,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2348        2.1793       0.2759            0.2759        9.8493  0.0001  0.8818
-      2            0.2348        1.9960       0.2759            0.2759        7.3377  0.0000  0.8916
+      1            0.2348        2.1793       0.2759            0.2759        9.8493  0.0001  0.5397
+      2            0.2348        1.9960       0.2759            0.2759        7.3377  0.0000  0.5299
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -927,8 +927,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2000        2.2516       0.3103            0.3103        2.5049  0.0001  0.8759
-      2            0.1913        2.1263       0.3448            0.3448        2.0233  0.0000  0.8622
+      1            0.2000        2.2516       0.3103            0.3103        2.5048  0.0001  0.5306
+      2            0.1913        2.1263       0.3448            0.3448        2.0232  0.0000  0.5401
 Can only infer signal shape of numpy arrays or and Datasets, got &lt;class &#39;skorch.helper.SliceDataset&#39;&gt;.
 /home/runner/work/braindecode/braindecode/braindecode/models/base.py:23: UserWarning: ShallowFBCSPNet: &#39;input_window_samples&#39; is depreciated. Use &#39;n_times&#39; instead.
   warnings.warn(
@@ -936,8 +936,8 @@ <h2><a class="toc-backref" href="#id16" role="doc-backlink">Training</a><a class
   warnings.warn(&quot;LogSoftmax final layer will be removed! &quot; +
   epoch    train_accuracy    train_loss    valid_acc    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  -----------  ----------------  ------------  ------  ------
-      1            0.2739        2.2403       0.2586            0.2586        6.1546  0.0063  1.7999
-      2            0.5304        1.7535       0.3448            0.3448        1.9382  0.0000  1.7757
+      1            0.2739        2.2403       0.2586            0.2586        6.1557  0.0063  1.0719
+      2            0.5304        1.7535       0.3448            0.3448        1.9383  0.0000  1.1192
 </pre></div>
 </div>
 </section>
@@ -1018,8 +1018,8 @@ <h2><a class="toc-backref" href="#id19" role="doc-backlink">References</a><a cla
 Hum. Brain Mapping, 38: 5391-5420. <a class="reference external" href="https://doi.org/10.1002/hbm.23730">https://doi.org/10.1002/hbm.23730</a>.</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 44.961 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  430 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 28.271 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  106 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-model-building-plot-hyperparameter-tuning-with-scikit-learn-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/5adeee55d3085fdf6cf644f6c7d12084/plot_hyperparameter_tuning_with_scikit-learn.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_hyperparameter_tuning_with_scikit-learn.py</span></code></a></p>
diff --git a/dev/auto_examples/model_building/plot_regression.html b/dev/auto_examples/model_building/plot_regression.html
index a9c8bcf2..693eb5c7 100644
--- a/dev/auto_examples/model_building/plot_regression.html
+++ b/dev/auto_examples/model_building/plot_regression.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Convolutional neural network regression model on fake data. &#8212; Braindecode 0.8 documentation</title>
+    <title>Convolutional neural network regression model on fake data. &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -785,9 +785,9 @@ <h2>Model training<a class="headerlink" href="#model-training" title="Link to th
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_loss    train_neg_root_mean_squared_error    valid_loss    valid_neg_root_mean_squared_error      lr     dur
 -------  ------------  -----------------------------------  ------------  -----------------------------------  ------  ------
-      1        7.2505                              -1.0922        0.8598                              -0.9275  0.0010  1.2870
-      2        1.9601                              -1.1497        0.2980                              -0.5382  0.0005  1.2746
-      3        2.3129                              -1.0412        0.2603                              -0.4996  0.0000  1.2206
+      1        7.2505                              -1.1215        0.9371                              -0.9685  0.0010  0.8932
+      2        1.9601                              -1.1443        0.2920                              -0.5329  0.0005  0.8717
+      3        2.3129                              -1.0412        0.2603                              -0.4996  0.0000  0.8760
 </pre></div>
 </div>
 </section>
@@ -813,7 +813,7 @@ <h2>Model evaluation<a class="headerlink" href="#model-evaluation" title="Link t
 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">axes</span></a><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">legend</span><span class="p">([</span><span class="s2">&quot;Train&quot;</span><span class="p">,</span> <span class="s2">&quot;Valid&quot;</span><span class="p">])</span>
 </pre></div>
 </div>
-<img src="../../_images/sphx_glr_plot_regression_001.png" srcset="../../_images/sphx_glr_plot_regression_001.png" alt="Train and valid losses, Train and valid errors" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend object at 0x7f4b82667b50&gt;
+<img src="../../_images/sphx_glr_plot_regression_001.png" srcset="../../_images/sphx_glr_plot_regression_001.png" alt="Train and valid losses, Train and valid errors" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend object at 0x7f3130f17cd0&gt;
 </pre></div>
 </div>
 </section>
@@ -856,8 +856,8 @@ <h2>References<a class="headerlink" href="#references" title="Link to this headi
 “On the convergence of adam and beyond.” arXiv preprint arXiv:1904.09237 (2019).</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 8.512 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  11 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 6.675 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  10 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-model-building-plot-regression-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/193f3437bf871ff79a1b5b3f01396c26/plot_regression.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_regression.py</span></code></a></p>
diff --git a/dev/auto_examples/model_building/plot_train_in_pure_pytorch_and_pytorch_lightning.html b/dev/auto_examples/model_building/plot_train_in_pure_pytorch_and_pytorch_lightning.html
index ac81e52f..74377765 100644
--- a/dev/auto_examples/model_building/plot_train_in_pure_pytorch_and_pytorch_lightning.html
+++ b/dev/auto_examples/model_building/plot_train_in_pure_pytorch_and_pytorch_lightning.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Training a Braindecode model in PyTorch &#8212; Braindecode 0.8 documentation</title>
+    <title>Training a Braindecode model in PyTorch &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -617,7 +617,7 @@ <h3><a class="toc-backref" href="#id4" role="doc-backlink">Preprocessing, the of
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f4b814601f0&gt;
+&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f3130eee770&gt;
 </pre></div>
 </div>
 </section>
@@ -899,60 +899,56 @@ <h3><a class="toc-backref" href="#id9" role="doc-backlink">Option 1: Pure PyTorc
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Epoch 1/2:
   0%|          | 0/5 [00:00&lt;?, ?it/s]
 Epoch 1/2, Batch 1/5, Loss: 1.784639:   0%|          | 0/5 [00:00&lt;?, ?it/s]
-Epoch 1/2, Batch 1/5, Loss: 1.784639:  20%|██        | 1/5 [00:00&lt;00:02,  1.97it/s]
-Epoch 1/2, Batch 2/5, Loss: 1.497504:  20%|██        | 1/5 [00:00&lt;00:02,  1.97it/s]
-Epoch 1/2, Batch 2/5, Loss: 1.497504:  40%|████      | 2/5 [00:00&lt;00:01,  2.06it/s]
-Epoch 1/2, Batch 3/5, Loss: 1.544960:  40%|████      | 2/5 [00:01&lt;00:01,  2.06it/s]
-Epoch 1/2, Batch 3/5, Loss: 1.544960:  60%|██████    | 3/5 [00:01&lt;00:00,  2.22it/s]
-Epoch 1/2, Batch 4/5, Loss: 1.552846:  60%|██████    | 3/5 [00:01&lt;00:00,  2.22it/s]
-Epoch 1/2, Batch 4/5, Loss: 1.552846:  80%|████████  | 4/5 [00:01&lt;00:00,  2.32it/s]
-Epoch 1/2, Batch 5/5, Loss: 1.648800:  80%|████████  | 4/5 [00:02&lt;00:00,  2.32it/s]
-Epoch 1/2, Batch 5/5, Loss: 1.648800: 100%|██████████| 5/5 [00:02&lt;00:00,  2.75it/s]
-Epoch 1/2, Batch 5/5, Loss: 1.648800: 100%|██████████| 5/5 [00:02&lt;00:00,  2.46it/s]
+Epoch 1/2, Batch 1/5, Loss: 1.784639:  20%|██        | 1/5 [00:00&lt;00:01,  2.85it/s]
+Epoch 1/2, Batch 2/5, Loss: 1.497504:  20%|██        | 1/5 [00:00&lt;00:01,  2.85it/s]
+Epoch 1/2, Batch 2/5, Loss: 1.497504:  40%|████      | 2/5 [00:00&lt;00:00,  3.16it/s]
+Epoch 1/2, Batch 3/5, Loss: 1.544960:  40%|████      | 2/5 [00:00&lt;00:00,  3.16it/s]
+Epoch 1/2, Batch 3/5, Loss: 1.544960:  60%|██████    | 3/5 [00:00&lt;00:00,  3.33it/s]
+Epoch 1/2, Batch 4/5, Loss: 1.552846:  60%|██████    | 3/5 [00:01&lt;00:00,  3.33it/s]
+Epoch 1/2, Batch 4/5, Loss: 1.552846:  80%|████████  | 4/5 [00:01&lt;00:00,  3.28it/s]
+Epoch 1/2, Batch 5/5, Loss: 1.648800:  80%|████████  | 4/5 [00:01&lt;00:00,  3.28it/s]
+Epoch 1/2, Batch 5/5, Loss: 1.648800: 100%|██████████| 5/5 [00:01&lt;00:00,  4.05it/s]
+Epoch 1/2, Batch 5/5, Loss: 1.648800: 100%|██████████| 5/5 [00:01&lt;00:00,  3.62it/s]
 
   0%|          | 0/5 [00:00&lt;?, ?it/s]
-Batch 1/5, Loss: 4.067186:   0%|          | 0/5 [00:00&lt;?, ?it/s]
-Batch 1/5, Loss: 4.067186:  20%|██        | 1/5 [00:00&lt;00:00,  9.31it/s]
-Batch 2/5, Loss: 4.475584:  20%|██        | 1/5 [00:00&lt;00:00,  9.31it/s]
-Batch 2/5, Loss: 4.475584:  40%|████      | 2/5 [00:00&lt;00:00,  9.31it/s]
-Batch 3/5, Loss: 4.224932:  40%|████      | 2/5 [00:00&lt;00:00,  9.31it/s]
-Batch 3/5, Loss: 4.224932:  60%|██████    | 3/5 [00:00&lt;00:00,  9.30it/s]
-Batch 4/5, Loss: 4.333470:  60%|██████    | 3/5 [00:00&lt;00:00,  9.30it/s]
-Batch 4/5, Loss: 4.333470:  80%|████████  | 4/5 [00:00&lt;00:00,  9.32it/s]
-Batch 5/5, Loss: 4.520719:  80%|████████  | 4/5 [00:00&lt;00:00,  9.32it/s]
-Batch 5/5, Loss: 4.520719: 100%|██████████| 5/5 [00:00&lt;00:00, 10.27it/s]
-Test Accuracy: 25.3%, Test Loss: 4.324378
-
-Train Accuracy: 30.90%, Average Train Loss: 1.605750, Test Accuracy: 25.3%, Average Test Loss: 4.324378
+Batch 1/5, Loss: 4.067336:   0%|          | 0/5 [00:00&lt;?, ?it/s]
+Batch 2/5, Loss: 4.475679:   0%|          | 0/5 [00:00&lt;?, ?it/s]
+Batch 2/5, Loss: 4.475679:  40%|████      | 2/5 [00:00&lt;00:00, 14.69it/s]
+Batch 3/5, Loss: 4.224905:  40%|████      | 2/5 [00:00&lt;00:00, 14.69it/s]
+Batch 4/5, Loss: 4.333737:  40%|████      | 2/5 [00:00&lt;00:00, 14.69it/s]
+Batch 4/5, Loss: 4.333737:  80%|████████  | 4/5 [00:00&lt;00:00, 14.09it/s]
+Batch 5/5, Loss: 4.520595:  80%|████████  | 4/5 [00:00&lt;00:00, 14.09it/s]
+Batch 5/5, Loss: 4.520595: 100%|██████████| 5/5 [00:00&lt;00:00, 15.76it/s]
+Test Accuracy: 25.3%, Test Loss: 4.324450
+
+Train Accuracy: 30.90%, Average Train Loss: 1.605750, Test Accuracy: 25.3%, Average Test Loss: 4.324450
 
 Epoch 2/2:
   0%|          | 0/5 [00:00&lt;?, ?it/s]
 Epoch 2/2, Batch 1/5, Loss: 1.460681:   0%|          | 0/5 [00:00&lt;?, ?it/s]
-Epoch 2/2, Batch 1/5, Loss: 1.460681:  20%|██        | 1/5 [00:00&lt;00:01,  2.50it/s]
-Epoch 2/2, Batch 2/5, Loss: 1.178580:  20%|██        | 1/5 [00:00&lt;00:01,  2.50it/s]
-Epoch 2/2, Batch 2/5, Loss: 1.178580:  40%|████      | 2/5 [00:00&lt;00:01,  2.31it/s]
-Epoch 2/2, Batch 3/5, Loss: 1.232657:  40%|████      | 2/5 [00:01&lt;00:01,  2.31it/s]
-Epoch 2/2, Batch 3/5, Loss: 1.232657:  60%|██████    | 3/5 [00:01&lt;00:00,  2.40it/s]
-Epoch 2/2, Batch 4/5, Loss: 1.294503:  60%|██████    | 3/5 [00:01&lt;00:00,  2.40it/s]
-Epoch 2/2, Batch 4/5, Loss: 1.294503:  80%|████████  | 4/5 [00:01&lt;00:00,  2.35it/s]
-Epoch 2/2, Batch 5/5, Loss: 1.144602:  80%|████████  | 4/5 [00:01&lt;00:00,  2.35it/s]
-Epoch 2/2, Batch 5/5, Loss: 1.144602: 100%|██████████| 5/5 [00:01&lt;00:00,  2.89it/s]
-Epoch 2/2, Batch 5/5, Loss: 1.144602: 100%|██████████| 5/5 [00:01&lt;00:00,  2.64it/s]
+Epoch 2/2, Batch 1/5, Loss: 1.460681:  20%|██        | 1/5 [00:00&lt;00:01,  3.67it/s]
+Epoch 2/2, Batch 2/5, Loss: 1.178580:  20%|██        | 1/5 [00:00&lt;00:01,  3.67it/s]
+Epoch 2/2, Batch 2/5, Loss: 1.178580:  40%|████      | 2/5 [00:00&lt;00:00,  3.66it/s]
+Epoch 2/2, Batch 3/5, Loss: 1.232657:  40%|████      | 2/5 [00:00&lt;00:00,  3.66it/s]
+Epoch 2/2, Batch 3/5, Loss: 1.232657:  60%|██████    | 3/5 [00:00&lt;00:00,  3.66it/s]
+Epoch 2/2, Batch 4/5, Loss: 1.294503:  60%|██████    | 3/5 [00:01&lt;00:00,  3.66it/s]
+Epoch 2/2, Batch 4/5, Loss: 1.294503:  80%|████████  | 4/5 [00:01&lt;00:00,  3.61it/s]
+Epoch 2/2, Batch 5/5, Loss: 1.144602:  80%|████████  | 4/5 [00:01&lt;00:00,  3.61it/s]
+Epoch 2/2, Batch 5/5, Loss: 1.144602: 100%|██████████| 5/5 [00:01&lt;00:00,  4.41it/s]
+Epoch 2/2, Batch 5/5, Loss: 1.144602: 100%|██████████| 5/5 [00:01&lt;00:00,  4.03it/s]
 
   0%|          | 0/5 [00:00&lt;?, ?it/s]
-Batch 1/5, Loss: 3.412761:   0%|          | 0/5 [00:00&lt;?, ?it/s]
-Batch 1/5, Loss: 3.412761:  20%|██        | 1/5 [00:00&lt;00:00,  9.21it/s]
-Batch 2/5, Loss: 3.751282:  20%|██        | 1/5 [00:00&lt;00:00,  9.21it/s]
-Batch 2/5, Loss: 3.751282:  40%|████      | 2/5 [00:00&lt;00:00,  9.26it/s]
-Batch 3/5, Loss: 3.565452:  40%|████      | 2/5 [00:00&lt;00:00,  9.26it/s]
-Batch 3/5, Loss: 3.565452:  60%|██████    | 3/5 [00:00&lt;00:00,  9.29it/s]
-Batch 4/5, Loss: 3.667822:  60%|██████    | 3/5 [00:00&lt;00:00,  9.29it/s]
-Batch 4/5, Loss: 3.667822:  80%|████████  | 4/5 [00:00&lt;00:00,  9.31it/s]
-Batch 5/5, Loss: 3.836633:  80%|████████  | 4/5 [00:00&lt;00:00,  9.31it/s]
-Batch 5/5, Loss: 3.836633: 100%|██████████| 5/5 [00:00&lt;00:00, 10.30it/s]
-Test Accuracy: 24.7%, Test Loss: 3.646790
-
-Train Accuracy: 44.10%, Average Train Loss: 1.262205, Test Accuracy: 24.7%, Average Test Loss: 3.646790
+Batch 1/5, Loss: 3.412822:   0%|          | 0/5 [00:00&lt;?, ?it/s]
+Batch 2/5, Loss: 3.751318:   0%|          | 0/5 [00:00&lt;?, ?it/s]
+Batch 2/5, Loss: 3.751318:  40%|████      | 2/5 [00:00&lt;00:00, 14.71it/s]
+Batch 3/5, Loss: 3.565414:  40%|████      | 2/5 [00:00&lt;00:00, 14.71it/s]
+Batch 4/5, Loss: 3.667956:  40%|████      | 2/5 [00:00&lt;00:00, 14.71it/s]
+Batch 4/5, Loss: 3.667956:  80%|████████  | 4/5 [00:00&lt;00:00, 14.68it/s]
+Batch 5/5, Loss: 3.836547:  80%|████████  | 4/5 [00:00&lt;00:00, 14.68it/s]
+Batch 5/5, Loss: 3.836547: 100%|██████████| 5/5 [00:00&lt;00:00, 16.28it/s]
+Test Accuracy: 24.7%, Test Loss: 3.646811
+
+Train Accuracy: 44.10%, Average Train Loss: 1.262205, Test Accuracy: 24.7%, Average Test Loss: 3.646811
 </pre></div>
 </div>
 </section>
@@ -1021,64 +1017,64 @@ <h3><a class="toc-backref" href="#id10" role="doc-backlink">Option 2: Train it w
 0         Non-trainable params
 47.4 K    Total params
 0.189     Total estimated model params size (MB)
-/home/runner/.local/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:441: The &#39;train_dataloader&#39; does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=1` in the `DataLoader` to improve performance.
+/home/runner/.local/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:441: The &#39;train_dataloader&#39; does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=3` in the `DataLoader` to improve performance.
 /home/runner/.local/lib/python3.10/site-packages/lightning/pytorch/loops/fit_loop.py:293: The number of training batches (5) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.
 
 Training: |          | 0/? [00:00&lt;?, ?it/s]
 Training:   0%|          | 0/5 [00:00&lt;?, ?it/s]
 Epoch 0:   0%|          | 0/5 [00:00&lt;?, ?it/s]
-Epoch 0:  20%|██        | 1/5 [00:00&lt;00:02,  1.81it/s]
-Epoch 0:  20%|██        | 1/5 [00:00&lt;00:02,  1.81it/s, v_num=0]
-Epoch 0:  40%|████      | 2/5 [00:00&lt;00:01,  2.01it/s, v_num=0]
-Epoch 0:  40%|████      | 2/5 [00:00&lt;00:01,  2.01it/s, v_num=0]
-Epoch 0:  60%|██████    | 3/5 [00:01&lt;00:00,  2.06it/s, v_num=0]
-Epoch 0:  60%|██████    | 3/5 [00:01&lt;00:00,  2.06it/s, v_num=0]
-Epoch 0:  80%|████████  | 4/5 [00:01&lt;00:00,  2.15it/s, v_num=0]
-Epoch 0:  80%|████████  | 4/5 [00:01&lt;00:00,  2.14it/s, v_num=0]
-Epoch 0: 100%|██████████| 5/5 [00:02&lt;00:00,  2.40it/s, v_num=0]
-Epoch 0: 100%|██████████| 5/5 [00:02&lt;00:00,  2.40it/s, v_num=0]
-Epoch 0: 100%|██████████| 5/5 [00:02&lt;00:00,  2.40it/s, v_num=0]
+Epoch 0:  20%|██        | 1/5 [00:00&lt;00:01,  2.87it/s]
+Epoch 0:  20%|██        | 1/5 [00:00&lt;00:01,  2.87it/s, v_num=0]
+Epoch 0:  40%|████      | 2/5 [00:00&lt;00:00,  3.21it/s, v_num=0]
+Epoch 0:  40%|████      | 2/5 [00:00&lt;00:00,  3.21it/s, v_num=0]
+Epoch 0:  60%|██████    | 3/5 [00:00&lt;00:00,  3.30it/s, v_num=0]
+Epoch 0:  60%|██████    | 3/5 [00:00&lt;00:00,  3.30it/s, v_num=0]
+Epoch 0:  80%|████████  | 4/5 [00:01&lt;00:00,  3.38it/s, v_num=0]
+Epoch 0:  80%|████████  | 4/5 [00:01&lt;00:00,  3.38it/s, v_num=0]
+Epoch 0: 100%|██████████| 5/5 [00:01&lt;00:00,  3.74it/s, v_num=0]
+Epoch 0: 100%|██████████| 5/5 [00:01&lt;00:00,  3.74it/s, v_num=0]
+Epoch 0: 100%|██████████| 5/5 [00:01&lt;00:00,  3.74it/s, v_num=0]
 Epoch 0:   0%|          | 0/5 [00:00&lt;?, ?it/s, v_num=0]
 Epoch 1:   0%|          | 0/5 [00:00&lt;?, ?it/s, v_num=0]
-Epoch 1:  20%|██        | 1/5 [00:00&lt;00:01,  2.28it/s, v_num=0]
-Epoch 1:  20%|██        | 1/5 [00:00&lt;00:01,  2.28it/s, v_num=0]
-Epoch 1:  40%|████      | 2/5 [00:00&lt;00:01,  2.37it/s, v_num=0]
-Epoch 1:  40%|████      | 2/5 [00:00&lt;00:01,  2.37it/s, v_num=0]
-Epoch 1:  60%|██████    | 3/5 [00:01&lt;00:00,  2.41it/s, v_num=0]
-Epoch 1:  60%|██████    | 3/5 [00:01&lt;00:00,  2.41it/s, v_num=0]
-Epoch 1:  80%|████████  | 4/5 [00:01&lt;00:00,  2.35it/s, v_num=0]
-Epoch 1:  80%|████████  | 4/5 [00:01&lt;00:00,  2.35it/s, v_num=0]
-Epoch 1: 100%|██████████| 5/5 [00:01&lt;00:00,  2.62it/s, v_num=0]
-Epoch 1: 100%|██████████| 5/5 [00:01&lt;00:00,  2.62it/s, v_num=0]
-Epoch 1: 100%|██████████| 5/5 [00:01&lt;00:00,  2.62it/s, v_num=0]`Trainer.fit` stopped: `max_epochs=2` reached.
-
-Epoch 1: 100%|██████████| 5/5 [00:01&lt;00:00,  2.61it/s, v_num=0]
+Epoch 1:  20%|██        | 1/5 [00:00&lt;00:01,  3.64it/s, v_num=0]
+Epoch 1:  20%|██        | 1/5 [00:00&lt;00:01,  3.63it/s, v_num=0]
+Epoch 1:  40%|████      | 2/5 [00:00&lt;00:00,  3.58it/s, v_num=0]
+Epoch 1:  40%|████      | 2/5 [00:00&lt;00:00,  3.58it/s, v_num=0]
+Epoch 1:  60%|██████    | 3/5 [00:00&lt;00:00,  3.61it/s, v_num=0]
+Epoch 1:  60%|██████    | 3/5 [00:00&lt;00:00,  3.61it/s, v_num=0]
+Epoch 1:  80%|████████  | 4/5 [00:01&lt;00:00,  3.62it/s, v_num=0]
+Epoch 1:  80%|████████  | 4/5 [00:01&lt;00:00,  3.62it/s, v_num=0]
+Epoch 1: 100%|██████████| 5/5 [00:01&lt;00:00,  4.01it/s, v_num=0]
+Epoch 1: 100%|██████████| 5/5 [00:01&lt;00:00,  4.01it/s, v_num=0]
+Epoch 1: 100%|██████████| 5/5 [00:01&lt;00:00,  4.01it/s, v_num=0]`Trainer.fit` stopped: `max_epochs=2` reached.
+
+Epoch 1: 100%|██████████| 5/5 [00:01&lt;00:00,  4.00it/s, v_num=0]
 /home/runner/.local/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/checkpoint_connector.py:145: `.test(ckpt_path=None)` was called without a model. The best model of the previous `fit` call will be used. You can pass `.test(ckpt_path=&#39;best&#39;)` to use the best model or `.test(ckpt_path=&#39;last&#39;)` to use the last model. If you pass a value, this warning will be silenced.
 Restoring states from the checkpoint path at /home/runner/work/braindecode/braindecode/examples/model_building/lightning_logs/version_0/checkpoints/epoch=1-step=10.ckpt
 Loaded model weights from the checkpoint at /home/runner/work/braindecode/braindecode/examples/model_building/lightning_logs/version_0/checkpoints/epoch=1-step=10.ckpt
-/home/runner/.local/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:441: The &#39;test_dataloader&#39; does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=1` in the `DataLoader` to improve performance.
+/home/runner/.local/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:441: The &#39;test_dataloader&#39; does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=3` in the `DataLoader` to improve performance.
 
 Testing: |          | 0/? [00:00&lt;?, ?it/s]
 Testing:   0%|          | 0/5 [00:00&lt;?, ?it/s]
 Testing DataLoader 0:   0%|          | 0/5 [00:00&lt;?, ?it/s]
-Testing DataLoader 0:  20%|██        | 1/5 [00:00&lt;00:00,  6.74it/s]
-Testing DataLoader 0:  40%|████      | 2/5 [00:00&lt;00:00,  7.74it/s]
-Testing DataLoader 0:  60%|██████    | 3/5 [00:00&lt;00:00,  7.77it/s]
-Testing DataLoader 0:  80%|████████  | 4/5 [00:00&lt;00:00,  7.89it/s]
-Testing DataLoader 0: 100%|██████████| 5/5 [00:00&lt;00:00,  8.76it/s]
-Testing DataLoader 0: 100%|██████████| 5/5 [00:00&lt;00:00,  8.62it/s]
+Testing DataLoader 0:  20%|██        | 1/5 [00:00&lt;00:00, 10.76it/s]
+Testing DataLoader 0:  40%|████      | 2/5 [00:00&lt;00:00, 11.81it/s]
+Testing DataLoader 0:  60%|██████    | 3/5 [00:00&lt;00:00, 12.59it/s]
+Testing DataLoader 0:  80%|████████  | 4/5 [00:00&lt;00:00, 13.02it/s]
+Testing DataLoader 0: 100%|██████████| 5/5 [00:00&lt;00:00, 14.48it/s]
+Testing DataLoader 0: 100%|██████████| 5/5 [00:00&lt;00:00, 14.22it/s]
 ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
        Test metric             DataLoader 0
 ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
-        test_acc            0.3402777910232544
-        test_loss            1.509909749031067
+        test_acc                  0.34375
+        test_loss           1.5098872184753418
 ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 
-[{&#39;test_acc&#39;: 0.3402777910232544, &#39;test_loss&#39;: 1.509909749031067}]
+[{&#39;test_acc&#39;: 0.34375, &#39;test_loss&#39;: 1.5098872184753418}]
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 17.203 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  545 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 11.524 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  289 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-model-building-plot-train-in-pure-pytorch-and-pytorch-lightning-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/66bb851a261b0b302f4dcb9e2f361aa6/plot_train_in_pure_pytorch_and_pytorch_lightning.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_train_in_pure_pytorch_and_pytorch_lightning.py</span></code></a></p>
diff --git a/dev/auto_examples/model_building/sg_execution_times.html b/dev/auto_examples/model_building/sg_execution_times.html
index 90f1f88f..2bfa5e02 100644
--- a/dev/auto_examples/model_building/sg_execution_times.html
+++ b/dev/auto_examples/model_building/sg_execution_times.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Computation times &#8212; Braindecode 0.8 documentation</title>
+    <title>Computation times &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../../_static/documentation_options.js?v=cc929139"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../../_static/design-tabs.js?v=36754332"></script>
@@ -444,36 +444,36 @@
   
   <section id="computation-times">
 <span id="sphx-glr-auto-examples-model-building-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">#</a></h1>
-<p><strong>03:05.497</strong> total execution time for <strong>auto_examples_model_building</strong> files:</p>
+<p><strong>02:07.202</strong> total execution time for <strong>auto_examples_model_building</strong> files:</p>
 <table class="table">
 <tbody>
-<tr class="row-odd"><td><p><a class="reference internal" href="plot_how_train_test_and_tune.html#sphx-glr-auto-examples-model-building-plot-how-train-test-and-tune-py"><span class="std std-ref">How to train, test and tune your model?</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_how_train_test_and_tune.py</span></code>)</p></td>
-<td><p>00:48.227</p></td>
-<td><p>535.8 MB</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="plot_bcic_iv_2a_moabb_cropped.html#sphx-glr-auto-examples-model-building-plot-bcic-iv-2a-moabb-cropped-py"><span class="std std-ref">Cropped Decoding on BCIC IV 2a Dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_bcic_iv_2a_moabb_cropped.py</span></code>)</p></td>
+<td><p>00:33.913</p></td>
+<td><p>746.8 MB</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="plot_hyperparameter_tuning_with_scikit-learn.html#sphx-glr-auto-examples-model-building-plot-hyperparameter-tuning-with-scikit-learn-py"><span class="std std-ref">Hyperparameter tuning with scikit-learn</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_hyperparameter_tuning_with_scikit-learn.py</span></code>)</p></td>
-<td><p>00:44.961</p></td>
-<td><p>430.1 MB</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="plot_how_train_test_and_tune.html#sphx-glr-auto-examples-model-building-plot-how-train-test-and-tune-py"><span class="std std-ref">How to train, test and tune your model?</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_how_train_test_and_tune.py</span></code>)</p></td>
+<td><p>00:32.571</p></td>
+<td><p>395.5 MB</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="plot_bcic_iv_2a_moabb_cropped.html#sphx-glr-auto-examples-model-building-plot-bcic-iv-2a-moabb-cropped-py"><span class="std std-ref">Cropped Decoding on BCIC IV 2a Dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_bcic_iv_2a_moabb_cropped.py</span></code>)</p></td>
-<td><p>00:44.670</p></td>
-<td><p>773.9 MB</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="plot_hyperparameter_tuning_with_scikit-learn.html#sphx-glr-auto-examples-model-building-plot-hyperparameter-tuning-with-scikit-learn-py"><span class="std std-ref">Hyperparameter tuning with scikit-learn</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_hyperparameter_tuning_with_scikit-learn.py</span></code>)</p></td>
+<td><p>00:28.271</p></td>
+<td><p>105.8 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_bcic_iv_2a_moabb_trial.html#sphx-glr-auto-examples-model-building-plot-bcic-iv-2a-moabb-trial-py"><span class="std std-ref">Basic Brain Decoding on EEG Data</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_bcic_iv_2a_moabb_trial.py</span></code>)</p></td>
-<td><p>00:19.207</p></td>
-<td><p>460.6 MB</p></td>
+<td><p>00:12.274</p></td>
+<td><p>502.4 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_train_in_pure_pytorch_and_pytorch_lightning.html#sphx-glr-auto-examples-model-building-plot-train-in-pure-pytorch-and-pytorch-lightning-py"><span class="std std-ref">Training a Braindecode model in PyTorch</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_train_in_pure_pytorch_and_pytorch_lightning.py</span></code>)</p></td>
-<td><p>00:17.203</p></td>
-<td><p>545.4 MB</p></td>
+<td><p>00:11.524</p></td>
+<td><p>288.9 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_regression.html#sphx-glr-auto-examples-model-building-plot-regression-py"><span class="std std-ref">Convolutional neural network regression model on fake data.</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_regression.py</span></code>)</p></td>
-<td><p>00:08.512</p></td>
-<td><p>10.6 MB</p></td>
+<td><p>00:06.675</p></td>
+<td><p>10.4 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_basic_training_epochs.html#sphx-glr-auto-examples-model-building-plot-basic-training-epochs-py"><span class="std std-ref">Simple training on MNE epochs</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_basic_training_epochs.py</span></code>)</p></td>
-<td><p>00:02.716</p></td>
-<td><p>46.1 MB</p></td>
+<td><p>00:01.974</p></td>
+<td><p>44.0 MB</p></td>
 </tr>
 </tbody>
 </table>
diff --git a/dev/cite.html b/dev/cite.html
index 9f8063e6..1673859b 100644
--- a/dev/cite.html
+++ b/dev/cite.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>How to cite Braindecode &#8212; Braindecode 0.8 documentation</title>
+    <title>How to cite Braindecode &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="_static/documentation_options.js?v=cc929139"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.AugmentedDataLoader.html b/dev/generated/braindecode.augmentation.AugmentedDataLoader.html
index 68f36cf2..df9ccccf 100644
--- a/dev/generated/braindecode.augmentation.AugmentedDataLoader.html
+++ b/dev/generated/braindecode.augmentation.AugmentedDataLoader.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.AugmentedDataLoader &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.AugmentedDataLoader &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.BandstopFilter.html b/dev/generated/braindecode.augmentation.BandstopFilter.html
index 21edd63c..9ac0d070 100644
--- a/dev/generated/braindecode.augmentation.BandstopFilter.html
+++ b/dev/generated/braindecode.augmentation.BandstopFilter.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.BandstopFilter &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.BandstopFilter &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.ChannelsDropout.html b/dev/generated/braindecode.augmentation.ChannelsDropout.html
index 628706cf..bf8725c9 100644
--- a/dev/generated/braindecode.augmentation.ChannelsDropout.html
+++ b/dev/generated/braindecode.augmentation.ChannelsDropout.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.ChannelsDropout &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.ChannelsDropout &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.ChannelsShuffle.html b/dev/generated/braindecode.augmentation.ChannelsShuffle.html
index b62c2640..e037ac3a 100644
--- a/dev/generated/braindecode.augmentation.ChannelsShuffle.html
+++ b/dev/generated/braindecode.augmentation.ChannelsShuffle.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.ChannelsShuffle &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.ChannelsShuffle &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.ChannelsSymmetry.html b/dev/generated/braindecode.augmentation.ChannelsSymmetry.html
index 29f8c52c..5afb1b03 100644
--- a/dev/generated/braindecode.augmentation.ChannelsSymmetry.html
+++ b/dev/generated/braindecode.augmentation.ChannelsSymmetry.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.ChannelsSymmetry &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.ChannelsSymmetry &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.Compose.html b/dev/generated/braindecode.augmentation.Compose.html
index 88a53566..1ca53446 100644
--- a/dev/generated/braindecode.augmentation.Compose.html
+++ b/dev/generated/braindecode.augmentation.Compose.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.Compose &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.Compose &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.FTSurrogate.html b/dev/generated/braindecode.augmentation.FTSurrogate.html
index ca5bbb06..95d6476f 100644
--- a/dev/generated/braindecode.augmentation.FTSurrogate.html
+++ b/dev/generated/braindecode.augmentation.FTSurrogate.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.FTSurrogate &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.FTSurrogate &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.FrequencyShift.html b/dev/generated/braindecode.augmentation.FrequencyShift.html
index ddfd8cea..48e223df 100644
--- a/dev/generated/braindecode.augmentation.FrequencyShift.html
+++ b/dev/generated/braindecode.augmentation.FrequencyShift.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.FrequencyShift &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.FrequencyShift &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.GaussianNoise.html b/dev/generated/braindecode.augmentation.GaussianNoise.html
index 2d6188a1..8df45c9b 100644
--- a/dev/generated/braindecode.augmentation.GaussianNoise.html
+++ b/dev/generated/braindecode.augmentation.GaussianNoise.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.GaussianNoise &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.GaussianNoise &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.IdentityTransform.html b/dev/generated/braindecode.augmentation.IdentityTransform.html
index 2f22bceb..62661b04 100644
--- a/dev/generated/braindecode.augmentation.IdentityTransform.html
+++ b/dev/generated/braindecode.augmentation.IdentityTransform.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.IdentityTransform &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.IdentityTransform &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.Mixup.html b/dev/generated/braindecode.augmentation.Mixup.html
index c0c75f34..648260aa 100644
--- a/dev/generated/braindecode.augmentation.Mixup.html
+++ b/dev/generated/braindecode.augmentation.Mixup.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.Mixup &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.Mixup &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.SensorsRotation.html b/dev/generated/braindecode.augmentation.SensorsRotation.html
index 42d7c0e2..e074aff6 100644
--- a/dev/generated/braindecode.augmentation.SensorsRotation.html
+++ b/dev/generated/braindecode.augmentation.SensorsRotation.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.SensorsRotation &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.SensorsRotation &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.SensorsXRotation.html b/dev/generated/braindecode.augmentation.SensorsXRotation.html
index 0f44234f..7238e915 100644
--- a/dev/generated/braindecode.augmentation.SensorsXRotation.html
+++ b/dev/generated/braindecode.augmentation.SensorsXRotation.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.SensorsXRotation &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.SensorsXRotation &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.SensorsYRotation.html b/dev/generated/braindecode.augmentation.SensorsYRotation.html
index 6f90016a..e2af067e 100644
--- a/dev/generated/braindecode.augmentation.SensorsYRotation.html
+++ b/dev/generated/braindecode.augmentation.SensorsYRotation.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.SensorsYRotation &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.SensorsYRotation &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.SensorsZRotation.html b/dev/generated/braindecode.augmentation.SensorsZRotation.html
index 13bb83b3..040caf85 100644
--- a/dev/generated/braindecode.augmentation.SensorsZRotation.html
+++ b/dev/generated/braindecode.augmentation.SensorsZRotation.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.SensorsZRotation &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.SensorsZRotation &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.SignFlip.html b/dev/generated/braindecode.augmentation.SignFlip.html
index 6a6b4fae..cf2ac549 100644
--- a/dev/generated/braindecode.augmentation.SignFlip.html
+++ b/dev/generated/braindecode.augmentation.SignFlip.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.SignFlip &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.SignFlip &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.SmoothTimeMask.html b/dev/generated/braindecode.augmentation.SmoothTimeMask.html
index 658e452b..4976c7ad 100644
--- a/dev/generated/braindecode.augmentation.SmoothTimeMask.html
+++ b/dev/generated/braindecode.augmentation.SmoothTimeMask.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.SmoothTimeMask &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.SmoothTimeMask &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.TimeReverse.html b/dev/generated/braindecode.augmentation.TimeReverse.html
index 3d21a16f..39a9bc49 100644
--- a/dev/generated/braindecode.augmentation.TimeReverse.html
+++ b/dev/generated/braindecode.augmentation.TimeReverse.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.TimeReverse &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.TimeReverse &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.Transform.html b/dev/generated/braindecode.augmentation.Transform.html
index 6e97a8dd..ff5e7b0e 100644
--- a/dev/generated/braindecode.augmentation.Transform.html
+++ b/dev/generated/braindecode.augmentation.Transform.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.Transform &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.Transform &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.bandstop_filter.html b/dev/generated/braindecode.augmentation.functional.bandstop_filter.html
index a2d5ec05..b16a9f6b 100644
--- a/dev/generated/braindecode.augmentation.functional.bandstop_filter.html
+++ b/dev/generated/braindecode.augmentation.functional.bandstop_filter.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.bandstop_filter &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.bandstop_filter &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.channels_dropout.html b/dev/generated/braindecode.augmentation.functional.channels_dropout.html
index e3d15cc5..d49b1d9b 100644
--- a/dev/generated/braindecode.augmentation.functional.channels_dropout.html
+++ b/dev/generated/braindecode.augmentation.functional.channels_dropout.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.channels_dropout &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.channels_dropout &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.channels_permute.html b/dev/generated/braindecode.augmentation.functional.channels_permute.html
index b26662cf..8df36aac 100644
--- a/dev/generated/braindecode.augmentation.functional.channels_permute.html
+++ b/dev/generated/braindecode.augmentation.functional.channels_permute.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.channels_permute &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.channels_permute &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.channels_shuffle.html b/dev/generated/braindecode.augmentation.functional.channels_shuffle.html
index 964cf8e0..4c465a0f 100644
--- a/dev/generated/braindecode.augmentation.functional.channels_shuffle.html
+++ b/dev/generated/braindecode.augmentation.functional.channels_shuffle.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.channels_shuffle &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.channels_shuffle &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.frequency_shift.html b/dev/generated/braindecode.augmentation.functional.frequency_shift.html
index 5e0c41a3..f020225d 100644
--- a/dev/generated/braindecode.augmentation.functional.frequency_shift.html
+++ b/dev/generated/braindecode.augmentation.functional.frequency_shift.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.frequency_shift &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.frequency_shift &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.ft_surrogate.html b/dev/generated/braindecode.augmentation.functional.ft_surrogate.html
index cbefe83f..b7218ca2 100644
--- a/dev/generated/braindecode.augmentation.functional.ft_surrogate.html
+++ b/dev/generated/braindecode.augmentation.functional.ft_surrogate.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.ft_surrogate &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.ft_surrogate &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.gaussian_noise.html b/dev/generated/braindecode.augmentation.functional.gaussian_noise.html
index b283bb31..833b12ff 100644
--- a/dev/generated/braindecode.augmentation.functional.gaussian_noise.html
+++ b/dev/generated/braindecode.augmentation.functional.gaussian_noise.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.gaussian_noise &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.gaussian_noise &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.identity.html b/dev/generated/braindecode.augmentation.functional.identity.html
index 99071973..9c7f0b90 100644
--- a/dev/generated/braindecode.augmentation.functional.identity.html
+++ b/dev/generated/braindecode.augmentation.functional.identity.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.identity &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.identity &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.mixup.html b/dev/generated/braindecode.augmentation.functional.mixup.html
index 0bd3b8ee..0a19d8b1 100644
--- a/dev/generated/braindecode.augmentation.functional.mixup.html
+++ b/dev/generated/braindecode.augmentation.functional.mixup.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.mixup &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.mixup &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.sensors_rotation.html b/dev/generated/braindecode.augmentation.functional.sensors_rotation.html
index 3f3d3345..f32f075d 100644
--- a/dev/generated/braindecode.augmentation.functional.sensors_rotation.html
+++ b/dev/generated/braindecode.augmentation.functional.sensors_rotation.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.sensors_rotation &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.sensors_rotation &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.sign_flip.html b/dev/generated/braindecode.augmentation.functional.sign_flip.html
index 2605a176..a20ad4b5 100644
--- a/dev/generated/braindecode.augmentation.functional.sign_flip.html
+++ b/dev/generated/braindecode.augmentation.functional.sign_flip.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.sign_flip &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.sign_flip &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.smooth_time_mask.html b/dev/generated/braindecode.augmentation.functional.smooth_time_mask.html
index f0e640cc..50eef333 100644
--- a/dev/generated/braindecode.augmentation.functional.smooth_time_mask.html
+++ b/dev/generated/braindecode.augmentation.functional.smooth_time_mask.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.smooth_time_mask &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.smooth_time_mask &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.augmentation.functional.time_reverse.html b/dev/generated/braindecode.augmentation.functional.time_reverse.html
index 0ec8c74e..ac613c89 100644
--- a/dev/generated/braindecode.augmentation.functional.time_reverse.html
+++ b/dev/generated/braindecode.augmentation.functional.time_reverse.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.augmentation.functional.time_reverse &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.augmentation.functional.time_reverse &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.classifier.EEGClassifier.html b/dev/generated/braindecode.classifier.EEGClassifier.html
index cd7c5e02..0f94841e 100644
--- a/dev/generated/braindecode.classifier.EEGClassifier.html
+++ b/dev/generated/braindecode.classifier.EEGClassifier.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.classifier.EEGClassifier &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.classifier.EEGClassifier &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.BCICompetitionIVDataset4.html b/dev/generated/braindecode.datasets.BCICompetitionIVDataset4.html
index 8ffdd4f6..c21e5266 100644
--- a/dev/generated/braindecode.datasets.BCICompetitionIVDataset4.html
+++ b/dev/generated/braindecode.datasets.BCICompetitionIVDataset4.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.BCICompetitionIVDataset4 &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.BCICompetitionIVDataset4 &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.BNCI2014001.html b/dev/generated/braindecode.datasets.BNCI2014001.html
index 77faa1e6..1cada5b2 100644
--- a/dev/generated/braindecode.datasets.BNCI2014001.html
+++ b/dev/generated/braindecode.datasets.BNCI2014001.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.BNCI2014001 &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.BNCI2014001 &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.BaseConcatDataset.html b/dev/generated/braindecode.datasets.BaseConcatDataset.html
index eedefd3f..6ac3f28d 100644
--- a/dev/generated/braindecode.datasets.BaseConcatDataset.html
+++ b/dev/generated/braindecode.datasets.BaseConcatDataset.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.BaseConcatDataset &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.BaseConcatDataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.BaseDataset.html b/dev/generated/braindecode.datasets.BaseDataset.html
index dbcfdc6f..a6fd72ac 100644
--- a/dev/generated/braindecode.datasets.BaseDataset.html
+++ b/dev/generated/braindecode.datasets.BaseDataset.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.BaseDataset &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.BaseDataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.HGD.html b/dev/generated/braindecode.datasets.HGD.html
index fc9dbd77..983c0e41 100644
--- a/dev/generated/braindecode.datasets.HGD.html
+++ b/dev/generated/braindecode.datasets.HGD.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.HGD &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.HGD &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.MOABBDataset.html b/dev/generated/braindecode.datasets.MOABBDataset.html
index 79785f43..ae20feba 100644
--- a/dev/generated/braindecode.datasets.MOABBDataset.html
+++ b/dev/generated/braindecode.datasets.MOABBDataset.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.MOABBDataset &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.MOABBDataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.SleepPhysionet.html b/dev/generated/braindecode.datasets.SleepPhysionet.html
index 78be991b..1f43317b 100644
--- a/dev/generated/braindecode.datasets.SleepPhysionet.html
+++ b/dev/generated/braindecode.datasets.SleepPhysionet.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.SleepPhysionet &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.SleepPhysionet &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.TUH.html b/dev/generated/braindecode.datasets.TUH.html
index 76b8290e..e6e2bf7b 100644
--- a/dev/generated/braindecode.datasets.TUH.html
+++ b/dev/generated/braindecode.datasets.TUH.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.TUH &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.TUH &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.TUHAbnormal.html b/dev/generated/braindecode.datasets.TUHAbnormal.html
index 20ccff56..314c90db 100644
--- a/dev/generated/braindecode.datasets.TUHAbnormal.html
+++ b/dev/generated/braindecode.datasets.TUHAbnormal.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.TUHAbnormal &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.TUHAbnormal &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.WindowsDataset.html b/dev/generated/braindecode.datasets.WindowsDataset.html
index bd84c58b..d1c4f538 100644
--- a/dev/generated/braindecode.datasets.WindowsDataset.html
+++ b/dev/generated/braindecode.datasets.WindowsDataset.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.WindowsDataset &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.WindowsDataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.create_from_X_y.html b/dev/generated/braindecode.datasets.create_from_X_y.html
index 79e9279a..d79bc391 100644
--- a/dev/generated/braindecode.datasets.create_from_X_y.html
+++ b/dev/generated/braindecode.datasets.create_from_X_y.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.create_from_X_y &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.create_from_X_y &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.create_from_mne_epochs.html b/dev/generated/braindecode.datasets.create_from_mne_epochs.html
index 5734f990..a11daf45 100644
--- a/dev/generated/braindecode.datasets.create_from_mne_epochs.html
+++ b/dev/generated/braindecode.datasets.create_from_mne_epochs.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.create_from_mne_epochs &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.create_from_mne_epochs &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datasets.create_from_mne_raw.html b/dev/generated/braindecode.datasets.create_from_mne_raw.html
index 30a72296..d5759923 100644
--- a/dev/generated/braindecode.datasets.create_from_mne_raw.html
+++ b/dev/generated/braindecode.datasets.create_from_mne_raw.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datasets.create_from_mne_raw &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datasets.create_from_mne_raw &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datautil.load_concat_dataset.html b/dev/generated/braindecode.datautil.load_concat_dataset.html
index a3205eb1..c46515b2 100644
--- a/dev/generated/braindecode.datautil.load_concat_dataset.html
+++ b/dev/generated/braindecode.datautil.load_concat_dataset.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datautil.load_concat_dataset &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datautil.load_concat_dataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.datautil.save_concat_dataset.html b/dev/generated/braindecode.datautil.save_concat_dataset.html
index 08f94295..5d7e92dd 100644
--- a/dev/generated/braindecode.datautil.save_concat_dataset.html
+++ b/dev/generated/braindecode.datautil.save_concat_dataset.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.datautil.save_concat_dataset &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.datautil.save_concat_dataset &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.ATCNet.html b/dev/generated/braindecode.models.ATCNet.html
index 2456fbc8..76ad58bb 100644
--- a/dev/generated/braindecode.models.ATCNet.html
+++ b/dev/generated/braindecode.models.ATCNet.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.ATCNet &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.ATCNet &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.Deep4Net.html b/dev/generated/braindecode.models.Deep4Net.html
index 973b88d0..400bf8b5 100644
--- a/dev/generated/braindecode.models.Deep4Net.html
+++ b/dev/generated/braindecode.models.Deep4Net.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.Deep4Net &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.Deep4Net &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.DeepSleepNet.html b/dev/generated/braindecode.models.DeepSleepNet.html
index 4fb39b15..46cc5d83 100644
--- a/dev/generated/braindecode.models.DeepSleepNet.html
+++ b/dev/generated/braindecode.models.DeepSleepNet.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.DeepSleepNet &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.DeepSleepNet &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.EEGConformer.html b/dev/generated/braindecode.models.EEGConformer.html
index d9a69742..91620753 100644
--- a/dev/generated/braindecode.models.EEGConformer.html
+++ b/dev/generated/braindecode.models.EEGConformer.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.EEGConformer &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.EEGConformer &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.EEGITNet.html b/dev/generated/braindecode.models.EEGITNet.html
index b4c13542..adcb9120 100644
--- a/dev/generated/braindecode.models.EEGITNet.html
+++ b/dev/generated/braindecode.models.EEGITNet.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.EEGITNet &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.EEGITNet &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.EEGInception.html b/dev/generated/braindecode.models.EEGInception.html
index 97f20bb4..c63c9c52 100644
--- a/dev/generated/braindecode.models.EEGInception.html
+++ b/dev/generated/braindecode.models.EEGInception.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.EEGInception &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.EEGInception &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.EEGInceptionERP.html b/dev/generated/braindecode.models.EEGInceptionERP.html
index 335ada2e..dbf77b7c 100644
--- a/dev/generated/braindecode.models.EEGInceptionERP.html
+++ b/dev/generated/braindecode.models.EEGInceptionERP.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.EEGInceptionERP &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.EEGInceptionERP &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.EEGInceptionMI.html b/dev/generated/braindecode.models.EEGInceptionMI.html
index e28c29e1..802cd689 100644
--- a/dev/generated/braindecode.models.EEGInceptionMI.html
+++ b/dev/generated/braindecode.models.EEGInceptionMI.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.EEGInceptionMI &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.EEGInceptionMI &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.EEGModuleMixin.html b/dev/generated/braindecode.models.EEGModuleMixin.html
index d579f4c6..7bb46156 100644
--- a/dev/generated/braindecode.models.EEGModuleMixin.html
+++ b/dev/generated/braindecode.models.EEGModuleMixin.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.EEGModuleMixin &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.EEGModuleMixin &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.EEGNetv1.html b/dev/generated/braindecode.models.EEGNetv1.html
index 3b8e1d6a..ba6b563c 100644
--- a/dev/generated/braindecode.models.EEGNetv1.html
+++ b/dev/generated/braindecode.models.EEGNetv1.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.EEGNetv1 &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.EEGNetv1 &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.EEGNetv4.html b/dev/generated/braindecode.models.EEGNetv4.html
index 6cecd3d7..e8cfe52a 100644
--- a/dev/generated/braindecode.models.EEGNetv4.html
+++ b/dev/generated/braindecode.models.EEGNetv4.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.EEGNetv4 &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.EEGNetv4 &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.EEGResNet.html b/dev/generated/braindecode.models.EEGResNet.html
index c9ecad9e..454acbb4 100644
--- a/dev/generated/braindecode.models.EEGResNet.html
+++ b/dev/generated/braindecode.models.EEGResNet.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.EEGResNet &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.EEGResNet &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.HybridNet.html b/dev/generated/braindecode.models.HybridNet.html
index 44d2bf31..da203a04 100644
--- a/dev/generated/braindecode.models.HybridNet.html
+++ b/dev/generated/braindecode.models.HybridNet.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.HybridNet &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.HybridNet &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.ShallowFBCSPNet.html b/dev/generated/braindecode.models.ShallowFBCSPNet.html
index a62cf001..fe157fc5 100644
--- a/dev/generated/braindecode.models.ShallowFBCSPNet.html
+++ b/dev/generated/braindecode.models.ShallowFBCSPNet.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.ShallowFBCSPNet &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.ShallowFBCSPNet &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.SleepStagerBlanco2020.html b/dev/generated/braindecode.models.SleepStagerBlanco2020.html
index a75c01c6..eb4b0917 100644
--- a/dev/generated/braindecode.models.SleepStagerBlanco2020.html
+++ b/dev/generated/braindecode.models.SleepStagerBlanco2020.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.SleepStagerBlanco2020 &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.SleepStagerBlanco2020 &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.SleepStagerChambon2018.html b/dev/generated/braindecode.models.SleepStagerChambon2018.html
index 73fb8166..7fe2a0ff 100644
--- a/dev/generated/braindecode.models.SleepStagerChambon2018.html
+++ b/dev/generated/braindecode.models.SleepStagerChambon2018.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.SleepStagerChambon2018 &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.SleepStagerChambon2018 &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.SleepStagerEldele2021.html b/dev/generated/braindecode.models.SleepStagerEldele2021.html
index 7c96cfdf..e4f4ebe5 100644
--- a/dev/generated/braindecode.models.SleepStagerEldele2021.html
+++ b/dev/generated/braindecode.models.SleepStagerEldele2021.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.SleepStagerEldele2021 &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.SleepStagerEldele2021 &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.TCN.html b/dev/generated/braindecode.models.TCN.html
index 8bbc67ae..01695357 100644
--- a/dev/generated/braindecode.models.TCN.html
+++ b/dev/generated/braindecode.models.TCN.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.TCN &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.TCN &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.TIDNet.html b/dev/generated/braindecode.models.TIDNet.html
index d36d5e53..6a9c146f 100644
--- a/dev/generated/braindecode.models.TIDNet.html
+++ b/dev/generated/braindecode.models.TIDNet.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.TIDNet &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.TIDNet &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.TimeDistributed.html b/dev/generated/braindecode.models.TimeDistributed.html
index 233528ed..7d9d2374 100644
--- a/dev/generated/braindecode.models.TimeDistributed.html
+++ b/dev/generated/braindecode.models.TimeDistributed.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.TimeDistributed &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.TimeDistributed &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.USleep.html b/dev/generated/braindecode.models.USleep.html
index f1ef4e04..af040edb 100644
--- a/dev/generated/braindecode.models.USleep.html
+++ b/dev/generated/braindecode.models.USleep.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.USleep &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.USleep &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.models.get_output_shape.html b/dev/generated/braindecode.models.get_output_shape.html
index d99c598e..92e94c8d 100644
--- a/dev/generated/braindecode.models.get_output_shape.html
+++ b/dev/generated/braindecode.models.get_output_shape.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.models.get_output_shape &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.models.get_output_shape &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.Crop.html b/dev/generated/braindecode.preprocessing.Crop.html
index 58ef6ca1..dd82fc82 100644
--- a/dev/generated/braindecode.preprocessing.Crop.html
+++ b/dev/generated/braindecode.preprocessing.Crop.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.Crop &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.Crop &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.DropChannels.html b/dev/generated/braindecode.preprocessing.DropChannels.html
index 6084656b..210988f3 100644
--- a/dev/generated/braindecode.preprocessing.DropChannels.html
+++ b/dev/generated/braindecode.preprocessing.DropChannels.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.DropChannels &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.DropChannels &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.Filter.html b/dev/generated/braindecode.preprocessing.Filter.html
index 37fbca50..49e32d97 100644
--- a/dev/generated/braindecode.preprocessing.Filter.html
+++ b/dev/generated/braindecode.preprocessing.Filter.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.Filter &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.Filter &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.Pick.html b/dev/generated/braindecode.preprocessing.Pick.html
index f33b4cc7..d751a4a7 100644
--- a/dev/generated/braindecode.preprocessing.Pick.html
+++ b/dev/generated/braindecode.preprocessing.Pick.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.Pick &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.Pick &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.Preprocessor.html b/dev/generated/braindecode.preprocessing.Preprocessor.html
index 3f59ab38..7815f96a 100644
--- a/dev/generated/braindecode.preprocessing.Preprocessor.html
+++ b/dev/generated/braindecode.preprocessing.Preprocessor.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.Preprocessor &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.Preprocessor &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.Resample.html b/dev/generated/braindecode.preprocessing.Resample.html
index a995729c..0bb271ac 100644
--- a/dev/generated/braindecode.preprocessing.Resample.html
+++ b/dev/generated/braindecode.preprocessing.Resample.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.Resample &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.Resample &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.SetEEGReference.html b/dev/generated/braindecode.preprocessing.SetEEGReference.html
index 9360a265..6557aeb1 100644
--- a/dev/generated/braindecode.preprocessing.SetEEGReference.html
+++ b/dev/generated/braindecode.preprocessing.SetEEGReference.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.SetEEGReference &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.SetEEGReference &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.create_fixed_length_windows.html b/dev/generated/braindecode.preprocessing.create_fixed_length_windows.html
index a42a32e7..b3e155b1 100644
--- a/dev/generated/braindecode.preprocessing.create_fixed_length_windows.html
+++ b/dev/generated/braindecode.preprocessing.create_fixed_length_windows.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.create_fixed_length_windows &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.create_fixed_length_windows &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.create_windows_from_events.html b/dev/generated/braindecode.preprocessing.create_windows_from_events.html
index ca2a4cfc..8f37b3e7 100644
--- a/dev/generated/braindecode.preprocessing.create_windows_from_events.html
+++ b/dev/generated/braindecode.preprocessing.create_windows_from_events.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.create_windows_from_events &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.create_windows_from_events &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.create_windows_from_target_channels.html b/dev/generated/braindecode.preprocessing.create_windows_from_target_channels.html
index 05463a08..082dc6ed 100644
--- a/dev/generated/braindecode.preprocessing.create_windows_from_target_channels.html
+++ b/dev/generated/braindecode.preprocessing.create_windows_from_target_channels.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.create_windows_from_target_channels &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.create_windows_from_target_channels &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.exponential_moving_demean.html b/dev/generated/braindecode.preprocessing.exponential_moving_demean.html
index 06e875a3..36e4a21d 100644
--- a/dev/generated/braindecode.preprocessing.exponential_moving_demean.html
+++ b/dev/generated/braindecode.preprocessing.exponential_moving_demean.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.exponential_moving_demean &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.exponential_moving_demean &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.exponential_moving_standardize.html b/dev/generated/braindecode.preprocessing.exponential_moving_standardize.html
index b24c10e0..0a8df5a5 100644
--- a/dev/generated/braindecode.preprocessing.exponential_moving_standardize.html
+++ b/dev/generated/braindecode.preprocessing.exponential_moving_standardize.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.exponential_moving_standardize &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.exponential_moving_standardize &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.filterbank.html b/dev/generated/braindecode.preprocessing.filterbank.html
index bd24cdbe..ce93d519 100644
--- a/dev/generated/braindecode.preprocessing.filterbank.html
+++ b/dev/generated/braindecode.preprocessing.filterbank.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.filterbank &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.filterbank &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.preprocessing.preprocess.html b/dev/generated/braindecode.preprocessing.preprocess.html
index 63281b93..fdae13e1 100644
--- a/dev/generated/braindecode.preprocessing.preprocess.html
+++ b/dev/generated/braindecode.preprocessing.preprocess.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.preprocessing.preprocess &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.preprocessing.preprocess &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.regressor.EEGRegressor.html b/dev/generated/braindecode.regressor.EEGRegressor.html
index ef44a666..eebf8efc 100644
--- a/dev/generated/braindecode.regressor.EEGRegressor.html
+++ b/dev/generated/braindecode.regressor.EEGRegressor.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.regressor.EEGRegressor &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.regressor.EEGRegressor &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.samplers.BalancedSequenceSampler.html b/dev/generated/braindecode.samplers.BalancedSequenceSampler.html
index 581c6d4b..92a59452 100644
--- a/dev/generated/braindecode.samplers.BalancedSequenceSampler.html
+++ b/dev/generated/braindecode.samplers.BalancedSequenceSampler.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.samplers.BalancedSequenceSampler &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.samplers.BalancedSequenceSampler &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.samplers.RecordingSampler.html b/dev/generated/braindecode.samplers.RecordingSampler.html
index c3f56ad8..af257193 100644
--- a/dev/generated/braindecode.samplers.RecordingSampler.html
+++ b/dev/generated/braindecode.samplers.RecordingSampler.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.samplers.RecordingSampler &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.samplers.RecordingSampler &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.samplers.RelativePositioningSampler.html b/dev/generated/braindecode.samplers.RelativePositioningSampler.html
index 3811c7f9..c1c7cd2a 100644
--- a/dev/generated/braindecode.samplers.RelativePositioningSampler.html
+++ b/dev/generated/braindecode.samplers.RelativePositioningSampler.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.samplers.RelativePositioningSampler &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.samplers.RelativePositioningSampler &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.samplers.SequenceSampler.html b/dev/generated/braindecode.samplers.SequenceSampler.html
index 3a0eaff1..4b8d6df0 100644
--- a/dev/generated/braindecode.samplers.SequenceSampler.html
+++ b/dev/generated/braindecode.samplers.SequenceSampler.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.samplers.SequenceSampler &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.samplers.SequenceSampler &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.training.CroppedLoss.html b/dev/generated/braindecode.training.CroppedLoss.html
index 967b4b01..6ab57c74 100644
--- a/dev/generated/braindecode.training.CroppedLoss.html
+++ b/dev/generated/braindecode.training.CroppedLoss.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.training.CroppedLoss &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.training.CroppedLoss &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.training.CroppedTimeSeriesEpochScoring.html b/dev/generated/braindecode.training.CroppedTimeSeriesEpochScoring.html
index 28f144f6..826b630a 100644
--- a/dev/generated/braindecode.training.CroppedTimeSeriesEpochScoring.html
+++ b/dev/generated/braindecode.training.CroppedTimeSeriesEpochScoring.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.training.CroppedTimeSeriesEpochScoring &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.training.CroppedTimeSeriesEpochScoring &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.training.CroppedTrialEpochScoring.html b/dev/generated/braindecode.training.CroppedTrialEpochScoring.html
index acf7f5c9..c3b36f1a 100644
--- a/dev/generated/braindecode.training.CroppedTrialEpochScoring.html
+++ b/dev/generated/braindecode.training.CroppedTrialEpochScoring.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.training.CroppedTrialEpochScoring &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.training.CroppedTrialEpochScoring &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.training.PostEpochTrainScoring.html b/dev/generated/braindecode.training.PostEpochTrainScoring.html
index 3b4a18f0..b54ed924 100644
--- a/dev/generated/braindecode.training.PostEpochTrainScoring.html
+++ b/dev/generated/braindecode.training.PostEpochTrainScoring.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.training.PostEpochTrainScoring &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.training.PostEpochTrainScoring &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.training.TimeSeriesLoss.html b/dev/generated/braindecode.training.TimeSeriesLoss.html
index 2ac273af..87b16f4a 100644
--- a/dev/generated/braindecode.training.TimeSeriesLoss.html
+++ b/dev/generated/braindecode.training.TimeSeriesLoss.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.training.TimeSeriesLoss &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.training.TimeSeriesLoss &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.training.mixup_criterion.html b/dev/generated/braindecode.training.mixup_criterion.html
index 1fbedc37..104e1261 100644
--- a/dev/generated/braindecode.training.mixup_criterion.html
+++ b/dev/generated/braindecode.training.mixup_criterion.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.training.mixup_criterion &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.training.mixup_criterion &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.training.predict_trials.html b/dev/generated/braindecode.training.predict_trials.html
index 2b4d97f6..f1a24e3a 100644
--- a/dev/generated/braindecode.training.predict_trials.html
+++ b/dev/generated/braindecode.training.predict_trials.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.training.predict_trials &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.training.predict_trials &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.training.trial_preds_from_window_preds.html b/dev/generated/braindecode.training.trial_preds_from_window_preds.html
index da196abb..066bd306 100644
--- a/dev/generated/braindecode.training.trial_preds_from_window_preds.html
+++ b/dev/generated/braindecode.training.trial_preds_from_window_preds.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.training.trial_preds_from_window_preds &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.training.trial_preds_from_window_preds &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.util.set_random_seeds.html b/dev/generated/braindecode.util.set_random_seeds.html
index a385015d..6acc69a9 100644
--- a/dev/generated/braindecode.util.set_random_seeds.html
+++ b/dev/generated/braindecode.util.set_random_seeds.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.util.set_random_seeds &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.util.set_random_seeds &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.visualization.compute_amplitude_gradients.html b/dev/generated/braindecode.visualization.compute_amplitude_gradients.html
index 9bccf463..2692ec08 100644
--- a/dev/generated/braindecode.visualization.compute_amplitude_gradients.html
+++ b/dev/generated/braindecode.visualization.compute_amplitude_gradients.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.visualization.compute_amplitude_gradients &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.visualization.compute_amplitude_gradients &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/generated/braindecode.visualization.plot_confusion_matrix.html b/dev/generated/braindecode.visualization.plot_confusion_matrix.html
index 8278bc28..a19057e4 100644
--- a/dev/generated/braindecode.visualization.plot_confusion_matrix.html
+++ b/dev/generated/braindecode.visualization.plot_confusion_matrix.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>braindecode.visualization.plot_confusion_matrix &#8212; Braindecode 0.8 documentation</title>
+    <title>braindecode.visualization.plot_confusion_matrix &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/genindex.html b/dev/genindex.html
index 895ebfd9..58740d5d 100644
--- a/dev/genindex.html
+++ b/dev/genindex.html
@@ -7,7 +7,7 @@
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Index &#8212; Braindecode 0.8 documentation</title>
+    <title>Index &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -40,7 +40,7 @@
 <link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="_static/documentation_options.js?v=cc929139"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/help.html b/dev/help.html
index 76952551..ba120ebd 100644
--- a/dev/help.html
+++ b/dev/help.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Frequently Asked Questions (FAQ) &#8212; Braindecode 0.8 documentation</title>
+    <title>Frequently Asked Questions (FAQ) &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="_static/documentation_options.js?v=cc929139"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/index.html b/dev/index.html
index d2745e5e..8432e06f 100644
--- a/dev/index.html
+++ b/dev/index.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Braindecode &#8212; Braindecode 0.8 documentation</title>
+    <title>Braindecode &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="_static/documentation_options.js?v=cc929139"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/install/install.html b/dev/install/install.html
index 58b38ab0..573052a8 100644
--- a/dev/install/install.html
+++ b/dev/install/install.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Installation &#8212; Braindecode 0.8 documentation</title>
+    <title>Installation &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/install/install_pip.html b/dev/install/install_pip.html
index 45d72ef5..db5d565d 100644
--- a/dev/install/install_pip.html
+++ b/dev/install/install_pip.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Installing from PyPI &#8212; Braindecode 0.8 documentation</title>
+    <title>Installing from PyPI &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/install/install_source.html b/dev/install/install_source.html
index e33799e9..adbe8282 100644
--- a/dev/install/install_source.html
+++ b/dev/install/install_source.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Installing from sources &#8212; Braindecode 0.8 documentation</title>
+    <title>Installing from sources &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="../_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="../_static/documentation_options.js?v=cc929139"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/py-modindex.html b/dev/py-modindex.html
index 5442bc39..1ba7cdf9 100644
--- a/dev/py-modindex.html
+++ b/dev/py-modindex.html
@@ -7,7 +7,7 @@
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Python Module Index &#8212; Braindecode 0.8 documentation</title>
+    <title>Python Module Index &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -40,7 +40,7 @@
 <link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="_static/documentation_options.js?v=cc929139"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/search.html b/dev/search.html
index bf3a0074..79f7d9d2 100644
--- a/dev/search.html
+++ b/dev/search.html
@@ -6,7 +6,7 @@
 
   <head>
     <meta charset="utf-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><title>Search - Braindecode 0.8 documentation</title>
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><title>Search - Braindecode 0.8.1 documentation</title>
   
   
   
@@ -39,7 +39,7 @@
 <link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="_static/documentation_options.js?v=cc929139"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/design-tabs.js?v=36754332"></script>
diff --git a/dev/searchindex.js b/dev/searchindex.js
index 2007f521..a0f8a075 100644
--- a/dev/searchindex.js
+++ b/dev/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"docnames": ["api", "auto_examples/advanced_training/index", "auto_examples/advanced_training/plot_bcic_iv_4_ecog_cropped", "auto_examples/advanced_training/plot_data_augmentation", "auto_examples/advanced_training/plot_data_augmentation_search", "auto_examples/advanced_training/plot_relative_positioning", "auto_examples/advanced_training/sg_execution_times", "auto_examples/applied_examples/index", "auto_examples/applied_examples/plot_bcic_iv_4_ecog_trial", "auto_examples/applied_examples/plot_sleep_staging_chambon2018", "auto_examples/applied_examples/plot_sleep_staging_eldele2021", "auto_examples/applied_examples/plot_sleep_staging_usleep", "auto_examples/applied_examples/plot_tuh_eeg_corpus", "auto_examples/applied_examples/sg_execution_times", "auto_examples/datasets_io/benchmark_lazy_eager_loading", "auto_examples/datasets_io/index", "auto_examples/datasets_io/plot_benchmark_preprocessing", "auto_examples/datasets_io/plot_custom_dataset_example", "auto_examples/datasets_io/plot_load_save_datasets", "auto_examples/datasets_io/plot_mne_dataset_example", "auto_examples/datasets_io/plot_moabb_dataset_example", "auto_examples/datasets_io/plot_split_dataset", "auto_examples/datasets_io/plot_tuh_discrete_multitarget", "auto_examples/datasets_io/sg_execution_times", "auto_examples/index", "auto_examples/model_building/index", "auto_examples/model_building/plot_basic_training_epochs", "auto_examples/model_building/plot_bcic_iv_2a_moabb_cropped", "auto_examples/model_building/plot_bcic_iv_2a_moabb_trial", "auto_examples/model_building/plot_how_train_test_and_tune", "auto_examples/model_building/plot_hyperparameter_tuning_with_scikit-learn", "auto_examples/model_building/plot_regression", "auto_examples/model_building/plot_train_in_pure_pytorch_and_pytorch_lightning", "auto_examples/model_building/sg_execution_times", "cite", "generated/braindecode.augmentation.AugmentedDataLoader", "generated/braindecode.augmentation.BandstopFilter", "generated/braindecode.augmentation.ChannelsDropout", "generated/braindecode.augmentation.ChannelsShuffle", "generated/braindecode.augmentation.ChannelsSymmetry", "generated/braindecode.augmentation.Compose", "generated/braindecode.augmentation.FTSurrogate", "generated/braindecode.augmentation.FrequencyShift", "generated/braindecode.augmentation.GaussianNoise", "generated/braindecode.augmentation.IdentityTransform", "generated/braindecode.augmentation.Mixup", "generated/braindecode.augmentation.SensorsRotation", "generated/braindecode.augmentation.SensorsXRotation", "generated/braindecode.augmentation.SensorsYRotation", "generated/braindecode.augmentation.SensorsZRotation", "generated/braindecode.augmentation.SignFlip", "generated/braindecode.augmentation.SmoothTimeMask", "generated/braindecode.augmentation.TimeReverse", "generated/braindecode.augmentation.Transform", "generated/braindecode.augmentation.functional.bandstop_filter", "generated/braindecode.augmentation.functional.channels_dropout", "generated/braindecode.augmentation.functional.channels_permute", "generated/braindecode.augmentation.functional.channels_shuffle", "generated/braindecode.augmentation.functional.frequency_shift", "generated/braindecode.augmentation.functional.ft_surrogate", "generated/braindecode.augmentation.functional.gaussian_noise", "generated/braindecode.augmentation.functional.identity", "generated/braindecode.augmentation.functional.mixup", "generated/braindecode.augmentation.functional.sensors_rotation", "generated/braindecode.augmentation.functional.sign_flip", "generated/braindecode.augmentation.functional.smooth_time_mask", "generated/braindecode.augmentation.functional.time_reverse", "generated/braindecode.classifier.EEGClassifier", "generated/braindecode.datasets.BCICompetitionIVDataset4", "generated/braindecode.datasets.BNCI2014001", "generated/braindecode.datasets.BaseConcatDataset", "generated/braindecode.datasets.BaseDataset", "generated/braindecode.datasets.HGD", "generated/braindecode.datasets.MOABBDataset", "generated/braindecode.datasets.SleepPhysionet", "generated/braindecode.datasets.TUH", "generated/braindecode.datasets.TUHAbnormal", "generated/braindecode.datasets.WindowsDataset", "generated/braindecode.datasets.create_from_X_y", "generated/braindecode.datasets.create_from_mne_epochs", "generated/braindecode.datasets.create_from_mne_raw", "generated/braindecode.datautil.load_concat_dataset", "generated/braindecode.datautil.save_concat_dataset", "generated/braindecode.models.ATCNet", "generated/braindecode.models.Deep4Net", "generated/braindecode.models.DeepSleepNet", "generated/braindecode.models.EEGConformer", "generated/braindecode.models.EEGITNet", "generated/braindecode.models.EEGInception", "generated/braindecode.models.EEGInceptionERP", "generated/braindecode.models.EEGInceptionMI", "generated/braindecode.models.EEGModuleMixin", "generated/braindecode.models.EEGNetv1", "generated/braindecode.models.EEGNetv4", "generated/braindecode.models.EEGResNet", "generated/braindecode.models.HybridNet", "generated/braindecode.models.ShallowFBCSPNet", "generated/braindecode.models.SleepStagerBlanco2020", "generated/braindecode.models.SleepStagerChambon2018", "generated/braindecode.models.SleepStagerEldele2021", "generated/braindecode.models.TCN", "generated/braindecode.models.TIDNet", "generated/braindecode.models.TimeDistributed", "generated/braindecode.models.USleep", "generated/braindecode.models.get_output_shape", "generated/braindecode.preprocessing.Crop", "generated/braindecode.preprocessing.DropChannels", "generated/braindecode.preprocessing.Filter", "generated/braindecode.preprocessing.Pick", "generated/braindecode.preprocessing.Preprocessor", "generated/braindecode.preprocessing.Resample", "generated/braindecode.preprocessing.SetEEGReference", "generated/braindecode.preprocessing.create_fixed_length_windows", "generated/braindecode.preprocessing.create_windows_from_events", "generated/braindecode.preprocessing.create_windows_from_target_channels", "generated/braindecode.preprocessing.exponential_moving_demean", "generated/braindecode.preprocessing.exponential_moving_standardize", "generated/braindecode.preprocessing.filterbank", "generated/braindecode.preprocessing.preprocess", "generated/braindecode.regressor.EEGRegressor", "generated/braindecode.samplers.BalancedSequenceSampler", "generated/braindecode.samplers.RecordingSampler", "generated/braindecode.samplers.RelativePositioningSampler", "generated/braindecode.samplers.SequenceSampler", "generated/braindecode.training.CroppedLoss", "generated/braindecode.training.CroppedTimeSeriesEpochScoring", "generated/braindecode.training.CroppedTrialEpochScoring", "generated/braindecode.training.PostEpochTrainScoring", "generated/braindecode.training.TimeSeriesLoss", "generated/braindecode.training.mixup_criterion", "generated/braindecode.training.predict_trials", "generated/braindecode.training.trial_preds_from_window_preds", "generated/braindecode.util.set_random_seeds", "generated/braindecode.visualization.compute_amplitude_gradients", "generated/braindecode.visualization.plot_confusion_matrix", "help", "index", "install/install", "install/install_pip", "install/install_source", "whats_new"], "filenames": ["api.rst", "auto_examples/advanced_training/index.rst", "auto_examples/advanced_training/plot_bcic_iv_4_ecog_cropped.rst", "auto_examples/advanced_training/plot_data_augmentation.rst", "auto_examples/advanced_training/plot_data_augmentation_search.rst", "auto_examples/advanced_training/plot_relative_positioning.rst", "auto_examples/advanced_training/sg_execution_times.rst", "auto_examples/applied_examples/index.rst", "auto_examples/applied_examples/plot_bcic_iv_4_ecog_trial.rst", "auto_examples/applied_examples/plot_sleep_staging_chambon2018.rst", "auto_examples/applied_examples/plot_sleep_staging_eldele2021.rst", "auto_examples/applied_examples/plot_sleep_staging_usleep.rst", "auto_examples/applied_examples/plot_tuh_eeg_corpus.rst", "auto_examples/applied_examples/sg_execution_times.rst", "auto_examples/datasets_io/benchmark_lazy_eager_loading.rst", "auto_examples/datasets_io/index.rst", "auto_examples/datasets_io/plot_benchmark_preprocessing.rst", "auto_examples/datasets_io/plot_custom_dataset_example.rst", "auto_examples/datasets_io/plot_load_save_datasets.rst", "auto_examples/datasets_io/plot_mne_dataset_example.rst", "auto_examples/datasets_io/plot_moabb_dataset_example.rst", "auto_examples/datasets_io/plot_split_dataset.rst", "auto_examples/datasets_io/plot_tuh_discrete_multitarget.rst", "auto_examples/datasets_io/sg_execution_times.rst", "auto_examples/index.rst", "auto_examples/model_building/index.rst", "auto_examples/model_building/plot_basic_training_epochs.rst", "auto_examples/model_building/plot_bcic_iv_2a_moabb_cropped.rst", "auto_examples/model_building/plot_bcic_iv_2a_moabb_trial.rst", "auto_examples/model_building/plot_how_train_test_and_tune.rst", "auto_examples/model_building/plot_hyperparameter_tuning_with_scikit-learn.rst", "auto_examples/model_building/plot_regression.rst", "auto_examples/model_building/plot_train_in_pure_pytorch_and_pytorch_lightning.rst", "auto_examples/model_building/sg_execution_times.rst", "cite.rst", "generated/braindecode.augmentation.AugmentedDataLoader.rst", "generated/braindecode.augmentation.BandstopFilter.rst", "generated/braindecode.augmentation.ChannelsDropout.rst", "generated/braindecode.augmentation.ChannelsShuffle.rst", "generated/braindecode.augmentation.ChannelsSymmetry.rst", "generated/braindecode.augmentation.Compose.rst", "generated/braindecode.augmentation.FTSurrogate.rst", "generated/braindecode.augmentation.FrequencyShift.rst", "generated/braindecode.augmentation.GaussianNoise.rst", "generated/braindecode.augmentation.IdentityTransform.rst", "generated/braindecode.augmentation.Mixup.rst", "generated/braindecode.augmentation.SensorsRotation.rst", "generated/braindecode.augmentation.SensorsXRotation.rst", "generated/braindecode.augmentation.SensorsYRotation.rst", "generated/braindecode.augmentation.SensorsZRotation.rst", "generated/braindecode.augmentation.SignFlip.rst", "generated/braindecode.augmentation.SmoothTimeMask.rst", "generated/braindecode.augmentation.TimeReverse.rst", "generated/braindecode.augmentation.Transform.rst", "generated/braindecode.augmentation.functional.bandstop_filter.rst", "generated/braindecode.augmentation.functional.channels_dropout.rst", "generated/braindecode.augmentation.functional.channels_permute.rst", "generated/braindecode.augmentation.functional.channels_shuffle.rst", "generated/braindecode.augmentation.functional.frequency_shift.rst", "generated/braindecode.augmentation.functional.ft_surrogate.rst", "generated/braindecode.augmentation.functional.gaussian_noise.rst", "generated/braindecode.augmentation.functional.identity.rst", "generated/braindecode.augmentation.functional.mixup.rst", "generated/braindecode.augmentation.functional.sensors_rotation.rst", "generated/braindecode.augmentation.functional.sign_flip.rst", "generated/braindecode.augmentation.functional.smooth_time_mask.rst", "generated/braindecode.augmentation.functional.time_reverse.rst", "generated/braindecode.classifier.EEGClassifier.rst", "generated/braindecode.datasets.BCICompetitionIVDataset4.rst", "generated/braindecode.datasets.BNCI2014001.rst", "generated/braindecode.datasets.BaseConcatDataset.rst", "generated/braindecode.datasets.BaseDataset.rst", "generated/braindecode.datasets.HGD.rst", "generated/braindecode.datasets.MOABBDataset.rst", "generated/braindecode.datasets.SleepPhysionet.rst", "generated/braindecode.datasets.TUH.rst", "generated/braindecode.datasets.TUHAbnormal.rst", "generated/braindecode.datasets.WindowsDataset.rst", "generated/braindecode.datasets.create_from_X_y.rst", "generated/braindecode.datasets.create_from_mne_epochs.rst", "generated/braindecode.datasets.create_from_mne_raw.rst", "generated/braindecode.datautil.load_concat_dataset.rst", "generated/braindecode.datautil.save_concat_dataset.rst", "generated/braindecode.models.ATCNet.rst", "generated/braindecode.models.Deep4Net.rst", "generated/braindecode.models.DeepSleepNet.rst", "generated/braindecode.models.EEGConformer.rst", "generated/braindecode.models.EEGITNet.rst", "generated/braindecode.models.EEGInception.rst", "generated/braindecode.models.EEGInceptionERP.rst", "generated/braindecode.models.EEGInceptionMI.rst", "generated/braindecode.models.EEGModuleMixin.rst", "generated/braindecode.models.EEGNetv1.rst", "generated/braindecode.models.EEGNetv4.rst", "generated/braindecode.models.EEGResNet.rst", "generated/braindecode.models.HybridNet.rst", "generated/braindecode.models.ShallowFBCSPNet.rst", "generated/braindecode.models.SleepStagerBlanco2020.rst", "generated/braindecode.models.SleepStagerChambon2018.rst", "generated/braindecode.models.SleepStagerEldele2021.rst", "generated/braindecode.models.TCN.rst", "generated/braindecode.models.TIDNet.rst", "generated/braindecode.models.TimeDistributed.rst", "generated/braindecode.models.USleep.rst", "generated/braindecode.models.get_output_shape.rst", "generated/braindecode.preprocessing.Crop.rst", "generated/braindecode.preprocessing.DropChannels.rst", "generated/braindecode.preprocessing.Filter.rst", "generated/braindecode.preprocessing.Pick.rst", "generated/braindecode.preprocessing.Preprocessor.rst", "generated/braindecode.preprocessing.Resample.rst", "generated/braindecode.preprocessing.SetEEGReference.rst", "generated/braindecode.preprocessing.create_fixed_length_windows.rst", "generated/braindecode.preprocessing.create_windows_from_events.rst", "generated/braindecode.preprocessing.create_windows_from_target_channels.rst", "generated/braindecode.preprocessing.exponential_moving_demean.rst", "generated/braindecode.preprocessing.exponential_moving_standardize.rst", "generated/braindecode.preprocessing.filterbank.rst", "generated/braindecode.preprocessing.preprocess.rst", "generated/braindecode.regressor.EEGRegressor.rst", "generated/braindecode.samplers.BalancedSequenceSampler.rst", "generated/braindecode.samplers.RecordingSampler.rst", "generated/braindecode.samplers.RelativePositioningSampler.rst", "generated/braindecode.samplers.SequenceSampler.rst", "generated/braindecode.training.CroppedLoss.rst", "generated/braindecode.training.CroppedTimeSeriesEpochScoring.rst", "generated/braindecode.training.CroppedTrialEpochScoring.rst", "generated/braindecode.training.PostEpochTrainScoring.rst", "generated/braindecode.training.TimeSeriesLoss.rst", "generated/braindecode.training.mixup_criterion.rst", "generated/braindecode.training.predict_trials.rst", "generated/braindecode.training.trial_preds_from_window_preds.rst", "generated/braindecode.util.set_random_seeds.rst", "generated/braindecode.visualization.compute_amplitude_gradients.rst", "generated/braindecode.visualization.plot_confusion_matrix.rst", "help.rst", "index.rst", "install/install.rst", "install/install_pip.rst", "install/install_source.rst", "whats_new.rst"], "titles": ["API Reference", "Advanced neural network training strategies", "Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset", "Data Augmentation on BCIC IV 2a Dataset", "Searching the best data augmentation on BCIC IV 2a Dataset", "Self-supervised learning on EEG with relative positioning", "Computation times", "Applied examples on real-world datasets", "Fingers flexion decoding on BCIC IV 4 ECoG Dataset", "Sleep staging on the Sleep Physionet dataset using Chambon2018 network", "Sleep staging on the Sleep Physionet dataset using Eldele2021", "Sleep staging on the Sleep Physionet dataset using U-Sleep network", "Process a big data EEG resource (TUH EEG Corpus)", "Computation times", "Benchmarking eager and lazy loading", "Loading and organizing data", "Benchmarking preprocessing with parallelization and serialization", "Custom Dataset Example", "Load and save dataset example", "MNE Dataset Example", "MOABB Dataset Example", "Split Dataset Example", "Multiple discrete targets with the TUH EEG Corpus", "Computation times", "Examples", "Basic model building and training", "Simple training on MNE epochs", "Cropped Decoding on BCIC IV 2a Dataset", "Basic Brain Decoding on EEG Data", "How to train, test and tune your model?", "Hyperparameter tuning with scikit-learn", "Convolutional neural network regression model on fake data.", "Training a Braindecode model in PyTorch", "Computation times", "How to cite Braindecode", "braindecode.augmentation.AugmentedDataLoader", "braindecode.augmentation.BandstopFilter", "braindecode.augmentation.ChannelsDropout", "braindecode.augmentation.ChannelsShuffle", "braindecode.augmentation.ChannelsSymmetry", "braindecode.augmentation.Compose", "braindecode.augmentation.FTSurrogate", "braindecode.augmentation.FrequencyShift", "braindecode.augmentation.GaussianNoise", "braindecode.augmentation.IdentityTransform", "braindecode.augmentation.Mixup", "braindecode.augmentation.SensorsRotation", "braindecode.augmentation.SensorsXRotation", "braindecode.augmentation.SensorsYRotation", "braindecode.augmentation.SensorsZRotation", "braindecode.augmentation.SignFlip", "braindecode.augmentation.SmoothTimeMask", "braindecode.augmentation.TimeReverse", "braindecode.augmentation.Transform", "braindecode.augmentation.functional.bandstop_filter", "braindecode.augmentation.functional.channels_dropout", "braindecode.augmentation.functional.channels_permute", "braindecode.augmentation.functional.channels_shuffle", "braindecode.augmentation.functional.frequency_shift", "braindecode.augmentation.functional.ft_surrogate", "braindecode.augmentation.functional.gaussian_noise", "braindecode.augmentation.functional.identity", "braindecode.augmentation.functional.mixup", "braindecode.augmentation.functional.sensors_rotation", "braindecode.augmentation.functional.sign_flip", "braindecode.augmentation.functional.smooth_time_mask", "braindecode.augmentation.functional.time_reverse", "braindecode.classifier.EEGClassifier", "braindecode.datasets.BCICompetitionIVDataset4", "braindecode.datasets.BNCI2014001", "braindecode.datasets.BaseConcatDataset", "braindecode.datasets.BaseDataset", "braindecode.datasets.HGD", "braindecode.datasets.MOABBDataset", "braindecode.datasets.SleepPhysionet", "braindecode.datasets.TUH", "braindecode.datasets.TUHAbnormal", "braindecode.datasets.WindowsDataset", "braindecode.datasets.create_from_X_y", "braindecode.datasets.create_from_mne_epochs", "braindecode.datasets.create_from_mne_raw", "braindecode.datautil.load_concat_dataset", "braindecode.datautil.save_concat_dataset", "braindecode.models.ATCNet", "braindecode.models.Deep4Net", "braindecode.models.DeepSleepNet", "braindecode.models.EEGConformer", "braindecode.models.EEGITNet", "braindecode.models.EEGInception", "braindecode.models.EEGInceptionERP", "braindecode.models.EEGInceptionMI", "braindecode.models.EEGModuleMixin", "braindecode.models.EEGNetv1", "braindecode.models.EEGNetv4", "braindecode.models.EEGResNet", "braindecode.models.HybridNet", "braindecode.models.ShallowFBCSPNet", "braindecode.models.SleepStagerBlanco2020", "braindecode.models.SleepStagerChambon2018", "braindecode.models.SleepStagerEldele2021", "braindecode.models.TCN", "braindecode.models.TIDNet", "braindecode.models.TimeDistributed", "braindecode.models.USleep", "braindecode.models.get_output_shape", "braindecode.preprocessing.Crop", "braindecode.preprocessing.DropChannels", "braindecode.preprocessing.Filter", "braindecode.preprocessing.Pick", "braindecode.preprocessing.Preprocessor", "braindecode.preprocessing.Resample", "braindecode.preprocessing.SetEEGReference", "braindecode.preprocessing.create_fixed_length_windows", "braindecode.preprocessing.create_windows_from_events", "braindecode.preprocessing.create_windows_from_target_channels", "braindecode.preprocessing.exponential_moving_demean", "braindecode.preprocessing.exponential_moving_standardize", "braindecode.preprocessing.filterbank", "braindecode.preprocessing.preprocess", "braindecode.regressor.EEGRegressor", "braindecode.samplers.BalancedSequenceSampler", "braindecode.samplers.RecordingSampler", "braindecode.samplers.RelativePositioningSampler", "braindecode.samplers.SequenceSampler", "braindecode.training.CroppedLoss", "braindecode.training.CroppedTimeSeriesEpochScoring", "braindecode.training.CroppedTrialEpochScoring", "braindecode.training.PostEpochTrainScoring", "braindecode.training.TimeSeriesLoss", "braindecode.training.mixup_criterion", "braindecode.training.predict_trials", "braindecode.training.trial_preds_from_window_preds", "braindecode.util.set_random_seeds", "braindecode.visualization.compute_amplitude_gradients", "braindecode.visualization.plot_confusion_matrix", "Frequently Asked Questions (FAQ)", "Braindecode", "Installation", "Installing from PyPI", "Installing from sources", "What\u2019s new"], "terms": {"thi": [0, 2, 8, 9, 10, 11, 14, 16, 17, 18, 19, 20, 22, 31, 47, 48, 49, 67, 68, 69, 70, 72, 74, 75, 76, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 111, 113, 115, 116, 119, 121, 127, 132, 135, 139, 140], "i": [0, 2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 20, 21, 22, 26, 27, 28, 30, 31, 34, 36, 40, 41, 42, 45, 46, 51, 53, 54, 58, 59, 62, 63, 65, 67, 68, 69, 70, 71, 72, 73, 77, 78, 79, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 109, 110, 111, 112, 113, 118, 119, 122, 127, 131, 132, 136, 137, 138, 140], "class": [0, 3, 4, 5, 9, 10, 11, 12, 14, 18, 20, 21, 26, 27, 28, 29, 30, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 59, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 105, 106, 107, 108, 109, 110, 111, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 134, 140], "camelcas": 0, "name": [0, 2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 20, 21, 22, 26, 29, 30, 32, 39, 67, 69, 70, 71, 72, 73, 78, 81, 106, 107, 108, 109, 111, 119, 125, 126, 127, 140], "function": [0, 2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 20, 22, 26, 27, 28, 30, 31, 32, 34, 41, 53, 67, 70, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 105, 109, 111, 113, 119, 125, 126, 127, 132, 140], "underscore_cas": 0, "braindecod": [0, 2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 25, 27, 28, 29, 30, 31, 33, 137, 138, 140], "base": [0, 2, 3, 4, 5, 8, 9, 10, 12, 16, 18, 20, 21, 26, 27, 28, 29, 30, 31, 32, 35, 43, 45, 60, 62, 67, 69, 70, 83, 85, 86, 87, 88, 89, 90, 92, 93, 99, 105, 107, 108, 112, 113, 119, 121, 129, 140], "datautil": [0, 5, 18, 77, 140], "exampl": [1, 2, 8, 9, 10, 11, 14, 15, 16, 22, 23, 25, 31, 36, 38, 39, 43, 44, 45, 46, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 111, 135, 140], "explain": [1, 4, 24, 27, 87], "more": [1, 2, 3, 4, 5, 8, 9, 10, 11, 16, 18, 20, 21, 22, 24, 26, 27, 28, 29, 30, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 101, 103, 105, 106, 107, 108, 110, 111, 118, 119, 132, 139, 140], "topic": [1, 24, 34], "finger": [1, 6, 7, 13, 24, 68, 70, 72, 91, 96, 104, 109, 112, 114, 116, 118, 125, 126, 128, 132, 140], "flexion": [1, 6, 7, 13, 24, 68, 70, 91, 96, 104, 109, 112, 114, 116, 118, 125, 126, 128, 132, 140], "crop": [1, 6, 8, 10, 11, 12, 16, 20, 24, 25, 29, 30, 31, 32, 33, 67, 68, 70, 73, 74, 77, 91, 96, 104, 109, 112, 113, 116, 118, 119, 124, 125, 126, 128, 130, 132, 134, 140], "decod": [1, 3, 4, 6, 7, 11, 13, 20, 22, 24, 25, 26, 29, 30, 31, 32, 33, 34, 67, 68, 70, 73, 78, 84, 86, 91, 95, 96, 103, 104, 109, 112, 113, 114, 116, 118, 119, 124, 125, 126, 128, 130, 132, 134, 136, 140], "bcic": [1, 6, 7, 13, 20, 24, 25, 29, 32, 33, 35, 37, 40, 41, 42, 50, 51, 53, 68, 70, 73, 91, 96, 104, 109, 112, 113, 114, 116, 118, 124, 125, 126, 128, 132, 134, 140], "iv": [1, 6, 7, 13, 20, 21, 24, 25, 26, 28, 29, 30, 32, 33, 35, 37, 40, 41, 42, 50, 51, 53, 68, 70, 73, 83, 90, 91, 96, 104, 109, 112, 113, 114, 116, 118, 124, 125, 126, 128, 132, 134, 140], "4": [1, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 33, 68, 69, 70, 72, 83, 84, 86, 87, 88, 89, 90, 91, 92, 93, 96, 98, 101, 103, 104, 109, 112, 114, 116, 117, 118, 120, 121, 125, 126, 128, 132], "ecog": [1, 6, 7, 13, 24, 68, 70, 91, 96, 104, 109, 111, 112, 114, 116, 118, 125, 126, 128, 132, 136, 140], "dataset": [1, 6, 13, 14, 15, 16, 23, 25, 26, 33, 35, 37, 40, 41, 42, 50, 51, 53, 67, 81, 83, 90, 91, 96, 98, 99, 102, 103, 104, 109, 112, 113, 114, 116, 118, 119, 121, 123, 124, 125, 126, 128, 130, 132, 133, 134, 135, 136, 138, 139, 140], "data": [1, 2, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 17, 18, 19, 21, 25, 30, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 53, 57, 60, 62, 63, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 80, 81, 84, 86, 91, 96, 104, 105, 107, 108, 109, 110, 111, 112, 113, 115, 116, 118, 119, 124, 129, 132, 134, 135, 136, 140], "augment": [1, 6, 24, 70, 73, 86, 91, 96, 109, 113, 116, 118, 132, 136, 140], "2a": [1, 6, 20, 21, 24, 25, 26, 28, 29, 30, 32, 33, 35, 37, 40, 41, 42, 50, 51, 53, 70, 73, 83, 90, 91, 96, 109, 113, 116, 118, 124, 132, 134, 140], "search": [1, 6, 24, 29, 30, 35, 37, 41, 51, 53, 67, 70, 73, 91, 96, 109, 113, 116, 118, 119, 132, 135, 140], "best": [1, 6, 24, 32, 35, 37, 41, 51, 53, 70, 73, 91, 96, 109, 113, 116, 118, 132], "self": [1, 4, 6, 11, 24, 32, 67, 70, 74, 83, 86, 91, 98, 109, 113, 118, 119, 121, 122, 123, 132, 135, 140], "supervis": [1, 4, 6, 24, 29, 32, 70, 74, 91, 98, 109, 113, 118, 121, 122, 132, 140], "learn": [1, 2, 3, 4, 6, 8, 9, 10, 11, 24, 25, 27, 28, 29, 31, 32, 33, 34, 36, 37, 38, 39, 43, 45, 51, 54, 55, 56, 57, 60, 62, 65, 67, 70, 73, 74, 84, 88, 89, 91, 95, 96, 98, 99, 109, 113, 116, 118, 119, 121, 122, 132, 134, 136, 138, 140], "eeg": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 20, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 69, 70, 72, 73, 74, 75, 76, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 108, 109, 111, 112, 113, 116, 118, 121, 122, 129, 132, 134, 136, 140], "rel": [1, 6, 24, 29, 30, 70, 74, 91, 98, 109, 113, 118, 121, 122, 132], "posit": [1, 6, 24, 27, 36, 46, 47, 48, 49, 51, 54, 63, 65, 70, 74, 91, 98, 109, 113, 118, 121, 122, 131, 132], "go": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 105], "end": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 34, 67, 90, 105, 110, 112, 113, 119, 125, 126, 127, 140], "download": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 68, 75, 76, 138], "full": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 132], "code": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 83, 86, 87, 88, 89, 99, 100, 101, 135, 137, 139, 140], "tutori": [2, 3, 4, 5, 8, 9, 10, 11, 22, 24, 26, 27, 28, 29, 30, 32, 139, 140], "show": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 19, 20, 21, 26, 28, 29, 30, 31, 32, 72, 91, 140], "you": [2, 3, 4, 5, 8, 9, 11, 12, 16, 17, 18, 19, 21, 22, 24, 27, 28, 29, 32, 34, 67, 119, 127, 135, 137, 138, 139], "how": [2, 3, 4, 5, 8, 9, 10, 11, 12, 17, 18, 19, 20, 21, 22, 24, 25, 26, 27, 28, 30, 31, 33, 67, 70, 73, 91, 96, 105, 109, 111, 113, 116, 118, 119, 132, 140], "deep": [2, 3, 4, 5, 8, 9, 10, 11, 14, 26, 27, 28, 29, 30, 31, 32, 34, 43, 60, 84, 88, 89, 95, 96, 98, 99, 101, 134, 136, 138], "bci": [2, 4, 8, 21, 26, 27, 28, 29, 30, 41, 59, 68, 69, 83, 90, 101], "competit": [2, 4, 8, 11, 14, 21, 26, 27, 28, 29, 30, 68, 69, 88, 89], "us": [2, 3, 4, 7, 8, 13, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 34, 36, 38, 39, 43, 45, 46, 47, 48, 49, 52, 55, 57, 59, 60, 63, 67, 69, 72, 77, 83, 86, 87, 88, 89, 90, 92, 94, 95, 97, 100, 101, 105, 107, 108, 110, 111, 119, 127, 130, 135, 138, 139, 140], "mode": [2, 24, 32, 67, 84, 107, 110, 119, 127, 139, 140], "For": [2, 4, 5, 8, 14, 26, 27, 28, 29, 32, 67, 103, 107, 111, 119, 121, 127, 129, 132, 136, 137, 138, 139], "we": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 20, 21, 22, 24, 26, 27, 28, 29, 30, 32, 34, 72, 86, 119, 132, 135, 138, 139], "predict": [2, 4, 5, 8, 9, 10, 11, 27, 28, 31, 67, 71, 91, 102, 119, 124, 125, 126, 127, 128, 129, 130, 131, 140], "5": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 67, 69, 83, 84, 85, 86, 88, 89, 90, 96, 97, 98, 99, 103, 119], "regress": [2, 5, 8, 24, 25, 30, 33, 70, 71, 84, 91, 96, 104, 112, 119, 124, 132, 140], "target": [2, 4, 5, 8, 9, 10, 15, 17, 18, 20, 23, 24, 27, 28, 29, 31, 45, 53, 62, 67, 68, 70, 71, 75, 77, 78, 80, 81, 112, 113, 119, 120, 121, 124, 125, 128, 129, 130, 134, 140], "correspond": [2, 5, 8, 12, 21, 29, 30, 31, 36, 39, 67, 68, 69, 70, 77, 78, 80, 111, 113, 118, 119, 120, 128], "each": [2, 4, 8, 9, 10, 11, 12, 14, 16, 17, 19, 21, 22, 26, 29, 30, 31, 35, 36, 37, 41, 46, 50, 52, 54, 55, 59, 63, 64, 66, 67, 68, 69, 70, 72, 74, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 110, 112, 113, 119, 121, 123, 125, 126, 127, 131], "The": [2, 3, 4, 5, 8, 10, 11, 12, 14, 16, 18, 20, 21, 26, 27, 29, 30, 31, 32, 35, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 51, 58, 67, 69, 71, 72, 77, 83, 86, 88, 89, 90, 92, 93, 94, 95, 97, 99, 103, 105, 106, 107, 108, 110, 111, 117, 119, 129, 130, 134, 137, 139], "were": [2, 8, 9, 11, 14, 19, 26, 30, 69, 70, 72, 86, 97, 107, 140], "record": [2, 4, 8, 9, 10, 11, 14, 16, 21, 22, 26, 31, 68, 69, 72, 74, 75, 76, 80, 84, 85, 86, 87, 88, 91, 92, 93, 94, 96, 97, 98, 99, 100, 111, 112, 113, 120, 121, 122, 140], "time": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 52, 66, 67, 68, 70, 74, 77, 83, 84, 85, 86, 87, 88, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 115, 116, 119, 120, 124, 125, 128, 131, 140], "seri": [2, 4, 5, 8, 9, 10, 29, 30, 31, 67, 71, 77, 80, 97, 98, 119, 121, 125, 140], "25": [2, 4, 5, 8, 9, 11, 12, 14, 16, 29, 31, 32, 69, 83, 84, 85, 86, 88, 89, 92, 93, 96, 98, 107], "hz": [2, 3, 4, 5, 8, 9, 11, 16, 27, 29, 30, 31, 36, 42, 54, 58, 69, 83, 86, 90, 103, 107], "so": [2, 5, 8, 9, 10, 11, 14, 16, 18, 26, 27, 28, 29, 30, 32, 36, 39, 67, 103, 112, 117, 119, 140], "an": [2, 5, 8, 10, 12, 14, 18, 19, 20, 21, 22, 26, 27, 29, 30, 32, 40, 46, 47, 48, 49, 53, 67, 69, 71, 72, 77, 80, 83, 84, 85, 87, 88, 89, 90, 91, 94, 95, 96, 97, 98, 99, 100, 102, 103, 106, 107, 109, 110, 111, 113, 119, 121, 127, 135, 136, 140], "author": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 31, 34, 86, 87, 88, 89, 90, 92, 93], "maciej": [2, 8, 140], "sliwowski": [2, 8], "maciek": [2, 8], "gmail": [2, 5, 8, 9, 10, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 31], "com": [2, 3, 5, 8, 9, 10, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 31, 75, 76, 139], "moham": [2, 8, 140], "fattouh": [2, 8, 140], "mo": [2, 8], "licens": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 31], "bsd": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 31], "3": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 30, 31, 32, 43, 45, 46, 60, 62, 63, 67, 68, 69, 72, 74, 83, 84, 88, 89, 90, 91, 94, 97, 101, 119, 120, 121, 130, 137, 140], "claus": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26], "first": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 19, 20, 26, 27, 28, 30, 39, 51, 65, 67, 70, 74, 75, 76, 83, 84, 86, 96, 99, 107, 110, 111, 113, 119, 135, 139], "In": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 18, 20, 21, 26, 27, 28, 29, 30, 32, 36, 43, 45, 46, 47, 48, 49, 51, 54, 60, 62, 63, 65, 67, 69, 107, 108, 111, 119, 132], "avail": [2, 3, 4, 8, 9, 10, 11, 12, 14, 16, 19, 22, 26, 27, 28, 29, 30, 32, 68, 74, 86, 88, 89, 99, 112, 113, 120, 121], "part": [2, 8, 16, 17, 19, 28, 29, 32, 37, 38, 51, 55, 57, 65, 86, 88, 89], "librari": [2, 3, 4, 8, 24, 26, 28, 29, 30, 34, 68, 139], "http": [2, 4, 5, 8, 12, 26, 27, 28, 29, 30, 34, 45, 62, 67, 68, 74, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 99, 100, 101, 103, 119, 129, 132, 134, 139], "searchwork": [2, 8, 68], "stanford": [2, 8, 68], "edu": [2, 4, 8, 68], "view": [2, 4, 8, 22, 68], "zk881ps0522": [2, 8, 68], "contain": [2, 5, 8, 12, 14, 16, 18, 21, 22, 26, 31, 35, 36, 37, 38, 39, 41, 42, 43, 45, 46, 51, 54, 62, 63, 65, 67, 68, 70, 73, 74, 77, 111, 112, 113, 119, 120, 121, 122, 128, 129, 135, 140], "signal": [2, 3, 4, 5, 8, 9, 10, 11, 12, 18, 20, 26, 28, 29, 30, 31, 35, 36, 37, 38, 41, 42, 46, 47, 48, 49, 51, 54, 55, 57, 58, 59, 63, 65, 69, 71, 74, 78, 79, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 110, 111, 112, 113, 117, 119, 122, 140], "differ": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 18, 21, 26, 27, 28, 29, 30, 69, 88, 89, 90, 103, 122, 137], "than": [2, 5, 8, 9, 10, 11, 12, 14, 16, 27, 32, 36, 54, 67, 80, 107, 113, 119, 140], "standard": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 32, 35, 43, 46, 47, 48, 49, 60, 63, 111, 116, 140], "setup": [2, 4, 8, 27, 137], "multipl": [2, 3, 4, 8, 9, 10, 14, 15, 16, 21, 23, 24, 27, 29, 30, 67, 70, 75, 90, 102, 103, 107, 111, 112, 117, 119, 130, 140], "trial": [2, 3, 4, 8, 19, 21, 27, 28, 29, 30, 31, 32, 67, 69, 72, 78, 80, 113, 119, 125, 126, 130, 131, 140], "usual": [2, 3, 4, 8, 16, 29, 32, 67, 119], "one": [2, 4, 8, 9, 10, 11, 14, 16, 20, 26, 27, 29, 30, 32, 40, 45, 51, 65, 67, 69, 70, 83, 86, 90, 91, 103, 111, 112, 113, 119, 120, 121, 122, 135], "per": [2, 4, 5, 8, 9, 10, 11, 27, 45, 51, 65, 69, 72, 74, 90, 101, 111, 140], "here": [2, 3, 4, 5, 8, 10, 11, 12, 21, 22, 24, 26, 27, 28, 29, 30, 32, 42, 58, 80, 90, 113], "chang": [2, 5, 8, 14, 18, 31, 44, 67, 111, 119, 127, 139], "ar": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 19, 20, 22, 24, 26, 27, 28, 29, 30, 31, 32, 34, 36, 45, 62, 67, 70, 77, 78, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 107, 108, 111, 112, 113, 117, 119, 122, 124, 128, 135, 137, 138, 139, 140], "sampl": [2, 3, 4, 5, 8, 9, 10, 14, 16, 17, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 41, 42, 45, 46, 47, 48, 49, 51, 54, 57, 58, 59, 65, 67, 69, 71, 72, 74, 78, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 112, 113, 120, 121, 122, 123, 129, 135, 140], "frequenc": [2, 3, 4, 8, 11, 12, 16, 17, 26, 27, 28, 29, 30, 31, 32, 36, 42, 54, 58, 72, 78, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 110, 117, 120, 140], "equal": [2, 8, 32, 78, 79, 80, 91, 104, 112], "If": [2, 8, 14, 18, 19, 22, 26, 29, 30, 32, 34, 36, 45, 67, 68, 69, 70, 72, 73, 74, 75, 76, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 108, 109, 110, 111, 112, 113, 117, 118, 119, 120, 122, 123, 127, 128, 129, 130, 135, 139], "pleas": [2, 3, 4, 5, 8, 11, 12, 22, 26, 27, 28, 29, 30, 32, 68, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 117, 139, 140], "cite": [2, 8, 68], "1": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 30, 31, 33, 36, 37, 38, 39, 41, 43, 44, 45, 46, 47, 48, 49, 51, 53, 54, 55, 56, 57, 59, 60, 62, 63, 65, 67, 68, 69, 70, 72, 74, 75, 76, 81, 83, 84, 88, 89, 90, 91, 94, 96, 97, 99, 101, 103, 104, 107, 110, 111, 112, 113, 114, 115, 116, 119, 120, 121, 129, 130, 131, 134], "miller": [2, 8, 27, 28, 29, 30, 68], "kai": [2, 8, 68], "j": [2, 4, 5, 8, 26, 27, 28, 29, 30, 31, 36, 39, 41, 43, 51, 54, 56, 59, 60, 65, 68, 84, 87, 92, 93, 95, 96, 98, 100, 101, 134], "A": [2, 3, 4, 5, 8, 9, 10, 16, 27, 28, 29, 30, 31, 35, 37, 38, 41, 53, 55, 57, 59, 67, 68, 70, 73, 75, 76, 85, 88, 89, 90, 92, 93, 97, 98, 101, 107, 111, 112, 113, 118, 119, 122, 130, 134, 140], "human": [2, 8, 26, 31, 34, 39, 56, 68, 84, 95, 96, 107, 134], "electrocorticograph": [2, 8, 68], "analys": [2, 8, 29, 30, 68], "natur": [2, 8, 14, 68], "behaviour": [2, 8, 68], "11": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 19, 20, 21, 27, 28, 29, 31, 32, 68, 85], "2019": [2, 8, 31, 68], "1225": [2, 8, 68], "1235": [2, 8, 68], "doi": [2, 8, 10, 26, 27, 28, 29, 30, 34, 68, 83, 84, 87, 88, 89, 95, 96, 97, 99, 101, 134], "org": [2, 4, 5, 8, 26, 27, 28, 29, 30, 34, 45, 62, 67, 68, 74, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 99, 100, 101, 103, 119, 129, 132, 134], "10": [2, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 33, 34, 39, 46, 47, 48, 49, 63, 67, 68, 83, 84, 86, 87, 88, 89, 95, 96, 97, 99, 101, 107, 111, 119, 120, 134], "1038": [2, 8, 68], "s41562": [2, 8, 68], "019": [2, 8, 68, 97], "0678": [2, 8, 68], "import": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 41, 59, 135, 139], "copi": [2, 11, 16, 41, 59, 68, 105, 135], "numpi": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 17, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 63, 67, 107, 110, 119, 132, 134], "np": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 26, 29, 31, 32, 67, 115, 116, 119, 120, 121, 122, 123, 130], "sklearn": [2, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 30, 31, 67, 119, 127, 134, 140], "from": [2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 37, 38, 41, 45, 46, 47, 48, 49, 55, 57, 59, 63, 67, 69, 71, 72, 74, 75, 76, 77, 78, 79, 80, 81, 83, 84, 85, 87, 88, 89, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 111, 112, 113, 119, 120, 121, 122, 123, 125, 126, 127, 129, 130, 137, 140], "mne": [2, 3, 4, 8, 9, 10, 11, 12, 14, 15, 17, 18, 20, 22, 23, 24, 25, 28, 30, 33, 46, 63, 68, 70, 71, 74, 77, 79, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 105, 106, 107, 108, 109, 110, 111, 112, 113, 117, 119, 135, 140], "set_log_level": [2, 8, 12, 14, 22], "bcicompetitionivdataset4": [2, 8, 140], "subject_id": [2, 3, 4, 5, 8, 9, 10, 11, 16, 17, 18, 19, 20, 21, 27, 28, 29, 30, 32, 68, 69, 72, 73, 74, 140], "can": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 20, 21, 22, 26, 27, 28, 29, 30, 32, 34, 42, 46, 63, 67, 70, 74, 75, 76, 77, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 106, 107, 108, 110, 111, 119, 130, 137, 138, 140], "easili": [2, 8, 20, 26, 28, 29, 30, 32, 121], "addit": [2, 8, 12, 17, 20, 21, 26, 28, 29, 30, 32, 43, 60, 67, 69, 70, 71, 77, 80, 113, 119, 134], "info": [2, 3, 4, 8, 12, 14, 16, 17, 19, 20, 21, 26, 27, 28, 29, 30, 32, 70, 77, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 108, 111, 121, 123, 135, 140], "store": [2, 4, 8, 9, 10, 11, 12, 14, 18, 22, 28, 29, 30, 32, 68, 70, 81, 140], "descript": [2, 5, 8, 12, 17, 18, 19, 20, 22, 27, 28, 29, 30, 32, 68, 69, 70, 71, 75, 76, 77, 80, 81, 83, 86, 88, 90, 92, 93, 94, 95, 97, 103, 112, 113], "attribut": [2, 8, 26, 28, 29, 30, 32, 67, 71, 77, 109, 119, 140], "case": [2, 8, 16, 21, 26, 27, 28, 29, 30, 32, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 111, 119, 132, 138, 140], "session": [2, 4, 8, 12, 18, 20, 21, 27, 28, 29, 30, 31, 32, 69, 72, 121], "column": [2, 8, 19, 21, 22, 27, 28, 29, 30, 32, 70, 77, 81, 91, 120, 121, 134], "select": [2, 4, 8, 9, 16, 20, 27, 28, 29, 30, 32, 36, 72, 111, 120], "valid": [2, 21, 26, 27, 31, 32, 67, 99, 111, 112, 113, 119, 127, 128, 140], "final": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 26, 27, 28, 29, 30, 32, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 116], "evalu": [2, 3, 4, 5, 8, 9, 10, 11, 14, 21, 27, 28, 30, 100], "train_set": [2, 3, 4, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32], "test_set": [2, 8, 29, 31, 32], "now": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 22, 26, 27, 28, 30, 111, 139, 140], "appli": [2, 3, 4, 5, 8, 9, 10, 12, 16, 18, 19, 20, 26, 27, 28, 29, 30, 32, 35, 36, 37, 38, 39, 41, 42, 43, 46, 47, 48, 49, 50, 51, 52, 53, 54, 67, 71, 77, 97, 98, 102, 107, 109, 111, 117, 118, 119, 129, 140], "like": [2, 8, 16, 26, 28, 29, 30, 32, 36, 41, 46, 54, 59, 63, 67, 78, 79, 80, 99, 107, 108, 119, 121, 139, 140], "bandpass": [2, 3, 4, 8, 20, 27, 28, 29, 30, 32, 69, 107, 117], "filter": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 20, 26, 27, 28, 29, 30, 32, 36, 54, 69, 83, 84, 86, 88, 89, 90, 93, 96, 98, 100, 101, 103, 109, 110, 117, 140], "our": [2, 5, 8, 9, 10, 11, 12, 16, 20, 26, 27, 28, 30, 32, 72, 137], "either": [2, 8, 26, 28, 29, 30, 67, 69, 70, 72, 91, 107, 111, 119, 130], "provid": [2, 8, 9, 10, 11, 26, 28, 30, 32, 34, 67, 69, 70, 71, 75, 76, 102, 107, 108, 109, 118, 119, 135], "raw": [2, 3, 4, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 27, 28, 29, 30, 31, 70, 71, 74, 75, 76, 80, 85, 105, 106, 107, 108, 109, 111, 112, 113, 117, 136, 140], "epoch": [2, 3, 4, 5, 8, 9, 10, 11, 14, 19, 24, 25, 27, 28, 29, 30, 31, 32, 33, 67, 70, 77, 79, 80, 91, 96, 105, 106, 107, 108, 109, 111, 112, 113, 119, 122, 125, 126, 127, 140], "your": [2, 3, 4, 8, 14, 16, 21, 24, 25, 27, 28, 30, 33, 34, 67, 70, 73, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 109, 113, 116, 118, 119, 132, 135, 137], "own": [2, 8, 27, 28, 29, 30, 32, 72, 135], "object": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 18, 19, 21, 27, 28, 29, 30, 31, 32, 40, 71, 74, 75, 76, 77, 80, 105, 109, 112, 113, 118, 134, 140], "underli": [2, 5, 8, 28, 30, 109], "arrai": [2, 4, 8, 11, 17, 22, 26, 28, 29, 30, 36, 46, 53, 54, 63, 67, 78, 79, 80, 107, 108, 109, 110, 119, 123, 130, 134], "step": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 18, 22, 28, 29, 30, 32, 80, 113, 135], "taken": [2, 5, 8, 14], "process": [2, 4, 5, 7, 8, 13, 14, 15, 16, 22, 24, 29, 30, 70, 75, 109, 112, 118, 140], "pipelin": [2, 5, 8, 29, 32], "onli": [2, 4, 5, 8, 9, 10, 11, 12, 14, 18, 19, 21, 26, 27, 29, 30, 32, 40, 53, 67, 72, 74, 80, 87, 88, 89, 90, 92, 93, 105, 107, 108, 110, 111, 113, 119, 128, 135, 139, 140], "cutoff": [2, 8, 16, 107], "proper": [2, 8], "other": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 18, 26, 29, 30, 32, 53, 67, 72, 74, 83, 84, 85, 91, 94, 95, 96, 97, 98, 99, 100, 103, 119], "mai": [2, 3, 4, 5, 8, 9, 10, 11, 16, 18, 19, 27, 28, 29, 32, 34, 67, 119, 127, 132, 135], "need": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 26, 27, 28, 29, 32, 67, 83, 86, 90, 119, 132, 137, 140], "These": [2, 5, 8, 26, 27, 28, 30], "prepocess": [2, 8, 28, 30], "directli": [2, 3, 5, 8, 12, 22, 26, 27, 28, 30, 31, 67, 77, 109, 111, 119, 139], "fly": [2, 8, 28, 30, 71, 77, 140], "transform": [2, 5, 8, 9, 10, 11, 20, 27, 28, 29, 30, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 64, 65, 66, 67, 71, 77, 78, 79, 80, 86, 91, 119, 140], "pytorch": [2, 8, 14, 22, 24, 25, 26, 27, 28, 30, 33, 67, 70, 73, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 109, 113, 116, 118, 119, 130, 132, 138, 140], "torchvis": [2, 8, 28, 30], "preprocessor": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 18, 20, 27, 28, 29, 30, 32, 118, 140], "exponential_moving_standard": [2, 3, 4, 8, 27, 28, 29, 30, 32], "low_cut_hz": [2, 3, 4, 8, 27, 28, 29, 30, 32], "low": [2, 3, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 30, 32, 36, 54, 88, 89, 107], "high_cut_hz": [2, 3, 4, 5, 8, 9, 10, 27, 28, 29, 30, 32], "200": [2, 8, 10, 11, 14, 84], "high": [2, 3, 4, 8, 11, 27, 28, 29, 30, 32, 36, 54, 72, 88, 89, 103, 107, 120], "higher": [2, 5, 8, 32, 99], "paramet": [2, 3, 4, 5, 8, 10, 14, 16, 17, 18, 19, 26, 28, 29, 30, 31, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 105, 106, 107, 108, 109, 110, 111, 112, 113, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 127, 128, 129, 130, 131, 132, 134, 140], "exponenti": [2, 3, 4, 8, 27, 28, 29, 30, 32, 103, 115, 116], "move": [2, 3, 4, 8, 14, 16, 27, 28, 29, 30, 32, 68, 91, 115, 116, 140], "factor_new": [2, 3, 4, 8, 27, 28, 29, 30, 32, 115, 116], "1e": [2, 3, 4, 8, 9, 10, 11, 27, 28, 29, 30, 32], "init_block_s": [2, 3, 4, 8, 27, 28, 29, 30, 32, 115, 116], "1000": [2, 3, 4, 8, 12, 22, 26, 27, 28, 29, 30, 32, 72, 88, 89, 121], "30": [2, 5, 8, 9, 10, 11, 16, 27, 31, 32, 74, 96, 97, 98, 99, 103], "second": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 30, 31, 32, 39, 69, 72, 75, 76, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 105], "limit": [2, 5, 8, 11, 12, 16, 26, 105], "memori": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 67, 113, 119], "run": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 67, 69, 72, 80, 83, 86, 90, 97, 107, 109, 110, 113, 119, 121, 132, 135, 139, 140], "6": [2, 3, 4, 5, 9, 10, 11, 12, 16, 17, 18, 19, 20, 21, 26, 27, 28, 29, 30, 31, 32, 33, 69, 72, 86, 107], "To": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 17, 22, 26, 27, 28, 29, 30, 31, 32, 107, 138, 139], "obtain": [2, 3, 4, 5, 8, 9, 11, 27, 28, 46, 63, 67, 71, 72, 77, 119, 121], "whole": [2, 8, 9, 10], "should": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 20, 26, 27, 28, 30, 36, 39, 46, 51, 54, 63, 65, 67, 68, 70, 71, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 105, 107, 108, 110, 111, 119, 127, 135, 139], "valid_set": [2, 3, 8, 9, 10, 11, 27, 28, 31], "deepcopi": 2, "tmin": [2, 8, 12, 16, 19, 105], "24": [2, 5, 9, 10, 11, 12, 16, 27, 32, 97, 101, 108], "tmax": [2, 8, 12, 105], "n_job": [2, 3, 4, 5, 12, 14, 16, 27, 28, 29, 30, 32, 75, 76, 81, 107, 110, 112, 113, 114, 118, 140], "0": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 41, 43, 44, 45, 53, 55, 57, 59, 62, 67, 69, 70, 74, 75, 76, 80, 83, 84, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 101, 103, 105, 106, 107, 108, 110, 111, 112, 113, 115, 116, 119, 121, 130, 134], "baseconcatdataset": [2, 5, 9, 10, 12, 14, 16, 21, 31, 67, 78, 79, 80, 81, 112, 113, 118, 119, 121, 130, 140], "0x7f4b8149c400": 2, "variabl": [2, 4, 8, 29, 30, 68, 132], "channel": [2, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 19, 26, 31, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 51, 55, 56, 57, 58, 59, 60, 62, 63, 65, 74, 77, 78, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 106, 107, 108, 111, 112, 113, 117, 140], "type": [2, 3, 4, 8, 11, 26, 27, 28, 29, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 51, 62, 67, 70, 72, 78, 79, 80, 81, 90, 91, 102, 104, 107, 108, 110, 111, 112, 113, 115, 116, 118, 119, 121, 123, 129, 131, 134, 140], "misc": [2, 4, 8, 77], "thu": [2, 4, 8, 105], "those": [2, 4, 5, 8, 12, 67, 107, 108, 119], "have": [2, 4, 5, 8, 11, 12, 14, 16, 17, 19, 21, 26, 27, 28, 29, 30, 32, 46, 51, 63, 65, 67, 78, 79, 80, 90, 109, 111, 112, 119, 127, 135, 138, 139, 140], "further": [2, 4, 5, 8, 9, 10, 11, 27, 29, 32, 67, 119], "howev": [2, 3, 4, 5, 8, 11, 14, 16, 21, 26, 27, 28, 29, 113], "mani": [2, 4, 5, 8, 16, 26, 27, 29, 32, 70], "ignor": [2, 4, 8, 51, 67, 83, 86, 90, 106, 109, 112, 113, 119, 122], "perform": [2, 4, 8, 9, 10, 11, 26, 27, 28, 29, 30, 32, 69, 70, 72, 83, 86, 90, 99, 115, 116, 140], "oper": [2, 3, 4, 8, 16, 36, 37, 38, 39, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 61, 105, 110], "see": [2, 3, 4, 5, 8, 9, 10, 11, 16, 18, 20, 21, 24, 26, 27, 28, 29, 30, 32, 45, 62, 67, 68, 69, 72, 74, 76, 77, 87, 91, 92, 93, 95, 100, 101, 105, 106, 107, 108, 110, 111, 112, 113, 118, 119, 120, 122, 123, 129, 132, 135, 138, 139], "tool": [2, 4, 8, 74, 136, 139], "stabl": [2, 4, 5, 8, 16, 26, 67, 74, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 119, 132, 134], "glossari": [2, 4, 8], "html": [2, 4, 5, 8, 12, 26, 27, 67, 74, 75, 76, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 119, 132, 134], "term": [2, 4, 8, 85, 91], "todo": 2, "ensur": [2, 103, 132, 138], "remov": [2, 3, 4, 5, 8, 9, 11, 18, 19, 20, 21, 26, 27, 28, 29, 30, 31, 32, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 106, 111, 131, 140], "pick_typ": [2, 3, 4, 8, 20, 27, 28, 29, 30, 32, 106], "true": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 26, 27, 28, 29, 30, 31, 32, 45, 46, 47, 48, 49, 67, 70, 71, 74, 75, 76, 77, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 109, 111, 112, 113, 114, 117, 119, 122, 123, 125, 126, 127, 130, 132, 140], "lambda": [2, 3, 4, 5, 8, 9, 10, 12, 27, 28, 29, 30, 32, 67, 94, 119], "x": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 20, 22, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 78, 79, 80, 83, 85, 86, 90, 95, 97, 98, 99, 100, 101, 102, 103, 110, 115, 116, 119, 124, 127, 128, 130], "1e6": [2, 3, 4, 5, 8, 9, 10, 12, 27, 28, 29, 30, 32], "pick": [2, 8, 10, 12, 19, 20, 107, 112, 113, 114, 140], "convert": [2, 3, 4, 5, 8, 9, 10, 12, 17, 19, 27, 28, 29, 30, 31, 32, 107], "v": [2, 3, 4, 5, 8, 9, 10, 12, 16, 27, 28, 29, 30, 32, 88, 89, 92, 93, 100], "uv": [2, 3, 4, 5, 8, 9, 10, 12, 27, 28, 29, 30, 32], "l_freq": [2, 3, 4, 5, 8, 9, 10, 16, 27, 28, 29, 30, 32, 107], "h_freq": [2, 3, 4, 5, 8, 9, 10, 16, 27, 28, 29, 30, 32, 107], "extract": [2, 8, 12, 14, 16, 17, 19, 22, 27, 32, 77, 88, 89, 90, 97, 99, 112, 113, 120, 122], "check": [2, 3, 4, 8, 9, 10, 11, 26, 27, 28, 29, 30, 32, 34, 83, 84, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 100, 101, 103, 135, 138, 140], "thei": [2, 3, 4, 8, 14, 16, 26, 27, 28, 29, 30, 32, 111, 140], "same": [2, 3, 4, 5, 8, 9, 10, 11, 14, 18, 21, 27, 28, 29, 30, 32, 42, 51, 58, 65, 67, 72, 74, 99, 119, 122], "all": [2, 3, 4, 8, 12, 14, 16, 24, 26, 27, 28, 29, 30, 32, 42, 43, 51, 58, 60, 65, 67, 68, 69, 72, 73, 74, 83, 86, 88, 89, 90, 91, 105, 107, 108, 110, 111, 112, 113, 119, 127, 140], "sfreq": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 20, 26, 27, 28, 29, 30, 31, 32, 36, 42, 54, 58, 78, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 119, 140], "assert": [2, 3, 4, 8, 12, 14, 27, 28, 29, 30, 32], "d": [2, 3, 4, 5, 8, 12, 14, 22, 26, 27, 28, 29, 30, 31, 32, 37, 38, 41, 55, 57, 59, 83, 84, 93, 95, 96, 97, 101, 122, 134, 140], "target_sfreq": [2, 8], "temp": [2, 8], "home": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 19, 26, 27, 28, 29, 30, 31, 32], "runner": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 19, 26, 27, 28, 29, 30, 31, 32], "work": [2, 3, 4, 5, 8, 9, 10, 12, 16, 18, 19, 20, 22, 24, 26, 27, 28, 29, 30, 31, 32, 67, 91, 103, 105, 119, 127, 136, 138, 140], "py": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 33], "55": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 32], "userwarn": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 18, 19, 26, 27, 28, 29, 30, 31, 32], "choic": [2, 3, 4, 5, 8, 9, 10, 12, 27, 28, 29, 30, 32, 86, 140], "cannot": [2, 3, 4, 5, 8, 9, 10, 11, 12, 27, 28, 29, 30, 32, 67, 105, 119], "save": [2, 3, 4, 5, 8, 9, 10, 12, 14, 15, 16, 23, 24, 27, 28, 29, 30, 32, 67, 70, 73, 81, 109, 113, 118, 119, 140], "warn": [2, 3, 4, 5, 8, 9, 10, 12, 14, 16, 18, 19, 26, 27, 28, 29, 30, 31, 32, 69, 99, 106, 112, 113, 132, 140], "contrast": [2, 4, 5, 27, 36, 43, 51, 54, 60, 65], "trialwis": [2, 4, 8, 20, 27, 28, 30, 67, 119, 130, 140], "befor": [2, 11, 16, 27, 28, 29, 30, 32, 67, 70, 71, 74, 77, 83, 84, 85, 86, 97, 98, 99, 115, 116, 119, 127, 132, 138, 140], "becaus": [2, 16, 26, 27, 29, 30, 135], "know": [2, 3, 4, 26, 27], "recept": [2, 27, 67, 119, 130], "field": [2, 27, 67, 111, 119, 130], "network": [2, 4, 5, 7, 8, 10, 13, 14, 25, 26, 27, 28, 29, 32, 33, 34, 43, 60, 67, 70, 71, 74, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 109, 112, 113, 118, 119, 121, 123, 124, 130, 132, 134, 140], "larg": [2, 5, 14, 16, 26, 27, 70, 113], "stride": [2, 9, 10, 11, 26, 27, 78, 79, 80, 84, 86, 91, 96, 101, 112, 113], "choos": [2, 3, 4, 8, 18, 27, 28, 29, 30, 32], "input": [2, 3, 4, 8, 10, 11, 14, 21, 26, 27, 28, 29, 32, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 64, 65, 66, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 119, 140], "size": [2, 3, 4, 5, 11, 14, 16, 26, 27, 28, 29, 30, 31, 32, 36, 51, 54, 65, 67, 78, 79, 80, 83, 86, 88, 89, 90, 91, 97, 98, 100, 101, 103, 104, 107, 110, 112, 113, 119, 122, 124, 128, 130, 134], "fed": [2, 27, 47, 48, 49], "dure": [2, 4, 5, 8, 9, 10, 11, 12, 14, 27, 28, 29, 30, 32, 67, 68, 107, 111, 119, 140], "ha": [2, 3, 4, 5, 8, 10, 12, 18, 19, 20, 21, 22, 27, 28, 29, 30, 31, 32, 47, 48, 49, 67, 70, 71, 74, 77, 80, 87, 88, 89, 90, 92, 93, 103, 107, 113, 119, 129, 135, 140], "larger": [2, 5, 27, 88, 89], "otherwis": [2, 14, 27, 29, 31, 80, 113], "chosen": [2, 16, 18, 27, 32, 51, 67, 107, 119, 130], "effici": [2, 3, 16, 27], "explan": [2, 27, 117, 118], "begin": [2, 27, 29, 30, 69, 97, 107, 112], "which": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 19, 20, 21, 24, 26, 27, 29, 30, 32, 34, 35, 38, 41, 46, 57, 59, 63, 67, 70, 71, 72, 77, 91, 99, 102, 107, 110, 111, 119, 121, 122, 123, 135], "rate": [2, 5, 14, 27, 28, 29, 30, 31, 32, 67, 72, 86, 88, 89, 97, 98, 99, 103, 119, 140], "input_window_sampl": [2, 3, 4, 8, 14, 26, 27, 28, 29, 30, 31, 32, 84, 86, 87, 88, 89, 92, 93, 94, 95, 96, 101, 104], "come": [2, 8, 14, 28, 30, 32, 123, 132], "some": [2, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 22, 26, 27, 28, 30, 34, 67, 70, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 111, 119, 132], "predefin": [2, 8, 28, 30], "convolut": [2, 5, 8, 9, 11, 24, 25, 26, 27, 28, 29, 30, 33, 34, 41, 43, 59, 60, 70, 71, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 112, 124, 132, 134, 140], "neural": [2, 4, 5, 8, 9, 10, 11, 14, 25, 26, 27, 28, 29, 33, 34, 43, 60, 70, 71, 84, 85, 86, 88, 89, 90, 91, 95, 96, 97, 98, 99, 101, 104, 112, 124, 132, 134, 140], "architectur": [2, 5, 8, 9, 10, 11, 26, 27, 28, 30, 67, 85, 86, 97, 98, 99, 103, 119, 136], "domain": [2, 4, 8, 16, 28, 30, 42, 58, 103, 107, 110], "shallow": [2, 8, 14, 26, 27, 28, 31, 96], "convnet": [2, 8, 26, 27, 28, 84, 95, 96], "visual": [2, 8, 9, 10, 11, 12, 26, 27, 28, 30, 31, 34, 72, 84, 86, 95, 96, 136, 140], "pure": [2, 5, 8, 28, 30, 140], "therefor": [2, 8, 12, 16, 27, 28, 29, 30, 32, 127], "just": [2, 4, 8, 22, 26, 28, 29, 30, 67, 84, 96, 119], "normal": [2, 5, 8, 9, 10, 28, 30, 97, 98, 121, 134, 140], "nn": [2, 3, 4, 5, 8, 9, 10, 11, 14, 26, 27, 28, 29, 30, 31, 32, 67, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 102, 103, 119, 130], "modul": [2, 4, 5, 8, 9, 10, 11, 14, 26, 28, 30, 32, 67, 83, 86, 88, 89, 90, 99, 102, 119, 130, 132, 134, 138, 140], "torch": [2, 3, 4, 5, 8, 9, 10, 11, 14, 22, 26, 27, 28, 29, 30, 31, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 119, 124, 128, 129, 130, 132, 140], "shallowfbcspnet": [2, 3, 4, 8, 14, 26, 27, 28, 29, 30, 31, 32], "util": [2, 3, 4, 5, 8, 9, 10, 11, 14, 18, 22, 26, 27, 28, 30, 31, 32, 67, 119, 140], "set_random_se": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32, 140], "cuda": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32, 67, 107, 110, 119, 132, 138], "is_avail": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32], "gpu": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 32, 67, 119, 138, 140], "devic": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32, 35, 67, 119, 140], "els": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 27, 28, 29, 30, 31, 32, 67, 119], "cpu": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 32, 67, 119], "backend": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32, 132, 140], "cudnn": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32, 132, 140], "benchmark": [2, 3, 4, 5, 8, 9, 10, 11, 15, 23, 24, 27, 28, 29, 30, 31, 32, 70, 74, 76, 84, 96, 109, 112, 118, 132, 140], "set": [2, 4, 8, 9, 10, 11, 12, 14, 16, 17, 19, 22, 26, 27, 29, 30, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 62, 67, 69, 70, 72, 84, 88, 89, 90, 96, 97, 98, 101, 103, 105, 108, 111, 112, 113, 119, 132, 138, 140], "random": [2, 3, 4, 5, 8, 9, 10, 11, 26, 27, 28, 30, 31, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 72, 120, 121, 122, 123, 127, 132, 140], "seed": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 60, 132], "abl": [2, 3, 4, 5, 8, 9, 10, 11, 12, 27, 28, 30, 67, 119, 135], "roughli": [2, 3, 4, 5, 8, 9, 11, 27, 28, 72], "reproduc": [2, 3, 4, 5, 8, 9, 10, 11, 24, 27, 28, 30, 132, 140], "note": [2, 3, 4, 5, 8, 9, 11, 17, 20, 26, 27, 28, 42, 58, 67, 68, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 108, 111, 119, 127, 132], "indetermin": [2, 3, 4, 5, 8, 9, 11, 27, 28], "still": [2, 3, 4, 5, 8, 9, 11, 27, 28, 29, 72], "make": [2, 3, 4, 5, 8, 9, 11, 12, 27, 28, 29, 30, 32, 99, 107, 135, 140], "substanti": [2, 3, 4, 5, 8, 9, 10, 11, 14, 19, 27, 28], "between": [2, 3, 4, 5, 8, 9, 11, 26, 27, 28, 29, 36, 37, 38, 41, 42, 45, 46, 47, 48, 49, 53, 54, 55, 57, 59, 62, 69, 78, 79, 80, 84, 86, 96, 97, 105, 112, 113, 123, 128], "consist": [2, 3, 4, 5, 8, 9, 11, 27, 28, 47, 48, 49, 69, 72], "cost": [2, 3, 4, 5, 8, 9, 11, 27, 28], "increas": [2, 3, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 32, 90, 99], "cudnn_benchmark": [2, 3, 4, 5, 8, 9, 11, 27, 28, 132], "fals": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 22, 26, 27, 28, 29, 30, 31, 32, 41, 45, 46, 47, 48, 49, 59, 63, 67, 68, 70, 71, 74, 75, 76, 77, 80, 82, 83, 84, 85, 86, 91, 96, 97, 98, 99, 100, 103, 105, 109, 111, 112, 113, 114, 117, 118, 119, 122, 123, 125, 126, 132, 134, 140], "20200220": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "n_class": [2, 3, 4, 9, 10, 11, 14, 26, 27, 28, 29, 30, 31, 32, 67, 83, 84, 85, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 101, 103, 119, 124, 128, 130], "number": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 22, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 60, 63, 65, 67, 70, 74, 75, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 110, 112, 113, 117, 118, 119, 120, 121, 122, 123, 130, 131], "chan": [2, 3, 4, 8, 27, 28, 29, 30, 32, 72], "n_chan": [2, 8, 11, 26, 27, 28, 30, 31, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 119], "shape": [2, 3, 4, 5, 8, 9, 10, 11, 17, 20, 22, 26, 27, 28, 29, 30, 32, 46, 63, 67, 85, 86, 91, 95, 97, 98, 99, 100, 101, 102, 103, 104, 123, 124, 128], "final_conv_length": [2, 3, 4, 8, 14, 26, 27, 28, 29, 30, 31, 32, 84, 92, 93, 96, 140], "2": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 30, 31, 36, 37, 38, 41, 42, 43, 45, 51, 54, 59, 60, 62, 65, 67, 69, 72, 74, 83, 84, 88, 89, 91, 92, 93, 94, 97, 99, 101, 103, 107, 111, 116, 119, 120, 121, 129, 130], "add_log_softmax": [2, 8, 26, 31, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103], "send": [2, 3, 4, 8, 9, 10, 11, 16, 27, 28, 29, 30, 32], "get_output_shap": [2, 27, 31, 91, 140], "to_dense_prediction_model": [2, 27, 31, 91, 140], "local": [2, 5, 10, 11, 14, 27, 31, 32, 68, 111, 135, 139], "lib": [2, 5, 10, 11, 27, 31, 32], "python3": [2, 5, 10, 11, 27, 31, 32], "site": [2, 5, 10, 11, 27, 31, 32], "packag": [2, 5, 10, 11, 27, 31, 32, 34, 137, 138], "deprec": [2, 5, 10, 19, 31, 88, 140], "86": [2, 11, 16, 31], "futurewarn": [2, 26, 30, 31, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103], "version": [2, 3, 4, 5, 9, 10, 18, 20, 21, 22, 29, 30, 31, 67, 86, 91, 105, 106, 107, 108, 110, 111, 119, 135, 137, 138, 139], "eegmodulemixin": [2, 31, 140], "method": [2, 4, 5, 8, 12, 16, 21, 26, 29, 31, 32, 34, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 67, 68, 70, 71, 77, 83, 85, 86, 90, 91, 95, 96, 97, 98, 99, 100, 101, 102, 103, 107, 109, 111, 119, 120, 121, 122, 124, 125, 126, 127, 128, 140], "msg": [2, 31], "categori": [2, 4, 31], "calcul": [2, 3, 4, 27, 28, 29, 30, 32, 67, 101, 119], "output": [2, 3, 4, 5, 11, 12, 14, 21, 26, 27, 28, 29, 30, 31, 32, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 107, 108, 110, 111, 112, 113, 119], "dummi": [2, 27], "n_preds_per_input": [2, 27, 31], "create_fixed_length_window": [2, 5, 12, 14, 16, 22, 31, 140], "It": [2, 3, 4, 8, 9, 10, 11, 18, 27, 28, 29, 30, 32, 41, 59, 67, 70, 77, 80, 99, 113, 119, 136], "defin": [2, 5, 9, 10, 11, 12, 14, 20, 21, 27, 28, 30, 39, 53, 56, 67, 77, 83, 86, 90, 101, 113, 119, 122], "start_offset_sampl": [2, 14, 22, 31, 112], "stop_offset_sampl": [2, 14, 22, 31, 112, 140], "none": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 18, 19, 20, 22, 26, 27, 28, 29, 31, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 57, 59, 60, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 108, 110, 111, 112, 113, 114, 115, 116, 118, 119, 120, 121, 122, 123, 125, 126, 127, 132, 134, 140], "window_size_sampl": [2, 5, 8, 9, 10, 11, 12, 14, 17, 19, 22, 27, 31, 78, 79, 80, 112, 113, 114], "window_stride_sampl": [2, 5, 9, 10, 11, 12, 14, 17, 19, 22, 27, 31, 78, 79, 80, 112, 113], "drop_last_window": [2, 12, 14, 17, 19, 22, 27, 31, 78, 79, 80, 112, 113], "targets_from": [2, 77, 112, 119], "last_target_onli": [2, 8, 77, 112, 114], "preload": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 22, 27, 28, 29, 30, 31, 32, 74, 75, 76, 80, 81, 111, 112, 113, 114, 118, 140], "thumb": [2, 8, 27], "": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 21, 22, 26, 27, 28, 30, 31, 32, 39, 41, 43, 46, 47, 48, 49, 56, 59, 60, 63, 67, 68, 69, 71, 72, 73, 74, 75, 76, 83, 89, 90, 92, 93, 98, 100, 103, 106, 107, 109, 111, 119, 120, 124, 127, 128], "consid": [2, 4, 29, 32, 47, 48, 49, 67, 119, 127], "well": [2, 5, 8, 12, 26, 27, 28, 29, 32, 80, 113, 136, 140], "encourag": [2, 8, 24, 27, 28], "find": [2, 4, 8, 30], "wai": [2, 5, 8, 16, 21, 24, 26, 29, 99, 137, 139], "target_transform": [2, 8, 9, 10, 70, 140], "suppli": [2, 3, 5, 8, 9, 10, 11, 27, 28, 29], "eegclassifi": [2, 5, 9, 10, 11, 26, 27, 28, 29, 30, 140], "croppedloss": [2, 27, 31], "criterion": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 67, 119], "criterion__loss_funct": [2, 27, 31], "loss": [2, 3, 4, 5, 8, 9, 10, 11, 14, 26, 27, 28, 29, 30, 31, 32, 67, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 119, 124, 128, 129], "mean": [2, 3, 4, 8, 10, 12, 14, 16, 19, 26, 27, 29, 30, 31, 32, 72, 84, 93, 96, 111, 115, 116, 119, 135], "default": [2, 8, 11, 12, 27, 28, 30, 31, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 67, 68, 74, 75, 76, 77, 80, 83, 84, 86, 88, 89, 90, 91, 105, 106, 107, 108, 110, 111, 113, 119, 127, 132, 140], "found": [2, 8, 10, 12, 16, 18, 19, 20, 26, 27, 28, 29, 32, 68, 111, 112, 113], "motor": [2, 4, 8, 27, 28, 69, 72, 83, 87, 90, 140], "strongli": [2, 8, 27, 28, 88, 89, 90], "hyperparamet": [2, 5, 8, 9, 10, 11, 14, 24, 25, 27, 28, 32, 33, 45, 67, 70, 73, 91, 96, 109, 113, 116, 118, 119, 132, 140], "optim": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32, 67, 72, 119], "cross": [2, 8, 16, 27, 28, 69], "skorch": [2, 3, 4, 5, 8, 9, 10, 11, 17, 26, 27, 28, 29, 30, 31, 67, 78, 79, 80, 119, 140], "callback": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32, 67, 119, 127], "lrschedul": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "helper": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31], "predefined_split": [2, 3, 5, 8, 9, 10, 11, 27, 28, 29, 31], "eegregressor": [2, 8, 26, 31, 140], "croppedtimeseriesepochscor": 2, "timeseriesloss": 2, "valu": [2, 4, 5, 8, 9, 10, 11, 12, 26, 27, 28, 30, 31, 32, 42, 45, 62, 67, 70, 71, 77, 80, 90, 101, 107, 108, 110, 111, 112, 113, 119, 128, 129, 130, 140], "good": [2, 8, 26, 27, 28], "mi": [2, 8], "lr": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32, 67, 119], "0625": [2, 3, 4, 8, 27, 28, 29, 32], "01": [2, 3, 4, 6, 8, 12, 16, 23, 26, 27, 28, 29, 32, 67, 88, 89, 119], "weight_decai": [2, 3, 4, 8, 27, 28, 29, 32], "batch_siz": [2, 3, 4, 5, 8, 9, 10, 11, 14, 22, 27, 28, 29, 30, 31, 32, 36, 45, 46, 54, 62, 63, 67, 85, 86, 91, 95, 97, 98, 99, 100, 101, 102, 104, 119, 124, 128, 130, 133], "27": [2, 4, 9, 11, 16, 29, 72], "64": [2, 3, 4, 5, 8, 10, 11, 14, 16, 17, 19, 27, 28, 29, 30, 32, 83, 93, 98], "n_epoch": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32], "8": [2, 3, 4, 5, 8, 9, 10, 11, 13, 14, 16, 17, 18, 19, 20, 21, 26, 27, 28, 29, 30, 31, 32, 33, 83, 86, 88, 89, 92, 93, 98, 117, 137], "regressor": [2, 8, 26, 31, 140], "aggregate_predict": [2, 67, 119], "mse_loss": [2, 31], "adamw": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "train_split": [2, 3, 4, 5, 8, 9, 10, 11, 26, 27, 28, 29, 30, 31, 67, 119], "optimizer__lr": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 67, 119], "optimizer__weight_decai": [2, 3, 4, 8, 27, 28, 29, 31], "iterator_train__shuffl": [2, 5, 9, 10, 11, 27, 31, 67, 119], "lr_schedul": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "cosineannealinglr": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "t_max": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "r2_train": 2, "metric": [2, 5, 9, 10, 11, 27, 28, 32, 134], "r2_score": 2, "lower_is_bett": [2, 5, 8, 9, 10, 11, 125, 126, 127], "on_train": [2, 5, 8, 9, 10, 11, 125, 126], "r2_valid": 2, "verbos": [2, 3, 4, 8, 29, 30, 67, 68, 105, 107, 108, 110, 111, 112, 113, 114, 119, 140], "specifi": [2, 3, 5, 8, 9, 10, 11, 12, 18, 21, 22, 26, 27, 28, 29, 67, 68, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 111, 118, 119], "y": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 20, 22, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 48, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 78, 79, 80, 85, 86, 90, 110, 119, 127], "alreadi": [2, 3, 5, 8, 9, 10, 11, 14, 19, 27, 28, 29, 70, 71, 77, 118, 119, 135, 137], "fit": [2, 3, 5, 8, 9, 10, 11, 14, 24, 26, 27, 28, 29, 30, 31, 32, 67, 113, 119], "train_loss": [2, 3, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32, 67, 119], "valid_loss": [2, 3, 5, 8, 9, 10, 11, 26, 27, 28, 29, 30, 31], "dur": [2, 3, 5, 8, 9, 10, 11, 26, 27, 28, 29, 30, 31], "16": [2, 5, 9, 11, 13, 16, 30, 83, 93, 98, 107], "9036": 2, "3098": 2, "5378": 2, "20": [2, 5, 9, 10, 11, 12, 16, 26, 27, 29, 31, 32, 39, 46, 47, 48, 49, 63, 97, 111], "7346": 2, "0006": [2, 3, 8, 27, 28, 29], "0870": 2, "13": [2, 5, 9, 11, 16, 17, 19, 26, 72, 74, 107, 117], "7536": 2, "7": [2, 3, 4, 5, 9, 10, 11, 12, 16, 17, 18, 19, 20, 21, 26, 27, 28, 29, 30, 31, 32, 34, 72, 83, 90, 91, 97], "1257": 2, "9596": 2, "18": [2, 4, 5, 11, 12, 16, 27, 90], "0738": 2, "5969": 2, "12": [2, 4, 5, 11, 16, 17, 18, 19, 23, 27, 29, 30, 69, 103, 134], "7771": 2, "7413": 2, "6787": 2, "17": [2, 5, 11, 16, 27, 32, 33, 101], "1884": 2, "0005": [2, 3, 22, 28, 31], "5724": 2, "7976": 2, "3917": 2, "5638": 2, "4413": 2, "0004": 2, "6026": [2, 11], "2720": 2, "1845": 2, "4237": 2, "0095": 2, "0002": [2, 3, 28], "6533": [2, 22], "5744": 2, "9208": 2, "3549": 2, "15": [2, 5, 9, 10, 11, 12, 13, 14, 16, 26, 27, 28, 29, 30, 46, 47, 48, 49, 86, 96, 101, 107, 110], "4433": [2, 22], "0001": [2, 30, 94, 116], "5924": 2, "9": [2, 3, 4, 5, 8, 9, 10, 11, 13, 16, 17, 18, 19, 20, 21, 23, 26, 27, 28, 29, 30, 32, 33, 69, 72, 88, 90, 103, 111], "8236": 2, "6185": 2, "3132": 2, "14": [2, 5, 8, 9, 10, 11, 13, 16, 17, 19, 27, 28, 72, 107, 132], "7797": 2, "0000": [2, 3, 8, 27, 28, 29, 30, 31], "6048": 2, "0650": 2, "3051": 2, "3316": 2, "0882": 2, "6093": 2, "def": [2, 3, 5, 8, 9, 10, 11, 12, 14, 16, 29, 31, 32], "pad_and_select_predict": 2, "pred": [2, 8, 32, 124, 128, 129, 131], "pad": [2, 9, 10, 11, 27, 98, 107, 110, 140], "constant": 2, "constant_valu": 2, "mask": [2, 5, 51, 65, 128], "isnan": 2, "squeez": [2, 3, 4, 26, 27, 28, 29, 30, 32], "return": [2, 5, 8, 9, 10, 11, 12, 14, 17, 19, 21, 29, 30, 31, 32, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 64, 65, 66, 67, 70, 71, 75, 76, 77, 78, 79, 80, 81, 85, 86, 91, 97, 98, 99, 102, 103, 104, 105, 106, 107, 108, 110, 111, 112, 113, 115, 116, 117, 118, 119, 120, 121, 127, 129, 130, 131, 134, 140], "t": [2, 4, 5, 11, 17, 19, 26, 27, 28, 29, 30, 31, 32, 41, 59, 67, 68, 69, 84, 95, 96, 103, 105, 115, 116, 119, 132, 134], "preds_train": [2, 8], "y_train": [2, 8, 9, 10, 11, 29], "predict_tri": [2, 67, 119, 140], "return_target": [2, 67, 119, 130], "preds_valid": [2, 8], "y_valid": [2, 8], "preds_test": [2, 8], "y_test": [2, 8, 29], "decreas": [2, 8, 11], "doe": [2, 8, 14, 16, 18, 27, 29, 32, 44, 67, 83, 91, 113, 119, 135], "divers": [2, 4, 8], "caus": [2, 8], "overfit": [2, 8, 9, 10, 11, 29], "better": [2, 5, 8, 10, 14, 16, 27, 28, 29, 32, 86, 127, 140], "improv": [2, 3, 5, 8, 9, 10, 11, 32, 107, 135, 140], "matplotlib": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 31, 134], "pyplot": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 31], "plt": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 31], "panda": [2, 4, 5, 8, 9, 10, 11, 14, 16, 20, 21, 27, 28, 29, 30, 31, 67, 70, 71, 77, 80, 119], "pd": [2, 4, 5, 8, 9, 10, 11, 14, 16, 27, 28, 29, 30, 31, 70, 71, 77, 120, 121, 122, 123], "line": [2, 8, 14, 27, 28, 31, 69, 135], "line2d": [2, 8, 27, 28], "fig": [2, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 30, 31, 134], "ax": [2, 3, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 30, 31, 91], "subplot": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 31], "figsiz": [2, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 31, 134], "set_titl": [2, 8, 16, 31], "arang": [2, 8], "label": [2, 3, 5, 8, 9, 10, 11, 12, 16, 22, 26, 27, 28, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 102, 119, 122, 124, 128, 130, 134], "set_ylabel": [2, 5, 8, 9, 10, 11, 16, 27, 28, 31], "legend": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 31], "set_xlabel": [2, 4, 5, 8, 9, 10, 11, 16, 27, 28, 31], "tight_layout": [2, 4, 5, 8, 9, 10, 11, 27, 28, 30], "correl": [2, 8, 27, 29], "coeffici": [2, 8, 45, 62, 129], "corr_coeff": [2, 8], "dim": [2, 8], "rang": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 26, 27, 28, 29, 31, 32, 41, 59, 68, 117, 134], "append": [2, 8, 12, 14, 16, 27, 28, 31, 67, 107, 119], "corrcoef": [2, 8], "print": [2, 4, 5, 8, 9, 10, 11, 14, 17, 20, 21, 22, 26, 27, 28, 29, 30, 32, 67, 119, 135], "dimens": [2, 5, 8, 51, 65, 83, 86, 99, 103, 110, 140], "round": [2, 8], "histori": [2, 5, 8, 9, 10, 11, 27, 28, 31, 67, 119], "throughout": [2, 8, 9, 10, 11, 28, 29, 32], "accuraci": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 32, 127, 140], "curv": [2, 8, 28], "results_column": [2, 8, 27, 28], "df": [2, 5, 8, 9, 10, 11, 12, 16, 27, 28], "datafram": [2, 4, 5, 8, 9, 10, 11, 14, 16, 20, 21, 22, 27, 28, 29, 30, 67, 70, 119, 120, 121, 122, 123], "index": [2, 5, 8, 9, 10, 11, 17, 27, 28, 30, 31, 71, 105, 115, 116, 120, 121, 131, 137], "ax1": [2, 5, 8, 9, 10, 11, 27, 28], "loc": [2, 8, 12, 26, 27, 28, 29], "style": [2, 5, 8, 27, 28, 47, 48, 49, 101], "marker": [2, 5, 8, 16, 27, 28], "o": [2, 4, 5, 8, 16, 27, 28, 36, 37, 38, 39, 43, 51, 54, 55, 56, 57, 60, 65, 122], "color": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 134], "tab": [2, 5, 8, 16, 27, 28], "blue": [2, 5, 8, 16, 27, 28], "fontsiz": [2, 8, 12, 27, 28], "tick_param": [2, 5, 8, 12, 27, 28], "axi": [2, 3, 5, 8, 27, 28, 31, 46, 47, 48, 49, 50, 52, 63, 64, 66, 91, 110, 131], "labelcolor": [2, 5, 8, 27, 28], "labels": [2, 8, 12, 27, 28], "ax2": [2, 5, 8, 9, 10, 11, 27, 28], "twinx": [2, 5, 8, 27, 28], "instanti": [2, 3, 4, 8, 14, 26, 27, 28, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 60, 67, 73, 119, 140], "share": [2, 8, 14, 27, 28], "red": [2, 8, 27, 28], "r2": [2, 8], "score": [2, 4, 5, 9, 10, 11, 29, 30, 67, 85, 97, 119, 125, 126, 127, 140], "where": [2, 4, 8, 9, 10, 22, 27, 28, 29, 36, 45, 46, 51, 54, 62, 63, 65, 67, 68, 70, 78, 119, 130, 132, 140], "been": [2, 3, 4, 8, 10, 14, 16, 18, 20, 21, 27, 28, 29, 30, 32, 87, 88, 89, 90, 91, 92, 93, 129, 135, 139, 140], "handl": [2, 3, 4, 8, 27, 28, 30, 111], "black": [2, 8, 12, 27, 28, 69, 72, 134], "linewidth": [2, 8, 27, 28], "linestyl": [2, 8, 12, 27, 28], "h": [2, 4, 5, 8, 27, 28, 36, 39, 43, 51, 54, 56, 60, 65, 83, 85, 87, 122], "get_label": [2, 8, 27, 28], "center": [2, 8, 9, 10, 29, 36, 54], "right": [2, 4, 8, 12, 27, 28, 29, 32, 39, 69, 72, 139], "total": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 33, 69], "script": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 132], "minut": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 74], "097": [2, 6], "estim": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32], "usag": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 135, 140], "810": [2, 6], "mb": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 33], "python": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 34, 105, 132, 136, 137, 139, 140], "sourc": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 136, 137], "plot_bcic_iv_4_ecog_crop": [2, 6], "jupyt": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32], "notebook": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32], "ipynb": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32], "galleri": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32], "gener": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 32, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 67, 91, 97, 100, 107, 119, 127, 134, 140], "sphinx": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32], "follow": [3, 4, 5, 9, 10, 11, 14, 26, 29, 32, 88, 89, 107, 110, 113, 119, 137, 138, 139, 140], "wise": [3, 4, 5, 9, 10, 11], "also": [3, 4, 5, 9, 10, 11, 12, 14, 18, 21, 26, 28, 34, 67, 77, 86, 88, 89, 99, 107, 108, 110, 119, 130, 135, 138, 139], "illustr": [3, 29], "effect": [3, 19], "simon": [3, 20, 140], "brandt": [3, 20, 140], "simonbrandt": [3, 20], "protonmail": [3, 20], "c\u00e9dric": [3, 4], "rommel": [3, 4, 140], "cedric": [3, 4, 140], "inria": [3, 4, 11], "fr": [3, 4, 11], "moabbdataset": [3, 4, 18, 20, 21, 27, 28, 29, 30, 32, 140], "dataset_nam": [3, 4, 18, 20, 21, 27, 28, 29, 30, 32, 73], "bnci2014001": [3, 4, 18, 20, 21, 29, 30], "renam": [3, 4, 12, 18, 20, 21, 29, 30, 140], "bnci2014_001": [3, 4, 18, 20, 21, 27, 28, 29, 30, 32], "must": [3, 4, 12, 14, 16, 18, 20, 21, 26, 29, 30, 77, 84, 96, 97, 102, 105, 109, 111, 112, 120, 138, 140], "abbrevi": [3, 4, 18, 20, 21, 29, 30], "its": [3, 4, 9, 10, 16, 18, 20, 21, 26, 29, 30, 31, 67, 70, 109, 119], "bnci2014": [3, 4, 18, 20, 21, 29, 30], "001": [3, 4, 18, 20, 21, 27, 28, 29, 30, 31, 69, 115, 116], "moabb": [3, 4, 15, 18, 21, 23, 24, 27, 28, 29, 30, 32, 69, 70, 72, 73, 109, 118, 138, 139, 140], "is_abbrev": [3, 4, 18, 20, 21, 29, 30], "inform": [3, 4, 12, 14, 17, 18, 20, 26, 29, 30, 41, 59, 67, 70, 77, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 119, 121, 139], "multipli": [3, 4, 5, 9, 10, 12, 27, 28, 29, 30, 32, 83, 88, 89], "cut": [3, 4, 19, 28, 29, 30, 36, 54, 78, 107], "38": [3, 4, 8, 9, 11, 13, 16, 27, 28, 29, 30, 31, 32], "factor": [3, 4, 5, 9, 10, 12, 27, 28, 29, 30, 32, 99, 101, 103, 110], "meg": [3, 4, 20, 27, 28, 29, 30, 32, 34, 107, 108, 136], "stim": [3, 4, 20, 27, 28, 29, 30, 32], "keep": [3, 4, 10, 11, 16, 27, 28, 29, 30, 32, 72, 74, 140], "sensor": [3, 4, 27, 28, 29, 30, 32, 39, 46, 47, 48, 49, 63, 72], "0x7f4b71698940": 3, "create_windows_from_ev": [3, 4, 5, 9, 10, 11, 18, 21, 27, 28, 29, 30, 32, 140], "trial_start_offset_second": [3, 4, 27, 28, 29, 30, 32], "start": [3, 4, 12, 14, 16, 22, 27, 28, 29, 30, 32, 51, 65, 67, 80, 105, 110, 112, 113, 119, 137], "offset": [3, 4, 16, 18, 27, 28, 29, 30, 32, 70, 80, 112, 113], "trial_start_offset_sampl": [3, 4, 5, 9, 10, 11, 18, 19, 21, 27, 28, 29, 30, 32, 80, 113], "int": [3, 4, 5, 9, 10, 14, 16, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 65, 67, 68, 69, 70, 72, 73, 74, 75, 76, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 108, 110, 111, 112, 113, 115, 116, 118, 119, 120, 121, 122, 123, 130, 132, 134], "windows_dataset": [3, 4, 5, 8, 9, 10, 11, 17, 18, 19, 27, 28, 29, 30, 31, 32, 78, 79, 80, 112, 113], "trial_stop_offset_sampl": [3, 4, 5, 9, 10, 11, 18, 19, 21, 27, 28, 29, 30, 31, 32, 80, 113, 140], "0train": [3, 4, 18, 20, 21, 27, 28, 29, 30, 32], "1test": [3, 4, 20, 21, 27, 28, 29, 30, 32], "callabl": [3, 26, 40, 53, 67, 70, 71, 77, 84, 96, 109, 119, 127], "custom": [3, 4, 15, 23, 24, 35, 70, 78], "loader": [3, 4, 5, 14, 32], "call": [3, 16, 26, 27, 29, 32, 67, 70, 77, 80, 83, 86, 90, 105, 109, 112, 113, 119, 125, 126, 127], "demonstr": [3, 4, 7, 22, 24, 26, 32], "below": [3, 5, 34, 36, 135, 138, 140], "illutr": 3, "purpos": [3, 14, 16, 32], "chose": 3, "frequencyshift": 3, "randomli": [3, 5, 27, 36, 37, 38, 43, 51, 55, 57, 60, 123], "translat": 3, "within": [3, 4, 72, 83, 86, 90, 101, 122, 140], "given": [3, 4, 5, 21, 32, 37, 38, 39, 41, 50, 52, 53, 67, 68, 81, 107, 108, 111, 119, 130, 140], "probabl": [3, 4, 26, 30, 32, 36, 37, 38, 39, 41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 67, 83, 84, 87, 96, 100, 101, 119], "actual": [3, 5, 12, 14, 22], "modifi": [3, 5, 10, 12, 41, 59, 67, 91, 105, 106, 108, 109, 117, 119, 132], "max_delta_freq": [3, 42], "shift": [3, 29, 42, 58], "next": [3, 4, 5, 9, 10, 11, 12, 14, 16, 18, 22], "let": [3, 4, 22, 26], "u": [3, 5, 7, 13, 24, 30, 70, 74, 91, 103, 109, 113, 118, 120, 121, 123, 132, 134, 139, 140], "result": [3, 12, 14, 16, 29, 32, 67, 80, 110, 113, 119, 127, 132, 135], "stack": [3, 8], "allow": [3, 5, 14, 26, 29, 30, 32, 40, 67, 80, 88, 89, 113, 119, 140], "fix": [3, 39, 56, 135, 140], "instead": [3, 4, 5, 8, 22, 27, 28, 29, 30, 31, 32, 67, 83, 86, 88, 90, 91, 111, 119, 140], "x_tr": 3, "_": [3, 5, 14, 16, 17, 26, 27, 28, 31, 32, 140], "as_tensor": 3, "float": [3, 5, 26, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 57, 58, 59, 60, 63, 67, 74, 78, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 101, 103, 105, 107, 110, 113, 115, 116, 119, 129, 134], "psd": 3, "plot": [3, 5, 12, 14, 16, 29, 31, 140], "plot_psd": 3, "freq": 3, "time_frequ": 3, "psd_array_multitap": 3, "fmin": 3, "fmax": 3, "100": [3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 20, 26, 27, 28, 29, 30, 31, 32, 36, 51, 69, 84, 103, 110], "log10": 3, "psds_mean": 3, "origin": [3, 11, 17, 19, 26, 29, 45, 46, 47, 48, 49, 51, 62, 63, 65, 70, 80, 86, 87, 88, 89, 90, 92, 93, 113, 117], "k": [3, 5, 9, 10, 11, 26, 27, 28, 30, 31, 32, 36, 43, 46, 47, 48, 49, 51, 54, 60, 63, 65, 84, 90, 95, 96, 134], "r": [3, 5, 9, 10, 11, 26, 27, 28, 29, 30, 31, 36, 43, 51, 54, 60, 65, 84, 88, 89, 92, 93, 95, 96, 134], "titl": [3, 12, 29, 30, 34], "multitap": 3, "gradiomet": 3, "xlabel": [3, 12, 29, 30], "ylabel": [3, 12, 30], "power": [3, 5, 30, 107, 110], "spectral": 3, "densiti": 3, "db": [3, 16, 111], "them": [3, 4, 5, 12, 14, 16, 17, 19, 26, 27, 29, 32, 67, 70, 83, 84, 85, 86, 90, 91, 94, 95, 96, 97, 98, 99, 100, 103, 119, 139], "try": [3, 4, 12, 18, 22, 24, 30, 135, 139], "comput": [3, 4, 5, 9, 10, 11, 18, 22, 34, 47, 48, 49, 67, 69, 80, 83, 86, 88, 89, 90, 92, 93, 97, 111, 113, 115, 116, 119, 124, 125, 126, 128, 132, 135, 139, 140], "list": [3, 5, 11, 14, 16, 21, 22, 26, 27, 28, 29, 31, 32, 34, 35, 39, 40, 47, 48, 49, 56, 67, 68, 69, 70, 72, 73, 74, 75, 76, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 106, 107, 108, 111, 112, 113, 117, 118, 119, 129, 131, 134, 140], "n_channel": [3, 4, 5, 9, 10, 14, 17, 19, 22, 29, 31, 32, 45, 46, 62, 63, 78, 83, 85, 86, 95, 97, 98, 99, 100, 101, 102, 115, 116], "auto": [3, 4, 8, 14, 17, 19, 26, 28, 29, 30, 32, 67, 84, 92, 93, 96, 107, 110, 111, 119, 140], "23": [3, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 30, 31, 32, 106], "depreci": [3, 4, 8, 27, 28, 29, 30, 31, 32], "n_time": [3, 4, 5, 8, 9, 10, 11, 12, 14, 17, 19, 26, 27, 28, 29, 30, 31, 32, 45, 62, 78, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 115, 116, 119, 124, 128], "180": [3, 4, 11, 26, 27, 28, 29, 30, 32], "logsoftmax": [3, 4, 26, 27, 28, 29, 30, 32, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 140], "layer": [3, 4, 5, 9, 10, 11, 26, 27, 28, 29, 30, 31, 32, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 140], "adjust": [3, 4, 26, 27, 28, 29, 30, 32, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103], "accordingli": [3, 4, 9, 26, 27, 28, 29, 30, 32, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 105], "e": [3, 4, 5, 9, 10, 11, 14, 16, 26, 27, 28, 29, 30, 32, 36, 39, 43, 51, 53, 54, 56, 60, 65, 67, 71, 74, 75, 76, 77, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 105, 106, 107, 108, 109, 113, 117, 119, 123, 127, 134, 139, 140], "g": [3, 4, 5, 9, 10, 11, 14, 16, 26, 27, 28, 29, 30, 32, 36, 39, 41, 43, 51, 53, 54, 56, 59, 60, 67, 71, 74, 75, 76, 77, 80, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 100, 101, 102, 103, 105, 106, 107, 108, 109, 113, 117, 119, 123, 127, 134, 140], "crossentropyloss": [3, 4, 9, 10, 11, 26, 27, 28, 29, 30, 32, 67, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 119], "order": [3, 4, 12, 21, 26, 39, 47, 48, 49, 56, 67, 72, 75, 76, 107, 111, 117, 119, 123, 140], "pass": [3, 4, 9, 10, 11, 16, 22, 26, 27, 28, 29, 30, 32, 35, 40, 53, 67, 73, 83, 85, 86, 90, 95, 97, 98, 99, 100, 101, 105, 107, 108, 110, 111, 119, 124, 127, 128, 140], "sequenti": [3, 4, 5, 9, 10, 11, 16, 26, 27, 28, 29, 30, 32, 72, 91], "batch": [3, 4, 5, 26, 30, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 64, 65, 66, 67, 84, 85, 91, 95, 96, 97, 98, 99, 100, 101, 104, 119, 126, 130, 140], "augmenteddataload": [3, 4, 140], "signflip": 3, "freq_shift": 3, "sign_flip": 3, "iter": [3, 4, 5, 20, 22, 45, 67, 91, 106, 119, 130], "argument": [3, 4, 16, 19, 26, 29, 32, 35, 37, 38, 39, 41, 50, 52, 53, 67, 73, 105, 107, 108, 109, 110, 111, 117, 119, 127, 140], "clf": [3, 4, 5, 9, 10, 11, 27, 28, 29, 30], "iterator_train": [3, 4, 67, 119], "tell": [3, 4, 135], "dataload": [3, 4, 5, 14, 32, 35, 67, 119, 130], "iterator_train__transform": [3, 4], "nllloss": [3, 4, 14, 28, 29, 30, 32, 67], "train_accuraci": [3, 27, 28, 29, 30, 32], "valid_acc": [3, 5, 9, 10, 11, 26, 28, 29, 30], "valid_accuraci": [3, 27, 28, 29, 30], "2500": [3, 22, 28, 29, 121], "6077": 3, "0178": 3, "7489": 3, "2569": 3, "3809": 3, "1896": 3, "3996": [3, 22], "3021": 3, "2767": 3, "7959": 3, "3702": 3, "3229": 3, "1763": 3, "2674": [3, 28], "6416": 3, "3995": 3, "classifi": [3, 4, 5, 9, 10, 11, 26, 29, 31, 140], "initi": [3, 5, 9, 10, 11, 26, 29, 30, 32, 67, 86, 88, 89, 103, 119], "module_": [3, 9, 10, 11, 26, 67, 119], "var_nam": [3, 4, 11, 26, 27, 28, 29, 32, 91], "depth": [3, 4, 11, 26, 27, 28, 29, 30, 32, 83, 88, 89, 91, 103], "idx": [3, 4, 9, 10, 11, 26, 27, 28, 29, 30, 32], "param": [3, 4, 5, 11, 26, 27, 28, 29, 30, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 51], "kernel": [3, 4, 11, 26, 27, 28, 29, 30, 32, 46, 47, 48, 49, 63, 83, 89, 90, 97, 98, 100, 103], "22": [3, 4, 5, 9, 11, 16, 17, 19, 27, 28, 29, 32], "1125": [3, 4, 28, 29, 32], "ensure4d": [3, 4, 26, 27, 28, 29, 32], "ensuredim": [3, 4, 26, 27, 28, 29, 32], "rearrang": [3, 4, 26, 27, 28, 29, 32, 140], "dimshuffl": [3, 4, 26, 27, 28, 29, 32], "combinedconv": [3, 4, 26, 27, 28, 29, 32], "conv_time_spat": [3, 4, 26, 27, 28, 29, 32], "40": [3, 4, 11, 14, 16, 26, 27, 28, 29, 31, 32, 86, 96], "1101": [3, 4, 28, 29, 32], "36": [3, 4, 9, 11, 16, 27, 28, 29, 32], "240": [3, 4, 17, 26, 27, 28, 29, 32], "batchnorm2d": [3, 4, 26, 27, 28, 29, 32, 84, 88, 89, 96], "bnorm": [3, 4, 26, 27, 28, 29, 32], "80": [3, 4, 10, 11, 16, 19, 26, 27, 28, 29, 32, 72, 99], "express": [3, 4, 26, 27, 28, 29, 32], "conv_nonlin_exp": [3, 4, 26, 27, 28, 29, 32], "avgpool2d": [3, 4, 26, 27, 28, 29, 32], "pool": [3, 4, 26, 27, 28, 29, 32, 83, 84, 86, 88, 89, 91, 96, 98, 101, 103], "69": [3, 4, 5, 16, 27, 28, 29, 30, 32], "75": [3, 4, 5, 9, 14, 16, 26, 27, 28, 29, 32, 86, 96, 101], "pool_nonlin_exp": [3, 4, 26, 27, 28, 29, 32], "dropout": [3, 4, 5, 9, 10, 26, 27, 28, 29, 30, 32, 83, 84, 86, 87, 88, 89, 96, 97, 98, 99, 100, 101], "drop": [3, 4, 10, 14, 19, 26, 27, 28, 29, 32, 37, 55, 80, 106, 113, 117], "final_lay": [3, 4, 11, 26, 27, 28, 29, 32], "conv2d": [3, 4, 9, 26, 27, 28, 29, 32], "conv_classifi": [3, 4, 26, 27, 28, 29, 32], "044": [3, 4, 28, 29, 32], "47": [3, 4, 5, 9, 10, 11, 16, 28, 29, 32], "364": [3, 4, 28, 29, 32], "trainabl": [3, 4, 11, 26, 27, 28, 29, 32], "non": [3, 4, 11, 16, 22, 26, 27, 28, 29, 30, 32, 67, 72, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 107, 119], "mult": [3, 4, 11, 26, 27, 28, 29, 32], "add": [3, 4, 5, 11, 26, 27, 28, 29, 32, 42, 43, 58, 60, 67, 70, 71, 77, 107, 119, 127, 140], "m": [3, 4, 5, 9, 10, 11, 12, 16, 22, 26, 27, 28, 29, 30, 31, 32, 36, 39, 43, 46, 47, 48, 49, 51, 54, 56, 60, 63, 65, 83, 84, 92, 93, 95, 96, 98, 103, 107, 120, 134, 139], "forward": [3, 4, 5, 11, 26, 27, 28, 29, 32, 40, 53, 67, 83, 85, 86, 90, 95, 97, 98, 99, 100, 101, 102, 103, 107, 109, 111, 119, 124, 128, 130], "backward": [3, 4, 11, 14, 26, 27, 28, 29, 32, 91, 107, 140], "35": [3, 4, 5, 9, 11, 16, 27, 28, 29, 31, 32], "04": [3, 4, 6, 11, 16, 23, 26, 27, 28, 29, 32], "50": [3, 4, 5, 9, 10, 11, 14, 16, 19, 28, 29, 30, 32, 69, 84], "would": [3, 26, 27, 29, 32, 67, 84, 96, 119], "equival": 3, "although": [3, 67, 83, 86, 90, 119], "composit": [3, 40], "composed_transform": 3, "possibl": [3, 4, 11, 12, 16, 18, 26, 67, 69, 112, 119, 132, 135, 140], "most": [3, 9, 10, 11, 14, 122, 135, 138], "windowsdataset": [3, 18, 26, 70, 78, 79, 80, 81, 112, 113, 118, 119, 140], "through": [3, 4, 11, 12, 14, 16, 20, 22, 27, 46, 63, 71, 77, 85, 97, 98, 99, 140], "commonli": 3, "done": [3, 11, 16, 18, 26, 27, 83, 112, 113], "advis": [3, 27, 30, 41, 59, 119], "abov": [3, 14, 16, 22, 27, 29, 135, 137], "compat": [3, 14, 17, 19, 30, 67, 78, 79, 80, 119, 140], "21": [3, 5, 6, 9, 11, 16, 27, 31, 111], "750": [3, 6, 11], "468": [3, 6, 140], "plot_data_augment": [3, 6], "inde": 4, "known": [4, 67], "often": [4, 9, 10, 11, 28, 30], "depend": [4, 5, 9, 10, 11, 12, 14, 16, 26, 29, 30, 32, 34, 67, 72, 99, 119, 130, 137, 139, 140], "task": [4, 9, 10, 11, 26, 30, 41, 59, 69, 71, 122], "phenomenon": 4, "studi": [4, 5, 7, 24], "methodologi": 4, "propos": [4, 37, 38, 41, 51, 55, 57, 59, 65, 90, 140], "openli": [4, 5, 9, 10, 11], "could": [4, 5, 14, 29, 32, 91, 139], "brain": [4, 24, 25, 26, 27, 29, 30, 31, 33, 34, 70, 73, 84, 88, 89, 91, 92, 93, 95, 96, 109, 113, 116, 118, 132, 134, 136], "recent": [4, 26, 135], "shown": [4, 5, 9, 11, 16, 29, 32, 69, 72], "artifici": 4, "cast": [4, 40], "paradigm": [4, 5, 67, 69, 119, 130], "present": [4, 12, 29, 32, 69, 72, 106], "both": [4, 5, 16, 22, 30, 69, 72, 97, 98, 103], "pretext": 4, "approach": [4, 5, 9, 10, 11, 16, 24, 30, 99, 120], "demand": 4, "intens": 4, "comparison": [4, 14, 27, 28], "strength": 4, "context": [4, 5, 29, 34, 99, 122], "bruno": [4, 140], "aristimunha": [4, 140], "ufabc": 4, "br": 4, "bnci": [4, 69], "websit": 4, "There": [4, 24, 26, 84, 96, 137, 139], "subject": [4, 5, 9, 10, 11, 12, 14, 18, 19, 20, 21, 22, 29, 36, 43, 51, 54, 60, 65, 68, 69, 71, 72, 73, 74, 121], "electrod": [4, 20, 69, 72, 111], "while": [4, 5, 14, 29, 32, 72, 83, 86, 90, 97, 131], "do": [4, 12, 14, 26, 27, 29, 32, 67, 78, 79, 80, 103, 112, 113, 119, 123, 132, 139, 140], "imageri": [4, 69, 83, 87, 90, 140], "144": 4, "focu": 4, "relat": [4, 5, 26, 27, 34, 72, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 119, 140], "activ": [4, 19, 26, 67, 72, 83, 84, 88, 89, 90], "0x7f4b714d6410": [4, 21], "out": [4, 8, 9, 10, 26, 36, 51, 54, 65, 67, 69, 119, 120, 128, 135], "provind": 4, "slicedataset": [4, 29, 30], "eval_set": [4, 30], "three": [4, 16, 29, 32, 67, 68, 86, 88, 89, 119, 135], "categor": [4, 120], "aggreg": [4, 86], "sever": [4, 12, 18, 24, 112, 113, 136], "being": [4, 10, 14, 27, 67, 72, 119], "spatial": [4, 26, 41, 59, 84, 96, 103, 140], "paper": [4, 11, 34, 46, 47, 48, 49, 63, 83, 86, 87, 88, 89, 90, 92, 93, 99, 140], "ftsurrog": 4, "smoothtimemask": 4, "channelsdropout": 4, "respect": [4, 5, 30], "two": [4, 5, 9, 10, 11, 12, 14, 16, 18, 27, 29, 32, 45, 51, 62, 69, 72, 74, 90, 97, 107, 110, 111, 122, 123, 129], "insid": [4, 29, 30, 88, 89, 139], "rememb": [4, 29, 32], "\u03c6max": 4, "2\u03c0": 4, "p_drop": [4, 37, 55], "linspac": [4, 12], "transforms_freq": 4, "phase_noise_magnitud": [4, 41, 59], "phase_freq": 4, "random_st": [4, 5, 8, 30, 36, 37, 38, 39, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 120, 121, 122, 123], "transforms_tim": 4, "mask_len_sampl": [4, 51, 65], "transforms_spati": 4, "prob": 4, "gridsearchcv": [4, 29, 30, 127, 140], "control": [4, 5, 10, 29, 67, 97, 105, 107, 108, 110, 111, 112, 113, 118, 119, 140], "over": [4, 10, 16, 29, 31, 32, 41, 46, 47, 48, 49, 59, 63, 67, 119, 140], "framework": 4, "necessari": [4, 67, 111, 119], "slicedata": 4, "mandatori": 4, "eval": [4, 30, 32, 140], "train_x": [4, 30], "train_i": [4, 30], "kfold": [4, 29, 30], "model_select": [4, 5, 8, 29, 30], "cv": [4, 29, 30], "n_split": [4, 29, 30], "shuffl": [4, 8, 14, 29, 30, 32, 38, 45, 57, 67, 119, 140], "fit_param": [4, 30, 119], "param_grid": [4, 29, 30], "return_train_scor": [4, 29, 30], "refit": [4, 29, 30], "error_scor": [4, 29, 30], "rais": [4, 14, 26, 29, 30, 31, 67, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 106, 113, 118, 140], "fold": [4, 30, 32], "candid": [4, 29, 30], "x27": 4, "lt": 4, "gt": 4, "uniniti": [4, 67, 119], "ou": 4, "environ": [4, 68, 132], "rerun": 4, "cell": 4, "represent": [4, 36, 43, 45, 51, 54, 60, 62, 65, 140], "trust": 4, "On": [4, 27, 30, 31, 71, 77], "github": [4, 30, 135, 137, 140], "unabl": 4, "render": 4, "page": [4, 29, 32, 34, 135, 140], "nbviewer": 4, "gridsearchcvgridsearchcv": 4, "analysi": [4, 5, 9, 10, 11, 26, 34, 136], "wa": [4, 5, 9, 10, 11, 27, 28, 29, 32, 67, 69, 72, 86, 99, 119, 120, 140], "search_result": [4, 29, 30], "cv_results_": [4, 29, 30], "best_run": [4, 29, 30], "rank_test_scor": [4, 29, 30], "best_aug": 4, "validation_scor": 4, "around": [4, 10, 32, 46, 47, 48, 49, 63, 113, 120], "mean_test_scor": [4, 30], "training_scor": 4, "mean_train_scor": [4, 30], "report_messag": 4, "gave": [4, 30], "format": [4, 14, 17, 19, 26, 78, 79, 80], "eval_x": [4, 30], "eval_i": [4, 30], "f": [4, 5, 10, 11, 12, 14, 16, 17, 18, 22, 26, 27, 28, 29, 30, 31, 32, 43, 60, 84, 88, 89, 95, 96, 101, 134], "2f": [4, 29, 30, 32], "accuracyof": 4, "78": [4, 5, 16, 74], "28": [4, 5, 11, 16, 27, 88, 89], "00": [4, 6, 10, 13, 16, 23, 26, 27, 32, 33], "bar": 4, "param_iterator_train__transform": 4, "yerr": 4, "std_train_scor": 4, "rot": 4, "45": [4, 11, 16, 29], "c0": 4, "c1": 4, "c2": 4, "strategi": [4, 25, 29, 30], "set_ylim": [4, 27, 28], "32": [4, 5, 9, 10, 11, 13, 16, 26, 27, 30, 83, 92, 101], "c": [4, 5, 9, 10, 11, 20, 27, 28, 29, 30, 41, 59, 85, 90, 92, 93, 103, 120, 135], "paillard": 4, "moreau": [4, 140], "gramfort": [4, 5, 9, 10, 34, 98, 122, 140], "2022": [4, 30, 83, 86, 87, 88, 89], "systemat": 4, "arxiv": [4, 5, 31, 36, 37, 38, 39, 41, 43, 45, 51, 54, 55, 56, 57, 59, 60, 62, 65, 92, 93, 100, 122, 129], "ab": [4, 5, 45, 62, 129], "2206": [4, 31], "14483": 4, "banvil": [4, 5, 9, 14, 16, 20, 122, 140], "chehab": [4, 5, 11, 122, 140], "hyv\u00e4rinen": [4, 5, 122], "engemann": [4, 5, 34, 122, 140], "2021": [4, 10, 11, 88, 89, 90, 99, 103, 120], "uncov": [4, 5, 122], "structur": [4, 5, 16, 17, 19, 121, 122, 140], "clinic": [4, 5, 7, 24, 122], "journal": [4, 28, 29, 30, 34, 90], "engin": [4, 5, 9, 10, 28, 29, 30, 46, 47, 48, 49, 63, 85, 86, 88, 89, 90, 98, 99], "046020": 4, "51": [4, 6, 11, 16, 27], "725": [4, 6], "106": [4, 6], "plot_data_augmentation_search": [4, 6], "access": [5, 9, 10, 11, 12, 14, 26, 87, 121, 137], "physionet": [5, 7, 13, 16, 24, 70, 74, 91, 98, 99, 102, 103, 109, 113, 118, 121, 123, 132, 134, 140], "ssl": [5, 27], "leverag": [5, 99], "unlabel": 5, "design": [5, 16, 99, 107], "prior": [5, 91], "understand": [5, 24, 29], "under": [5, 14, 68, 118, 139, 140], "autocorrel": 5, "requir": [5, 11, 12, 14, 16, 17, 22, 53, 67, 72, 77, 119, 140], "anoth": [5, 21, 29, 32, 122], "interest": [5, 12, 22, 26], "onc": [5, 16, 29, 107, 112, 122, 139], "reus": [5, 9, 11], "featur": [5, 9, 10, 26, 29, 85, 86, 88, 89, 90, 91, 97, 98, 99, 103, 135, 139, 140], "extractor": [5, 9, 10, 85, 97, 98, 99, 103], "weight": [5, 9, 10, 11, 29, 30, 32, 83, 134], "downstream": 5, "help": [5, 9, 10, 21, 111], "reduc": [5, 10, 14, 16, 74, 113], "quantiti": 5, "compar": [5, 14, 16, 22, 27, 29, 32], "strictli": 5, "rp": 5, "simpl": [5, 12, 16, 24, 25, 32, 33, 91, 96], "whether": [5, 14, 26, 37, 38, 39, 41, 46, 47, 48, 49, 50, 52, 53, 59, 63, 67, 70, 77, 78, 79, 80, 81, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 112, 117, 118, 119, 122, 127, 132, 135], "close": [5, 16, 18, 122, 135], "far": [5, 122], "apart": 5, "yield": [5, 14, 20, 69, 101, 135], "physiolog": [5, 9, 10, 11], "relev": [5, 29, 34, 67, 119], "boost": 5, "classif": [5, 9, 10, 11, 26, 27, 30, 36, 41, 43, 51, 54, 59, 60, 65, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101], "regim": 5, "hubert": [5, 9, 14, 16, 20, 140], "jbanvil": [5, 9, 14, 16, 20], "87": [5, 16, 27], "few": [5, 9, 10, 11, 14, 16, 26, 140], "sleep_physionet": [5, 9, 10, 11], "sleepphysionet": [5, 9, 10, 11, 16, 140], "recording_id": [5, 9, 10, 11, 12, 14, 16, 22, 74, 75, 76], "crop_wake_min": [5, 9, 10, 11, 16, 74], "microvolt": [5, 9, 10], "lowpass": [5, 9, 10, 16], "sinc": [5, 9, 10, 11, 12, 22, 26, 30, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 119, 135], "don": [5, 11, 17, 19, 67, 119], "resampl": [5, 12, 14, 18, 20, 74, 107, 140], "0x7f4b71698670": 5, "As": [5, 16, 26, 27, 29, 67, 119], "conveni": [5, 111], "later": [5, 12, 22, 71, 72, 75, 76, 84], "window_size_": [5, 9, 10, 11], "map": [5, 9, 10, 11, 12, 22, 26, 27, 28, 29, 30, 31, 34, 67, 80, 83, 84, 95, 96, 102, 112, 113, 119, 134], "merg": [5, 9, 10, 11, 140], "aasm": [5, 9, 10, 11], "w": [5, 9, 10, 11, 12, 27, 28, 29, 30], "z": [5, 9, 10, 31, 46, 49, 63, 100], "scale": [5, 9, 10, 11, 12, 16, 86, 88, 89, 90, 140], "standard_scal": [5, 9, 10], "channel_wis": [5, 9, 10, 11, 16], "0x7f4b6393bc40": 5, "new": [5, 9, 10, 11, 20, 39, 56, 67, 86, 105, 106, 107, 108, 110, 111, 119, 135, 139], "receiv": [5, 86], "pair": [5, 122], "indic": [5, 9, 10, 21, 31, 45, 62, 70, 107, 108, 111, 121, 122, 123, 140], "when": [5, 9, 10, 11, 14, 16, 22, 27, 29, 30, 32, 34, 40, 41, 46, 47, 48, 49, 53, 59, 63, 67, 68, 73, 78, 79, 80, 83, 86, 103, 106, 107, 108, 111, 112, 113, 118, 119, 132, 135, 140], "train_test_split": [5, 8, 29], "uniqu": [5, 9, 10, 11, 21, 67, 71, 119], "subj_train": 5, "subj_test": 5, "test_siz": [5, 8, 29], "subj_valid": 5, "relativepositioningdataset": 5, "__getitem__": [5, 67, 119], "expect": [5, 14, 26, 32, 67, 119], "__init__": [5, 32], "list_of_d": [5, 70], "super": [5, 32, 125, 126], "return_pair": 5, "ind1": 5, "ind2": 5, "properti": [5, 70, 140], "_return_pair": 5, "setter": 5, "split_id": [5, 9, 10, 11, 12, 70, 140], "dict": [5, 9, 10, 11, 21, 26, 35, 36, 37, 38, 39, 41, 42, 43, 45, 46, 51, 70, 71, 73, 77, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 112, 113, 117, 119, 140], "item": [5, 14, 19, 20, 26, 27, 28, 32], "main": [5, 88, 89, 90], "tau_po": [5, 122], "tau_neg": [5, 122], "neg": [5, 27, 31, 67, 122], "separ": [5, 29, 32, 69, 107, 113, 122], "less": [5, 27, 29, 32], "min": [5, 12, 29, 74, 107], "n_exampl": [5, 122], "regular": [5, 115, 116], "instanc": [5, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 60, 67, 83, 86, 90, 105, 106, 107, 108, 111, 119, 121, 140], "000": [5, 14, 16, 17, 18, 19, 22, 23, 31], "lower": [5, 9, 12, 29, 32, 36, 54, 107, 127], "250": [5, 20, 27, 69, 83, 86, 90], "relativepositioningsampl": 5, "60": [5, 10, 12, 16, 19, 32], "n_examples_train": 5, "len": [5, 8, 9, 10, 11, 12, 14, 17, 20, 22, 29, 32, 72, 117], "n_examples_valid": 5, "n_examples_test": 5, "train_sampl": [5, 9, 10, 11], "get_metadata": [5, 9, 10, 11, 27, 28, 29, 31, 70, 121], "same_rec_neg": [5, 122], "valid_sampl": [5, 9, 10, 11], "presampl": [5, 122], "test_sampl": 5, "introduc": [5, 9, 10, 11, 14, 15, 24, 25, 27, 31], "four": [5, 9, 46, 69, 72], "embedd": 5, "dimension": [5, 67, 86, 119, 130], "last": [5, 22, 27, 31, 32, 51, 65, 72, 74, 78, 79, 80, 83, 86, 107, 110, 112, 113, 140], "embed": [5, 9, 10, 83, 86], "after": [5, 12, 16, 21, 26, 28, 29, 32, 69, 74, 84, 96, 97, 98, 124, 127, 140], "tempor": [5, 9, 10, 14, 26, 83, 84, 86, 87, 89, 96, 97, 98, 99, 100, 101, 103, 140], "wrap": [5, 26, 32, 70], "siames": 5, "contrastivenet": 5, "sleepstagerchambon2018": [5, 9, 26], "input_size_sampl": [5, 9, 10, 11], "emb_siz": 5, "emb": 5, "n_output": [5, 9, 10, 11, 26, 31, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 119], "n_conv_ch": [5, 98], "apply_batch_norm": [5, 97, 98], "linear": [5, 9, 10, 26, 30, 45, 62, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107], "top": [5, 9, 10, 11, 34], "x1": [5, 122], "x2": [5, 122], "z1": 5, "z2": 5, "flatten": [5, 9, 10, 11], "similar": [5, 27, 105], "account": [5, 70, 112], "smaller": [5, 27, 32, 80, 88, 89, 113], "checkpoint": [5, 32], "earlystop": [5, 29, 32], "epochscor": [5, 8, 9, 10, 11, 67, 119], "5e": 5, "128": [5, 10, 11, 67, 72, 88, 89, 98, 103, 119], "512": [5, 11, 31, 33], "enough": [5, 72], "num_work": [5, 14, 32, 130], "cp": 5, "dirnam": 5, "f_criterion": 5, "f_optim": 5, "f_histori": 5, "early_stop": 5, "patienc": 5, "train_acc": 5, "bcewithlogitsloss": [5, 67, 119], "adam": [5, 9, 10, 11, 14, 31], "max_epoch": [5, 29, 32, 67, 119], "iterator_train__sampl": [5, 9, 10, 11], "iterator_valid__sampl": [5, 9, 10, 11], "iterator_train__num_work": 5, "iterator_valid__num_work": 5, "load_param": 5, "lowest": 5, "pt": [5, 83], "delet": [5, 22, 70, 118], "file": [5, 6, 12, 13, 14, 16, 17, 18, 19, 23, 26, 33, 70, 74, 75, 81, 105, 123, 135, 140], "5234": 5, "7013": 5, "6680": 5, "6320": 5, "5210": [5, 30], "5938": 5, "7149": 5, "4880": 5, "8357": 5, "2055": 5, "4922": 5, "0039": 5, "6440": 5, "6172": 5, "1741": [5, 101], "7031": 5, "6120": 5, "5988": 5, "1792": 5, "5391": [5, 27, 28, 29, 30, 31], "6751": 5, "5920": 5, "6208": 5, "1589": 5, "6719": 5, "6235": [5, 9], "5840": 5, "6256": 5, "1662": [5, 34], "6641": 5, "6315": 5, "6200": 5, "6109": 5, "1501": 5, "6562": 5, "6261": 5, "6480": 5, "5934": 5, "1736": 5, "6484": 5, "6720": 5, "5778": 5, "1405": 5, "6161": 5, "6920": 5, "5739": 5, "1579": 5, "6322": 5, "7000": 5, "5788": 5, "1569": 5, "6260": 5, "6840": 5, "5776": 5, "1694": 5, "6328": 5, "6427": 5, "6880": 5, "5794": 5, "1691": 5, "5923": 5, "6800": 5, "5763": 5, "1791": 5, "6193": 5, "6760": 5, "5727": 5, "1568": 5, "7344": 5, "5650": 5, "5677": 5, "1645": 5, "5943": 5, "5627": 5, "1551": 5, "7578": 5, "5444": 5, "6960": 5, "5535": 5, "1598": 5, "19": [5, 9, 10, 11, 16, 27, 28, 33, 105, 111], "7812": 5, "5250": 5, "7120": 5, "5440": 5, "1485": 5, "5657": 5, "7160": 5, "5369": 5, "7422": 5, "5285": 5, "7280": 5, "5309": 5, "1529": 5, "6797": 5, "5494": 5, "7200": [5, 10], "5262": 5, "1672": 5, "6264": 5, "7240": 5, "5229": 5, "1711": 5, "5611": 5, "1790": 5, "5018": 5, "5204": 5, "1591": 5, "balanc": [5, 9, 10, 11, 120, 140], "to_list": [5, 9, 10, 11], "ys1": 5, "ys2": 5, "y1": 5, "y2": 5, "zip": [5, 12, 16, 24], "l": [5, 9, 10, 11, 12, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 83, 84, 95, 96, 103, 120, 134], "orang": [5, 12, 16], "lines1": 5, "labels1": 5, "get_legend_handles_label": 5, "lines2": 5, "labels2": 5, "displai": [5, 9, 10, 11, 27, 28, 29, 32, 72, 132], "confus": [5, 9, 10, 11, 134, 140], "matrix": [5, 9, 10, 11, 38, 39, 46, 56, 57, 63, 86, 134, 140], "report": [5, 9, 10, 11, 14, 29, 32, 75, 76, 83, 135], "confusion_matrix": [5, 9, 10, 11, 27, 28, 134], "classification_report": [5, 9, 10, 11], "switch": [5, 32, 140], "y_pred": [5, 9, 10, 11, 27, 28, 67, 103, 126], "y_true": [5, 9, 10, 11, 27, 28, 67], "89": [5, 10, 16], "42": [5, 6, 11, 16, 27, 30], "precis": [5, 9, 10, 11, 134], "recal": [5, 9, 10, 11], "f1": [5, 9, 10, 11, 83, 93, 127], "support": [5, 9, 10, 11, 18, 27, 32, 67, 107, 110, 111, 117, 119, 140], "68": [5, 16], "74": [5, 16, 27], "71": [5, 16], "121": [5, 12], "73": [5, 16], "67": [5, 16, 27, 32, 103], "70": [5, 16], "129": [5, 11, 13], "macro": [5, 9, 10, 11], "avg": [5, 9, 10, 11], "logist": 5, "balanced_accuracy_scor": [5, 11], "linear_model": 5, "logisticregress": 5, "standardscal": 5, "make_pipelin": 5, "singl": [5, 9, 10, 27, 30, 40, 41, 42, 58, 59, 67, 85, 99, 111, 119, 130, 140], "no_grad": [5, 32], "feat": 5, "batch_x": [5, 22], "concaten": [5, 9, 10, 70, 83, 102, 107, 112, 113], "log_reg": 5, "penalti": 5, "l2": [5, 83], "class_weight": [5, 9, 10, 11], "solver": 5, "lbfg": 5, "multi_class": 5, "multinomi": 5, "clf_pipe": 5, "train_y_pr": 5, "valid_y_pr": 5, "test_y_pr": 5, "train_bal_acc": [5, 9, 10, 11], "valid_bal_acc": [5, 9, 10, 11], "test_bal_acc": 5, "bal": 5, "acc": [5, 29, 32], "4f": 5, "_logist": 5, "460": [5, 33, 140], "convergencewarn": 5, "fail": [5, 12], "converg": [5, 29, 31], "statu": 5, "stop": [5, 32, 36, 54, 80, 107, 112, 113, 131, 140], "NO": 5, "reach": [5, 9, 10, 32], "max_it": 5, "scikit": [5, 24, 25, 33, 67, 70, 73, 91, 96, 109, 113, 116, 118, 119, 132, 134, 140], "document": [5, 10, 12, 34, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 105, 107, 108, 110, 111, 135, 139, 140], "altern": [5, 26, 32, 67, 119], "option": [5, 10, 18, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 67, 70, 73, 80, 83, 89, 90, 91, 107, 110, 113, 119, 130, 134, 139, 140], "n_iter_i": 5, "_check_optimize_result": 5, "8877": 5, "5425": 5, "6449": 5, "110": [5, 11, 13], "52": [5, 11, 16, 26], "416": 5, "63": [5, 16], "53": [5, 16, 22], "91": [5, 11, 16], "77": [5, 11, 16], "76": [5, 16, 27], "142": [5, 140], "109": 5, "83": [5, 11, 16, 22, 27], "562": [5, 21, 23], "84": [5, 11, 16], "62": [5, 14, 16, 26, 27], "105": 5, "54": [5, 16], "170": [5, 140], "1088": [5, 101], "66": [5, 16, 27], "much": [5, 27, 67, 110, 119], "chanc": [5, 9, 10], "level": [5, 9, 10, 22, 68, 105, 107, 108, 110, 111, 140], "problem": [5, 26, 41, 59, 135, 138], "quick": [5, 121], "2d": [5, 134], "space": [5, 16], "pca": 5, "decomposit": 5, "cm": [5, 69, 134], "n_compon": 5, "tsne": 5, "compon": [5, 9, 10, 11, 72, 88, 89], "fit_transform": 5, "get_cmap": 5, "viridi": 5, "enumer": [5, 12, 29, 32], "n1": [5, 9, 10, 11], "n2": [5, 9, 10, 11], "n3": [5, 9, 10, 11], "scatter": [5, 16, 31], "alpha": [5, 9, 10, 11, 12, 45, 83, 88, 89], "advanced_train": 5, "plot_relative_posit": [5, 6], "472": [5, 140], "matplotlibdeprecationwarn": 5, "minor": 5, "releas": [5, 88, 135, 139], "colormap": [5, 134], "obj": 5, "0x7f4b815150f0": 5, "nonlinear": [5, 29, 67, 83, 94, 119], "project": [5, 12, 14, 19, 26, 75, 76, 111], "umap": 5, "might": [5, 14, 16, 26, 29, 30, 32, 113, 121], "insight": 5, "explor": [5, 29], "ag": [5, 12, 18, 22, 69, 72, 75, 76], "sex": 5, "specif": [5, 9, 10, 11, 16, 18, 30, 67, 81, 97, 105, 119, 121, 137], "subset": [5, 8, 20, 29, 31, 70, 107, 108, 140], "achiev": [5, 9, 10, 11], "reason": [5, 10, 29, 32, 67, 119, 127], "avenu": 5, "entir": [5, 14, 20, 29, 32, 140], "describ": [5, 11, 26, 27, 28, 29, 32, 72, 84, 85, 88, 89, 90, 91, 96, 97, 98, 99, 103], "discov": 5, "2020": [5, 36, 37, 38, 43, 51, 54, 55, 57, 60, 65, 88, 89, 97, 101, 122], "preprint": [5, 31, 36, 37, 38, 39, 41, 43, 51, 54, 55, 56, 57, 59, 60, 65, 92, 93, 100, 122], "2007": [5, 36, 43, 51, 54, 60, 65, 122], "16104": [5, 122], "kemp": [5, 9, 10, 11], "b": [5, 9, 10, 11, 16, 27, 39, 56, 86, 92, 93, 103], "zwinderman": [5, 9, 10, 11], "tuk": [5, 9, 10, 11], "kamphuisen": [5, 9, 10, 11], "obery": 5, "2000": [5, 9, 10, 11, 22, 26, 30, 121], "neuron": [5, 9, 10, 11], "feedback": [5, 9, 10, 11, 69], "loop": [5, 9, 10, 11, 14, 67, 119], "slow": [5, 9, 10, 11, 16, 132, 140], "wave": [5, 9, 10, 11], "microcontinu": [5, 9, 10, 11], "ieee": [5, 9, 10, 11, 46, 47, 48, 49, 63, 83, 85, 86, 87, 88, 89, 98, 99], "transact": [5, 10, 83, 85, 86, 88, 89, 98, 99], "biomed": 5, "1185": [5, 9, 10, 11, 22], "1194": [5, 9, 10, 11], "goldberg": [5, 9, 10, 11], "amar": [5, 9, 10, 11], "glass": [5, 9, 10, 11], "hausdorff": [5, 9, 10, 11], "ivanov": [5, 9, 10, 11], "p": [5, 9, 10, 27, 28, 29, 30, 31, 36, 43, 51, 54, 60, 65, 92, 93, 98], "mark": [5, 9, 10, 11], "stanlei": [5, 9, 10, 11], "physiobank": [5, 9, 10, 11], "physiotoolkit": [5, 9, 10, 11], "research": [5, 9, 10, 11, 30, 34, 136], "resourc": [5, 7, 9, 10, 11, 13, 16, 24, 70, 75, 109, 112, 118, 140], "complex": [5, 9, 10, 11, 29, 32, 72, 97], "circul": [5, 9, 10, 11], "101": [5, 9, 10, 11, 12], "e215": [5, 9, 10, 11], "e220": [5, 9, 10, 11], "chambon": [5, 9, 10, 98], "galtier": [5, 9, 10, 98], "arnal": [5, 9, 10, 98], "wainrib": [5, 9, 10, 98], "2018": [5, 9, 10, 28, 29, 30, 39, 41, 43, 45, 56, 59, 60, 62, 93, 98, 100], "multivari": [5, 9, 10, 98], "multimod": [5, 9, 10, 98], "tran": [5, 9, 10], "system": [5, 9, 10, 46, 63, 85, 86, 88, 89, 98, 99, 138], "rehabilit": [5, 9, 10, 85, 86, 88, 89, 98, 99], "26": [5, 9, 10, 11, 16, 20, 27, 98], "758": [5, 9, 10, 98], "769": [5, 9, 10, 98], "33": [5, 6, 9, 11, 16], "898": [5, 6, 11], "228": [5, 6, 11], "470": [6, 140], "execut": [6, 11, 12, 13, 14, 16, 17, 19, 23, 33, 72, 118], "auto_examples_advanced_train": 6, "analaysi": [7, 24], "sleep": [7, 13, 16, 24, 30, 41, 59, 70, 74, 85, 91, 97, 98, 99, 102, 103, 109, 113, 118, 120, 121, 123, 132, 134, 140], "cognit": [7, 24], "experi": [7, 14, 24, 29, 32, 68, 72], "stage": [7, 13, 24, 29, 30, 32, 70, 74, 85, 91, 97, 98, 99, 102, 103, 109, 113, 118, 120, 121, 123, 132, 134, 140], "chambon2018": [7, 13, 24, 70, 74, 91, 98, 102, 109, 113, 118, 121, 123, 132, 134], "eldele2021": [7, 13, 24, 70, 74, 91, 99, 102, 109, 113, 118, 121, 123, 132, 134], "big": [7, 13, 24, 70, 75, 109, 112, 118, 140], "tuh": [7, 13, 14, 15, 23, 24, 70, 76, 109, 112, 118, 140], "corpu": [7, 13, 14, 15, 23, 24, 70, 75, 76, 109, 112, 118, 140], "bcicomp": 8, "0x7f4b83924dc0": 8, "decid": [8, 28, 37, 38, 39, 41, 50, 52, 53], "about": [8, 9, 10, 12, 26, 30, 71, 77, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 132, 135], "length": [8, 9, 11, 12, 14, 16, 26, 27, 30, 45, 62, 70, 80, 83, 84, 85, 86, 87, 88, 89, 91, 92, 93, 94, 96, 97, 98, 99, 100, 101, 107, 112, 113, 140], "preced": 8, "create_windows_from_target_channel": [8, 140], "cnosid": 8, "finer": [8, 140], "fexion": 8, "idx_train": 8, "idx_valid": 8, "n_out_chan": 8, "long": [8, 14, 29, 30, 72, 85], "respons": [8, 9, 10, 11, 28, 30], "manag": [8, 9, 10, 11, 28, 30, 31], "inherit": [8, 9, 10, 11, 26, 28, 30, 67, 119], "neuralnetregressor": 8, "logic": [8, 9, 10, 11, 28, 30, 32], "pearson": 8, "pearson_r_scor": 8, "net": [8, 26, 67, 99, 103, 119, 125, 126, 127], "mseloss": [8, 119], "valid_pearson_r": 8, "train_pearson_r": 8, "train_r2": 8, "valid_r2": 8, "5083": 8, "1251": [8, 22], "5570": 8, "7348": 8, "1511": 8, "6144": 8, "3855": 8, "7986": 8, "3712": 8, "3153": 8, "2587": 8, "3973": 8, "1306": 8, "083": [8, 13], "214": [8, 11, 13], "plot_bcic_iv_4_ecog_tri": [8, 13], "test": [9, 10, 11, 16, 21, 24, 25, 27, 28, 30, 33, 67, 70, 72, 73, 91, 96, 109, 113, 116, 118, 119, 132, 140], "adapt": [9, 11, 16, 87, 88, 89, 99, 100, 101], "distribut": [9, 10, 29, 45, 137], "individu": [9, 10, 11, 12, 26, 27, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 119, 140], "integr": [9, 10, 32], "omit": [9, 36], "downsampl": [9, 10, 110], "apply_on_arrai": [9, 10, 12, 109], "0x7f4b834ab8e0": 9, "0x7f4b836e9cc0": 9, "take": [9, 10, 11, 16, 17, 29, 31, 53, 81, 83, 86, 90, 99], "everi": [9, 10, 11, 12, 14, 18, 22, 29, 32, 72, 83, 86, 90], "consecut": [9, 10, 11, 51, 65, 102, 113, 120, 123], "simplifi": [9, 10, 121, 140], "rather": [9, 10], "freez": [9, 10, 140], "sequencesampl": [9, 10, 11, 140], "n_window": [9, 10, 11, 22, 83, 120, 123], "n_windows_strid": [9, 10, 11, 123], "maxim": [9, 10, 30, 36], "overlap": [9, 10, 11, 78, 79, 80, 107, 112, 113], "372": 9, "383": 9, "implement": [9, 10, 14, 16, 26, 29, 45, 53, 62, 67, 83, 87, 88, 89, 90, 92, 93, 119, 129, 130, 136, 140], "get_center_label": [9, 10], "isinst": [9, 10], "ceil": [9, 10, 101], "astyp": [9, 10], "appear": [9, 10, 11, 69], "lot": [9, 10, 11, 67, 119], "night": [9, 10, 11], "spent": [9, 10, 11], "imbalanc": [9, 10, 11], "avoid": [9, 10, 11, 12, 14, 16, 22, 27, 29, 74, 140], "frequent": [9, 10, 11], "compute_class_weight": [9, 10, 11], "vector": [9, 10, 107, 110], "timedistribut": [9, 10, 140], "31": [9, 10, 11, 16, 26, 27, 29, 86], "feat_extractor": [9, 10], "return_feat": [9, 10, 85, 97, 98, 99], "start_dim": [9, 10], "len_last_lay": [9, 10], "neuralnetclassifi": [9, 10, 11, 28, 30], "mass": 9, "ss3": 9, "speak": [9, 11, 14], "recommend": [9, 11, 16, 29, 30, 34, 86, 138, 139], "balanced_accuraci": [9, 10], "criterion__weight": [9, 10, 11], "tensor": [9, 10, 11, 22, 26, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 85, 86, 90, 95, 97, 98, 99, 100, 101, 102, 119, 124, 128, 129], "2136": 9, "5768": 9, "0888": 9, "6372": 9, "0938": 9, "2036": 9, "4788": 9, "6676": 9, "9176": 9, "2324": 9, "4033": 9, "0966": 9, "2102": 9, "6337": 9, "9441": 9, "2888": 9, "3407": 9, "1149": 9, "2465": 9, "6790": 9, "8773": 9, "3993": 9, "2126": 9, "4517": 9, "4013": 9, "4104": 9, "5294": 9, "0967": 9, "2768": 9, "4076": 9, "6179": 9, "8842": 9, "5755": 9, "9662": 9, "5927": 9, "5671": [9, 22], "3686": 9, "9107": 9, "6251": 9, "8905": 9, "7076": 9, "5786": 9, "2948": 9, "9392": 9, "6877": 9, "8148": 9, "7154": 9, "5876": 9, "3442": 9, "9546": 9, "6995": 9, "7434": 9, "5274": 9, "5296": 9, "6187": 9, "9716": 9, "spatial_conv": 9, "kernel_s": [9, 10, 91, 100, 140], "feature_extractor": [9, 10], "ident": [9, 11, 32, 44, 67, 84, 119], "relu": [9, 10, 90], "maxpool2d": 9, "dilat": [9, 10, 11, 27, 91], "ceil_mod": [9, 10], "end_dim": [9, 10], "inplac": [9, 10, 16], "in_featur": [9, 10], "816": 9, "out_featur": [9, 10], "bia": [9, 10, 11], "sharex": [9, 10, 11], "plot_confusion_matrix": [9, 10, 11, 27, 28, 140], "confusion_mat": [9, 10, 11, 27, 28, 134], "class_nam": [9, 10, 11, 27, 28, 134], "wake": [9, 10, 11, 74], "rem": [9, 10, 11], "61": [9, 16, 26, 27], "57": [9, 14, 16, 26], "43": [9, 10, 11, 16, 23, 29], "194": 9, "03": [9, 10, 11, 13, 16, 27, 33], "29": [9, 10, 11, 16, 27, 31, 99], "hypnogram": [9, 10, 11], "overlaid": [9, 10, 11], "correctli": [9, 10, 11, 91, 139, 140], "identifi": [9, 10, 11, 80, 113], "amount": [9, 10, 11, 16, 110], "expert": [9, 10, 11], "annot": [9, 10, 11, 18, 19, 21, 27, 28, 29, 30, 32, 107], "text": [9, 10, 11, 29, 134], "150": [9, 10, 11, 72], "22222222222223": [9, 10, 11], "despit": [9, 10, 11], "held": [9, 10], "includ": [9, 11, 12, 14, 28, 29, 30, 32, 38, 57, 73, 105, 107, 108, 112, 113, 135, 136], "especi": [9, 30, 32], "ah": [9, 10, 11], "hac": [9, 10, 11], "jjl": [9, 10, 11], "obery\u00e9": [9, 10, 11], "bme": [9, 10, 11], "al": [9, 10, 11, 26, 72, 84, 85, 87, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 127], "lan": [9, 10, 11], "jm": [9, 10, 11], "pch": [9, 10, 11], "rg": [9, 10, 11], "mietu": [9, 10, 11], "je": [9, 10, 11], "moodi": [9, 10, 11], "gb": [9, 10, 11], "peng": [9, 10, 11, 43, 60], "he": [9, 10, 11], "335": [9, 13], "plot_sleep_staging_chambon2018": [9, 13], "attent": [10, 83, 86, 99], "divyesh": [10, 140], "narayanan": [10, 140], "400": [10, 11, 140], "speed": [10, 11, 16, 140], "0x7f4b61778850": 10, "fpz": 10, "cz": [10, 12, 26, 111, 117], "give": [10, 12, 22, 26, 46, 63, 107, 135], "pz": [10, 12], "oz": 10, "130": [10, 19], "reject": [10, 19, 112, 113, 114], "flat": [10, 19, 37, 55, 112, 113, 114], "bad": [10, 14, 19, 107, 108, 111, 135], "slower": [10, 14, 19], "futur": [10, 19, 26, 30, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103], "0x7f4b83820b80": [10, 28], "133": [10, 11], "sleepstagereldele2021": [10, 26, 140], "1471": 10, "1814": 10, "3459": 10, "1795": 10, "4752": 10, "3149": 10, "2712": 10, "8820": 10, "1955": 10, "2186": 10, "1581": 10, "8598": [10, 31], "4518": 10, "4974": 10, "2256": 10, "2200": 10, "2246": 10, "8489": 10, "_mrcnn": 10, "gelu": 10, "approxim": [10, 47, 48, 49], "features1": 10, "conv1d": [10, 11, 103], "batchnorm1d": [10, 11], "ep": [10, 116], "05": [10, 11, 12, 16, 27, 33, 101], "momentum": [10, 26, 84, 88, 89, 96], "affin": 10, "track_running_stat": 10, "maxpool1d": [10, 11], "features2": 10, "afr": [10, 99], "_sebasicblock": 10, "conv1": 10, "bn1": 10, "conv2": 10, "bn2": 10, "se": 10, "_selay": 10, "avg_pool": 10, "adaptiveavgpool1d": [10, 101], "output_s": [10, 91, 102], "fc": [10, 99], "sigmoid": [10, 67, 119], "_tce": 10, "modulelist": 10, "_encoderlay": 10, "self_attn": 10, "_multiheadedattent": 10, "conv": [10, 11, 103], "_causalconv1d": 10, "feed_forward": 10, "_positionwisefeedforward": 10, "w_1": 10, "120": [10, 72, 99], "w_2": 10, "sublayer_output": 10, "_sublayeroutput": 10, "norm": [10, 83], "layernorm": 10, "06": [10, 11, 16, 23], "elementwise_affin": 10, "n4": 10, "_classif": 10, "undefinedmetricwarn": 10, "ill": 10, "zero_divis": 10, "behavior": [10, 30, 32, 67, 119, 140], "_warn_prf": 10, "averag": [10, 12, 27, 29, 31, 32, 67, 83, 91, 111, 119, 124], "msg_start": 10, "02": [10, 11, 13, 16, 23, 26, 27, 32, 33], "48": [10, 11, 16, 18, 20, 27, 29, 33, 69, 90], "faster": [10, 16, 27, 67, 110, 119], "eldel": [10, 99], "et": [10, 26, 72, 84, 85, 87, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 127], "With": [10, 99], "vol": [10, 99], "pp": [10, 36, 43, 46, 47, 48, 49, 51, 54, 60, 63, 65, 86, 99], "809": [10, 99], "818": [10, 99], "1109": [10, 83, 87, 88, 89, 99], "tnsre": [10, 88, 89, 99], "3076234": [10, 99], "708": [10, 13, 16, 18], "plot_sleep_staging_eldele2021": [10, 13], "look": [11, 12, 17, 22, 26, 29, 68, 121], "simpler": 11, "current": [11, 67, 111, 119, 135], "seq2seq": 11, "written": [11, 118, 137], "veri": [11, 29, 32, 70, 113], "short": [11, 12, 29, 32, 69, 85], "too": 11, "small": [11, 12, 27, 29, 135], "theo": [11, 140], "gnassoun": [11, 140], "omar": [11, 140], "emir": 11, "zero": [11, 16, 51, 65, 107, 110, 113, 116], "median": 11, "unit": [11, 26, 107, 139], "interquartil": 11, "upsampl": [11, 103, 110], "light": [11, 134], "No": [11, 19, 26, 29, 32, 69], "robust_scal": 11, "0x7f4b837f3fa0": 11, "shorter": [11, 140], "fulli": [11, 29, 30, 83, 86, 88, 89, 90], "usleep": [11, 26, 140], "in_chan": [11, 26, 31, 84, 92, 93, 94, 95, 96, 101, 103, 104], "with_skip_connect": [11, 103], "balanced_accuracy_multi": 11, "deactiv": 11, "set_param": [11, 67, 119], "callbacks__valid_acc": 11, "306": 11, "even": [11, 26, 29, 32, 67, 68, 103, 119], "odd": [11, 90, 103], "trigger": 11, "intern": [11, 14, 16, 20, 21, 43, 45, 46, 47, 48, 49, 60, 62, 63, 109], "aten": 11, "src": 11, "nativ": 11, "cpp": 11, "1008": 11, "2040": 11, "6129": 11, "1707": 11, "5807": 11, "2757": 11, "2224": 11, "5430": 11, "1594": 11, "5866": 11, "6061": 11, "3464": 11, "4928": 11, "1853": 11, "6227": 11, "3000": [11, 22, 31], "encod": [11, 99, 103], "_encoderblock": 11, "1500": [11, 101, 121], "block_prepool": 11, "102": 11, "maxpool": [11, 103], "405": 11, "375": 11, "726": 11, "188": 11, "constantpad1d": 11, "377": 11, "94": [11, 16, 27, 29], "160": [11, 72], "004": 11, "960": 11, "49": [11, 16], "565": [11, 23], "876": 11, "108": 11, "58": [11, 16], "536": [11, 29], "152": [11, 140], "115": 11, "368": 11, "338": 11, "bottom": 11, "302": 11, "452": 11, "698": 11, "elu": [11, 83, 84, 88, 89, 94], "604": 11, "_decoderblock": 11, "block_preskip": 11, "block_postskip": 11, "428": [11, 140], "641": 11, "786": 11, "65": [11, 16], "304": [11, 140], "323": 11, "912": 11, "156": [11, 16, 23], "216": 11, "163": 11, "620": 11, "34": [11, 16, 30], "863": 11, "154": 11, "237": 11, "635": 11, "37": [11, 16, 22, 26, 27], "515": [11, 140], "520": [11, 140], "39": [11, 16, 22], "324": 11, "41": [11, 16, 27], "56": [11, 16], "060": 11, "660": 11, "44": [11, 16, 27, 30, 32, 33, 72], "376": 11, "645": 11, "195": 11, "46": [11, 16, 26, 33], "363": 11, "727": 11, "225": 11, "161": [11, 140], "126": 11, "522": 11, "tanh": 11, "avgpool1d": 11, "482": 11, "011": 11, "93": [11, 16, 43, 60], "197": [11, 140], "399": 11, "perslev": [11, 103, 120], "darkner": [11, 103, 120], "kempfner": [11, 103, 120], "nikol": [11, 103, 120], "jennum": [11, 103, 120], "pj": [11, 103, 120], "igel": [11, 103, 120], "resili": [11, 103, 120], "npj": [11, 103, 120], "digit": [11, 22, 103, 120], "med": [11, 103, 120], "72": [11, 16, 30, 103, 120], "111": 11, "plot_sleep_staging_usleep": [11, 13], "showcas": [12, 29, 32], "templ": [12, 75, 76, 140], "univers": [12, 72, 75, 76, 140], "hospit": [12, 75, 76, 140], "www": [12, 14, 34, 68, 75, 76], "isip": [12, 14, 75, 76], "piconepress": [12, 14, 75, 76], "tuh_eeg": [12, 14, 22, 75, 76], "shtml": [12, 75, 76], "c_tueg": [12, 75], "luka": [12, 17, 18, 19, 20, 21, 22, 31, 34, 140], "gemein": [12, 17, 18, 19, 20, 21, 22, 31, 140], "tempfil": [12, 16, 18], "error": [12, 22, 27, 30, 31, 80, 106, 112, 113, 114, 119, 135, 140], "messag": [12, 14, 22, 135], "creation": [12, 22], "mock": [12, 22], "want": [12, 14, 18, 21, 22, 24, 28, 29, 30, 32, 67, 119, 136, 139], "disconsid": 12, "section": [12, 22, 72, 138], "_tuhmock": [12, 22], "noqa": [12, 22], "f811": [12, 22], "firstli": [12, 21], "complet": [12, 14, 16, 27, 67, 119], "read": [12, 14, 16, 17, 18, 19, 75, 76, 81, 113], "tuh_path": [12, 14, 22], "pars": 12, "path": [12, 14, 16, 17, 18, 19, 22, 32, 68, 70, 75, 76, 81, 82], "patient": [12, 68], "id": [12, 18, 20, 29, 70, 75, 76, 81, 112, 113, 140], "sort": [12, 27, 28, 140], "chronolog": [12, 75, 76], "year": [12, 34], "month": [12, 34], "dai": [12, 69], "segment": [12, 16, 29, 32, 86, 107], "regard": 12, "gender": [12, 18, 22, 75, 76], "insert": [12, 22, 91], "job": [12, 67, 75, 81, 107, 110, 112, 113, 118, 119], "load": [12, 16, 17, 19, 22, 23, 68, 70, 73, 74, 76, 81, 84, 96, 109, 112, 113, 118, 140], "target_nam": [12, 14, 18, 22, 31, 70, 71, 75, 76, 81, 140], "add_physician_report": [12, 22, 75, 76], "__name__": 12, "statist": 12, "plt_histogram": 12, "df_of_ages_gend": 12, "ylim": 12, "show_titl": 12, "dafaram": 12, "male_df": 12, "female_df": 12, "figur": [12, 27, 28, 29, 69, 83, 134], "suptitl": 12, "95": [12, 16, 67, 119], "male": 12, "hist": 12, "bin": 12, "green": 12, "orient": 12, "horizont": 12, "axhlin": 12, "1f": [12, 32], "std": [12, 29, 43, 60, 72], "barh": [12, 29], "height": [12, 29], "width": [12, 30, 101, 107], "xlim": 12, "upper": [12, 16, 107], "left": [12, 27, 28, 29, 39, 67, 69, 72, 119], "ytick": 12, "gca": 12, "invert_xaxi": 12, "femal": [12, 72], "122": 12, "subplots_adjust": 12, "wspace": 12, "hspace": 12, "count": [12, 67, 119], "labelpad": 12, "durat": [12, 29, 30, 31, 105, 107, 113], "least": [12, 107, 121, 122, 131], "five": [12, 68], "select_by_dur": 12, "inf": 12, "determin": [12, 30, 67, 89, 119], "d_i": 12, "ones": [12, 26, 120, 140], "split": [12, 15, 20, 23, 24, 26, 31, 67, 70, 73, 84, 96, 113, 119, 140], "discard": [12, 74], "incomplet": 12, "configur": [12, 16, 27, 29, 32], "subdivis": 12, "le": 12, "repres": [12, 21, 47, 48, 49, 86], "re": [12, 21, 67, 111, 119, 135], "referenc": [12, 111], "short_ch_nam": 12, "a1": 12, "a2": 12, "fp1": 12, "fp2": 12, "f3": 12, "f4": 12, "c3": [12, 26], "c4": [12, 26], "p3": 12, "p4": 12, "o1": [12, 117], "o2": 12, "f7": 12, "f8": 12, "t3": 12, "t4": 12, "t5": 12, "t6": 12, "fz": 12, "subdivid": 12, "refer": [12, 34, 36, 37, 38, 39, 41, 43, 45, 46, 47, 48, 49, 51, 54, 55, 56, 57, 59, 60, 62, 63, 65, 68, 69, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 111, 117, 120, 122, 129, 134], "ar_ch_nam": 12, "ref": 12, "le_ch_nam": 12, "ar_ch_map": 12, "ch_name": [12, 14, 17, 26, 78, 106, 117], "le_ch_map": 12, "ch_map": 12, "select_by_channel": 12, "endswith": 12, "seta": 12, "kei": [12, 21, 26, 27, 28, 70, 71, 77, 112, 113], "recod": 12, "setb": 12, "issubset": 12, "region": [12, 107], "micro": 12, "volt": 12, "clip": 12, "outlier": 12, "800": [12, 18], "common": [12, 14, 111, 138, 140], "custom_rename_channel": 12, "unexpect": [12, 135], "rename_channel": 12, "custom_crop": 12, "include_tmax": [12, 105], "bigger": 12, "set_eeg_refer": [12, 111], "ref_channel": [12, 111], "ch_type": [12, 26, 111], "pick_channel": [12, 106, 109], "a_min": 12, "a_max": 12, "parallel": [12, 14, 15, 23, 24, 70, 74, 75, 81, 88, 89, 90, 107, 109, 110, 112, 113, 118, 140], "addition": [12, 18, 26, 34, 67, 119, 130], "serial": [12, 15, 18, 23, 24, 70, 74, 109, 112, 118, 140], "lazi": [12, 15, 16, 23, 24, 76, 84, 96, 112, 140], "capabl": [12, 16, 29, 32, 67, 119], "automat": [12, 14, 26, 68, 85, 101, 111, 140], "reload": [12, 16, 118], "machin": [12, 14, 16, 29, 32, 34, 36, 39, 43, 51, 54, 56, 60, 65, 67, 119], "build": [12, 27, 32, 137, 139], "core": [12, 16, 32], "out_path": 12, "mkdtemp": [12, 18], "directori": [12, 16, 18, 27, 68, 70, 75, 76, 81, 118, 139], "tuh_preproc": 12, "concat_d": [12, 16, 18, 112, 113, 114, 118], "save_dir": [12, 16, 118], "readi": [12, 16, 17, 18, 19, 31], "model": [12, 14, 21, 33, 34, 43, 60, 67, 70, 71, 73, 109, 112, 113, 116, 118, 119, 124, 125, 126, 127, 128, 129, 130, 132, 133, 136, 140], "train": [12, 14, 20, 21, 33, 67, 70, 72, 73, 77, 91, 96, 109, 113, 116, 118, 119, 132, 140], "disk": [12, 14, 16, 75, 76, 113], "tuh_window": [12, 22], "988": [12, 13], "plot_tuh_eeg_corpu": [12, 13], "242": 13, "auto_examples_applied_exampl": 13, "07": [13, 16, 27, 29], "sake": 14, "etc": [14, 28, 30, 109], "preprocess": [14, 15, 18, 19, 20, 21, 22, 23, 24, 26, 31, 70, 74, 136, 140], "continu": [14, 16, 20, 71, 72, 78, 79, 80, 112, 113, 138, 140], "fast": [14, 16, 32, 132], "expens": [14, 67, 119], "ultim": 14, "becom": [14, 16, 29], "imposs": 14, "tb": 14, "potenti": [14, 16, 32, 138], "issu": [14, 16, 135, 140], "overhead": [14, 113], "accommod": 14, "window": [14, 16, 18, 19, 21, 26, 67, 70, 77, 78, 79, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 107, 110, 112, 113, 119, 120, 121, 122, 123, 130, 131, 140], "overal": 14, "though": [14, 16, 29, 32], "impact": [14, 27, 30], "dispatch": 14, "enabl": [14, 16, 27, 32, 67, 69, 101, 119, 140], "fif": [14, 16, 18, 70, 81, 140], "edf": [14, 16, 17, 19, 22], "itertool": [14, 16], "product": [14, 16], "seaborn": [14, 29, 30], "sn": [14, 29, 30], "tuhabnorm": [14, 18, 140], "deep4net": [14, 26, 31, 140], "affect": [14, 27, 127], "algorithm": [14, 26, 28, 29, 30, 32], "set_num_thread": 14, "thread": 14, "autom": [14, 29], "abnorm": [14, 76], "slide": [14, 31, 83, 112], "bundl": 14, "prepar": [14, 16, 20, 32], "load_example_data": 14, "window_len_": 14, "n_record": [14, 121], "creat": [14, 16, 17, 18, 19, 20, 21, 31, 67, 70, 77, 78, 79, 80, 111, 112, 113, 119, 130, 140], "bool": [14, 26, 41, 45, 46, 47, 48, 49, 59, 63, 67, 68, 70, 71, 74, 75, 76, 77, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 108, 109, 110, 111, 112, 113, 117, 118, 119, 122, 123, 127, 130, 132, 134], "windows_d": [14, 16], "assum": [14, 26, 67, 105, 119, 124, 128, 140], "patholog": [14, 18, 76], "window_len_sampl": 14, "xxx": [14, 94], "itself": [14, 29, 30, 135], "drop_bad": [14, 80, 113], "create_example_model": 14, "kind": [14, 26], "str": [14, 22, 26, 27, 28, 29, 35, 67, 68, 70, 71, 73, 75, 76, 77, 80, 81, 84, 86, 91, 96, 105, 106, 107, 108, 109, 110, 111, 112, 113, 118, 119, 127, 134], "n_filters_tim": [14, 26, 31, 84, 86, 96], "filter_time_length": [14, 26, 84, 86, 96], "n_filters_spat": [14, 26, 31, 84, 96], "pool_time_length": [14, 26, 84, 86, 96], "pool_time_strid": [14, 26, 84, 86, 96], "split_first_lay": [14, 26, 84, 94, 96], "batch_norm": [14, 26, 84, 96], "batch_norm_alpha": [14, 26, 84, 88, 89, 94, 96], "drop_prob": [14, 26, 30, 84, 86, 87, 88, 89, 92, 93, 96, 100, 101], "elif": [14, 31], "n_filters_2": [14, 31, 84], "filter_length_2": [14, 84], "n_filters_3": [14, 31, 84], "filter_length_3": [14, 84], "n_filters_4": [14, 31, 84], "filter_length_4": [14, 84], "first_pool_mod": [14, 84], "max": [14, 16, 26, 29, 84, 92, 96, 98, 101, 103, 107, 116], "later_pool_mod": [14, 84], "double_time_conv": 14, "stride_before_pool": [14, 31, 84], "valueerror": [14, 26, 31, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103], "run_train": 14, "serv": [14, 69, 71, 77], "loss_val": 14, "zero_grad": [14, 32], "256": [14, 26, 140], "minibatch": 14, "pin_memori": 14, "pin": 14, "n_repetit": 14, "repeat": [14, 135], "get": [14, 16, 17, 22, 27, 28, 29, 32, 67, 119], "folder": [14, 32, 68], "storag": 14, "tuh_eeg_abnorm": 14, "v2": 14, "cycl": 14, "combin": [14, 16, 70], "all_result": 14, "win_len_": 14, "model_kind": 14, "repetit": [14, 16, 72], "nrepetit": 14, "n": [14, 16, 22, 26, 27, 28, 29, 30, 32, 36, 37, 38, 43, 45, 51, 54, 55, 57, 60, 62, 65, 83, 92, 93, 98, 129], "data_loading_start": 14, "data_loading_end": 14, "training_setup_start": 14, "worker_init_fn": 14, "training_setup_end": 14, "model_training_start": 14, "trained_model": 14, "model_training_end": 14, "del": 14, "data_prepar": 14, "training_setup": 14, "model_train": 14, "csv": 14, "results_df": 14, "fname": 14, "lazy_vs_eager_loading_result": 14, "to_csv": 14, "summar": 14, "catplot": 14, "row": [14, 22, 39, 70, 91, 134], "hue": 14, "col": 14, "strip": 14, "hardwar": [14, 16], "pretti": [14, 135], "worker": [14, 32, 130, 140], "speedup": 14, "benchmark_lazy_eager_load": [14, 23], "basic": [15, 27, 29, 32, 33, 53, 70, 73, 90, 91, 96, 109, 113, 116, 118, 132, 134, 140], "eager": [15, 23, 24, 76, 84, 96, 112], "discret": [15, 23, 24, 70, 75, 112, 140], "simplest": 16, "scenario": [16, 113], "act": [16, 111], "stai": [16, 27, 69], "aris": 16, "bottleneck": [16, 32, 88, 89, 101], "consider": 16, "solut": [16, 111], "clear": 16, "downsid": 16, "write": [16, 18], "cours": [16, 68], "whenev": 16, "up": [16, 17, 69, 103, 110, 140], "significantli": 16, "joblib": [16, 118], "made": [16, 27, 90, 140], "remain": [16, 29, 32], "tradeoff": 16, "memory_profil": 16, "memory_usag": 16, "goe": 16, "prepare_data": 16, "n_rec": 16, "tmp_dir": 16, "temporarydirectori": 16, "overwrit": [16, 18, 67, 70, 71, 75, 76, 77, 82, 118, 119], "measur": 16, "peak": [16, 112, 113], "character": 16, "n_repet": 16, "all_n_rec": 16, "all_n_job": 16, "mem": 16, "proc": 16, "time_taken": 16, "max_mem": 16, "1m": [16, 27], "81": [16, 19], "9k": 16, "803kb": 16, "183k": 16, "926kb": 16, "295k": 16, "969kb": 16, "410k": 16, "979kb": 16, "508k": 16, "974kb": 16, "606k": 16, "971kb": 16, "721k": 16, "989kb": 16, "836k": 16, "995kb": 16, "950k": 16, "997kb": 16, "06m": 16, "17m": 16, "986kb": 16, "28m": 16, "991kb": 16, "38m": 16, "00mb": 16, "49m": 16, "01mb": 16, "61m": 16, "02mb": 16, "72m": 16, "84m": 16, "95m": 16, "04mb": [16, 27], "03mb": 16, "27m": 16, "37m": 16, "47m": 16, "57m": 16, "972kb": 16, "69m": 16, "985kb": 16, "79m": 16, "987kb": 16, "89m": 16, "988kb": 16, "00m": 16, "11m": 16, "990kb": 16, "23m": 16, "34m": 16, "46m": 16, "90m": 16, "01m": 16, "12m": 16, "993kb": 16, "33m": 16, "982kb": [16, 27], "44m": [16, 27], "55m": 16, "67m": 16, "77m": 16, "87m": 16, "98m": 16, "994kb": 16, "10m": 16, "999kb": 16, "21m": 16, "32m": 16, "78m": 16, "22m": 16, "54m": 16, "65m": 16, "88m": 16, "45m": 16, "68m": 16, "80m": [16, 27], "91m": 16, "03m": 16, "14m": 16, "08": [16, 33], "05mb": 16, "26m": 16, "60m": 16, "07mb": 16, "83m": 16, "06mb": 16, "18m": 16, "09": [16, 27], "29m": 16, "40m": 16, "52m": 16, "63m": [16, 27], "75m": 16, "86m": 16, "2m": [16, 27], "3m": [16, 27], "4m": [16, 27], "6m": [16, 27], "7m": [16, 27], "8m": [16, 27], "9m": [16, 27], "0m": [16, 27], "5m": [16, 27], "08mb": 16, "992kb": 16, "998kb": 16, "981kb": 16, "952kb": 16, "954kb": 16, "965kb": 16, "960kb": 16, "975kb": 16, "978kb": 16, "976kb": 16, "996kb": 16, "59": [16, 29], "984kb": 16, "983kb": 16, "79": 16, "977kb": 16, "82": [16, 43, 60], "85": [16, 27, 28], "88": [16, 27], "90": [16, 27, 29, 32, 134], "92": 16, "96": [16, 27], "97": [16, 27], "98": 16, "99": 16, "130gb": 16, "90k": 16, "4mb": [16, 27], "mne_data": [16, 17, 19, 27, 68], "sc4001e0": 16, "psg": 16, "detect": [16, 17, 19, 30, 72], "sc4011e0": 16, "2507000": 16, "25070": 16, "sec": [16, 17, 18, 19, 31], "contigu": [16, 51, 65], "fir": [16, 107], "phase": [16, 41, 59, 107], "causal": [16, 107], "firwin": [16, 107], "ham": [16, 107], "0194": 16, "passband": 16, "rippl": 16, "stopband": 16, "attenu": [16, 107], "edg": [16, 107], "transit": [16, 36, 54, 107], "bandwidth": [16, 36, 54], "450": 16, "tmp": [16, 18], "tmprkujhpaz": 16, "3260000": 16, "32600": 16, "subdirectori": [16, 18, 70, 118], "open": [16, 18, 135, 136, 138], "isotrak": 16, "2884000": 16, "5391000": 16, "28840": 16, "53910": 16, "1975000": 16, "5235000": 16, "19750": 16, "52350": 16, "700": [16, 18], "match": [16, 18, 19, 26, 30, 70, 83], "exist": [16, 18, 22, 29, 31, 68, 70, 71, 77, 111, 118], "encount": [16, 18, 135], "mix": [16, 18, 45, 62, 129], "i_d": [16, 18], "tmp0g57aua5": 16, "tmpej2cwuxz": 16, "tmpjf9zhor8": 16, "sub_df": 16, "groupbi": 16, "mib": 16, "without": [16, 26, 27, 29, 30, 32, 67, 119, 129, 140], "circl": 16, "advantag": [16, 29, 88, 89], "togeth": [16, 27, 140], "430": [16, 23, 30, 33], "plot_benchmark_preprocess": [16, 23], "create_from_x_i": 17, "fetch": [17, 19, 20, 21, 69, 72, 73], "imagin": [17, 19], "hand": [17, 19, 24, 28, 30, 69, 72], "feet": [17, 18, 19, 21, 27, 28, 29, 30, 32, 69, 72], "event_cod": [17, 19], "yet": [17, 19, 91, 139], "physionet_path": [17, 19], "eegbci": [17, 19], "load_data": [17, 19], "update_path": [17, 19], "io": [17, 19, 27, 71, 105, 107, 117], "read_raw_edf": [17, 19], "stim_channel": [17, 19], "eegmmidb": [17, 19], "s022": [17, 19], "s022r05": [17, 19], "19999": [17, 19], "124": [17, 19, 27], "994": [17, 19], "s022r06": [17, 19], "s022r09": [17, 19], "s022r10": [17, 19], "s022r13": [17, 19], "s022r14": [17, 19], "ani": [17, 18, 26, 27, 29, 32, 67, 99, 107, 111, 119, 139], "get_data": 17, "500": [17, 19, 28, 121, 140], "rawarrai": [17, 19, 31, 80], "float64": [17, 19, 31], "20000": 17, "manipul": 17, "x_i": 17, "y_i": 17, "window_ind": 17, "start_ind": 17, "stop_ind": 17, "871": [17, 23], "plot_custom_dataset_exampl": [17, 23], "load_concat_dataset": [18, 140], "skip": [18, 22, 29, 32, 90, 103], "fn": [18, 109], "event": [18, 19, 20, 26, 29, 30, 74, 80, 112, 113], "0x7f4b813bc280": 18, "concat": [18, 70, 83, 112, 113, 118], "json": [18, 70, 81, 140], "hold": [18, 70, 71, 77, 112, 113], "due": [18, 32, 140], "tmpdir": 18, "temporari": [18, 140], "tmpl8p_rszc": 18, "complianc": 18, "upon": [18, 26], "dataset_load": 18, "ids_to_load": [18, 81], "3868": 18, "386": 18, "left_hand": [18, 21, 27, 28, 29, 30, 32], "right_hand": [18, 21, 27, 28, 29, 30, 32], "tongu": [18, 21, 27, 28, 29, 30, 32, 69], "again": [18, 22, 29], "epo": [18, 70, 81], "windows_dataset_load": 18, "845": [18, 23], "269": [18, 23, 140], "plot_load_save_dataset": [18, 23], "create_from_mne_raw": 19, "create_from_mne_epoch": 19, "t0": 19, "t1": 19, "t2": 19, "point": [19, 20, 26, 69, 111, 115, 116], "beforehand": 19, "list_of_epoch": [19, 79], "baselin": [19, 26], "Not": [19, 26], "metadata": [19, 26, 70, 77, 112, 119, 120, 121, 122, 123], "correct": [19, 26, 32, 67, 87, 88, 89, 90, 92, 93, 119, 140], "ad": [19, 27, 70, 75, 76, 101, 103, 111, 140], "938": [19, 23], "plot_mne_dataset_exampl": [19, 23], "daniel": [20, 34, 140], "wilson": [20, 140], "dan": [20, 140], "wil": 20, "break": [20, 69], "place": [20, 31, 91, 105, 117], "legaci": 20, "inst": [20, 106, 107, 108, 111], "criteria": [20, 67, 119], "subset_nam": 20, "232164": 20, "793": [20, 23], "294": [20, 23, 140], "plot_moabb_dataset_exampl": [20, 23], "aim": [21, 22], "dictionari": [21, 26, 67, 70, 73, 107, 119], "string": [21, 22, 26, 34, 39, 47, 48, 49, 67, 70, 107, 108, 109, 118, 119, 127], "entri": [21, 106], "0x7f4b71546b00": 21, "0x7f4b714d55d0": 21, "0x7f4b714d6380": 21, "0x7f4b714d61d0": 21, "0x7f4b714d75e0": 21, "0x7f4b714d54e0": 21, "integ": [21, 22, 27, 28, 39, 51, 56, 65, 70, 107, 108], "0x7f4b715463b0": 21, "0x7f4b714d5bd0": 21, "0x7f4b714d7880": 21, "0x7f4b714d5c90": 21, "0x7f4b714d5090": 21, "0x7f4b714d4580": 21, "similarli": [21, 32], "0x7f4b8153e050": 21, "0x7f4b8153c730": 21, "0x7f4b8153ef80": 21, "0x7f4b8153c760": 21, "0x7f4b8153f9a0": 21, "0x7f4b8153d270": 21, "0x7f4b8153e3e0": 21, "0x7f4b8153f4f0": 21, "0x7f4b8153f760": 21, "0x7f4b8153efb0": 21, "0x7f4b8153e7a0": 21, "295": [21, 23, 140], "plot_split_dataset": [21, 23], "welcom": 22, "ll": 22, "guid": [22, 29, 138], "log": [22, 26, 27, 32, 67, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 105, 107, 108, 110, 111, 112, 113, 119, 140], "excess": 22, "v1": [22, 32], "02_tcp_le": 22, "00000058": 22, "s001": 22, "01_tcp_ar": 22, "099": 22, "00009932": 22, "s004": 22, "03_tcp_ar_a": 22, "123": 22, "00012331": 22, "s0": 22, "00000000": 22, "149": 22, "00014928": 22, "ndarrai": [22, 46, 63, 67, 110, 115, 116, 119, 123, 130, 131], "92922518": 22, "22477157": 22, "12493701": 22, "28417889": 22, "13578887": 22, "56835277": 22, "25153176": 22, "7638324": 22, "14345092": 22, "30167542": 22, "68056549": 22, "70380673": 22, "70052629": 22, "21543634": 22, "96330007": 22, "02736802": 22, "65902848": 22, "15756383": 22, "38658058": 22, "04194231": 22, "15447331": 22, "set_descript": [22, 32, 70, 71, 77], "ind": 22, "16017832": 22, "11754766": 22, "6515615": 22, "50407195": 22, "7429778": 22, "9292252": 22, "86039335": 22, "5169721": 22, "0308012": 22, "1209397": 22, "5210943": 22, "2247716": 22, "373041": 22, "14827406": 22, "25829056": 22, "1486133": 22, "15352039": 22, "30362263": 22, "939559": 22, "5686462": 22, "5503989": 22, "3299779": 22, "3865806": 22, "7443461": 22, "1792846": 22, "25878426": 22, "5670986": 22, "2997373": 22, "0537782": 22, "4429058": 22, "05458383": 22, "000525": 22, "66521484": 22, "15447332": 22, "dtype": [22, 30, 140], "float32": 22, "2600": 22, "3600": [22, 74], "dl": 22, "batch_i": 22, "batch_ind": 22, "simpli": [22, 26], "8024": 22, "4564": 22, "7404": 22, "2522": 22, "0508": 22, "4418": 22, "5201": 22, "2037": 22, "0273": 22, "0506": 22, "1677": 22, "1145": 22, "7075": 22, "1768": 22, "0260": 22, "7216": 22, "2742": 22, "3986": 22, "3912": 22, "8000": 22, "0593": 22, "8097": 22, "1729": 22, "6267": 22, "8419": 22, "6685": 22, "9266": 22, "1319": 22, "1409": 22, "6246": 22, "6229": 22, "5953": 22, "3169": 22, "4604": 22, "2885": 22, "0168": 22, "6279": 22, "7673": 22, "6671": 22, "0448": 22, "1422": 22, "5395": 22, "4664": 22, "1882": 22, "2031": 22, "6282": 22, "4535": 22, "8585": 22, "2657": 22, "9942": 22, "3878": 22, "1360": 22, "9132": 22, "9481": 22, "5033": 22, "3406": 22, "6089": 22, "9883": 22, "2919": 22, "3796": 22, "8036": 22, "7666": 22, "8174": 22, "3829": 22, "1508": 22, "8516": 22, "0426": 22, "1322": 22, "4122": 22, "2526": 22, "9711": 22, "6890": 22, "4660": 22, "5510": 22, "3613": 22, "0280": 22, "1350": 22, "2249": [22, 29], "9406": 22, "7754": 22, "7664": 22, "1807": 22, "8206": 22, "1281": 22, "1607": 22, "9353": 22, "0165": 22, "6509": 22, "7276": 22, "2137": 22, "5619": 22, "0408": 22, "9825": 22, "3648": 22, "6978": 22, "8943": 22, "2374": 22, "4398": 22, "8218": 22, "5172": 22, "2975": [22, 28], "0311": 22, "1602": 22, "1175": 22, "6516": 22, "5041": 22, "7430": 22, "9292": 22, "8604": 22, "5170": 22, "0308": 22, "1209": 22, "5211": 22, "2248": 22, "3730": 22, "1483": 22, "2583": 22, "1486": 22, "1535": 22, "1249": 22, "3036": 22, "9396": 22, "5686": 22, "5504": 22, "3300": 22, "3866": 22, "7443": 22, "1793": [22, 30], "2588": 22, "2997": 22, "0419": 22, "0538": 22, "4429": 22, "0546": 22, "6652": 22, "1545": 22, "127": [22, 23], "plot_tuh_discrete_multitarget": [22, 23], "auto_examples_datasets_io": 23, "fundament": [24, 25], "tune": [24, 25, 32, 33, 70, 73, 86, 91, 96, 109, 113, 116, 118, 132, 140], "fake": [24, 25, 26, 33, 70, 71, 84, 91, 96, 104, 112, 124, 132, 140], "auto_examples_python": 24, "auto_examples_jupyt": 24, "develop": [26, 29, 32, 135, 139], "particular": 26, "pierr": [26, 140], "guetschel": [26, 140], "suppos": 26, "stumbl": 26, "schirrmeist": [26, 27, 28, 29, 30, 31, 34, 72, 84, 95, 96, 134, 140], "2017": [26, 27, 28, 29, 30, 31, 34, 46, 47, 48, 49, 63, 72, 84, 85, 95, 96, 134], "articl": [26, 34], "mention": [26, 29], "novel": [26, 88, 89], "shallowconvnet": [26, 31], "fortun": 26, "publish": 26, "what": [26, 29, 67, 83, 112, 113, 119], "exact": 26, "visit": [26, 29], "api": [26, 139], "models_dict": [26, 67, 119, 140], "atcnet": [26, 140], "deepsleepnet": [26, 140], "eegconform": [26, 140], "eegitnet": [26, 140], "eegincept": [26, 89, 140], "eeginceptionerp": [26, 88, 140], "eeginceptionmi": [26, 140], "eegnetv1": 26, "eegnetv4": 26, "eegresnet": [26, 140], "hybridnet": 26, "sleepstagerblanco2020": [26, 140], "tcn": [26, 83, 140], "tidnet": [26, 140], "investig": 26, "docstr": [26, 140], "__doc__": 26, "schirrmeister2017": [26, 72, 84, 95, 96], "conv_nonlin": [26, 96], "pool_mod": [26, 92, 93, 96], "pool_nonlin": [26, 96], "normalis": [26, 84, 96], "chs_info": [26, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 119], "fill": [26, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103], "ch": [26, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103], "detail": [26, 29, 32, 45, 62, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 107, 108, 110, 111, 117, 118, 132, 139], "input_window_second": [26, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 119], "alia": [26, 83, 84, 85, 86, 87, 88, 89, 90, 92, 93, 94, 96, 97, 98, 99, 100, 101, 103], "softmax": [26, 27, 31, 67, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 119], "doc": [26, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 132, 139, 140], "infer": [26, 29, 30, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 113, 119, 127], "attempt": [26, 83, 84, 85, 91, 94, 95, 96, 97, 98, 99, 100, 103, 111], "springenberg": [26, 27, 28, 29, 30, 31, 34, 84, 95, 96, 134], "fieder": [26, 27, 28, 29, 30, 31, 34, 84, 95, 96, 134], "glasstett": [26, 27, 28, 29, 30, 31, 34, 84, 95, 96, 134], "eggensperg": [26, 27, 28, 29, 30, 31, 34, 84, 95, 96, 134], "tangermann": [26, 27, 28, 29, 30, 31, 34, 84, 95, 96, 134], "hutter": [26, 27, 28, 29, 30, 34, 84, 95, 96, 134], "ball": [26, 27, 28, 29, 30, 31, 34, 72, 84, 95, 96, 134], "aug": [26, 34, 84, 95, 96, 134], "dx": [26, 34, 84, 88, 89, 95, 96, 134], "1002": [26, 27, 28, 29, 30, 34, 84, 95, 96, 134], "hbm": [26, 27, 28, 29, 30, 34, 84, 95, 96, 134], "23730": [26, 27, 28, 29, 30, 34, 84, 95, 96, 134], "__str__": 26, "976": [26, 27], "882": 26, "202": 26, "quit": [26, 29], "popular": 26, "collect": [26, 67, 72, 119], "1024": 26, "simul": 26, "create_info": 26, "randn": 26, "256hz": 26, "epochsarrai": 26, "randint": [26, 31], "99609": 26, "off": [26, 29, 30, 107], "wrapper": [26, 28, 29], "form": [26, 45, 62, 69, 70, 71, 77], "facilit": [26, 140], "easiest": [26, 29], "former": [26, 67, 83, 86, 90, 119], "prefix": [26, 67, 119], "module__": 26, "validsplit": [26, 30, 67, 119], "module__final_conv_length": 26, "along": [26, 71, 77, 110, 138, 140], "6926": 26, "0767": 26, "0114": 26, "0099": 26, "0100": 26, "0101": 26, "0102": 26, "0104": 26, "840": 26, "924": 26, "844": 26, "pre": [26, 78, 111, 140], "via": [26, 28, 29, 30, 103, 107, 137, 138, 140], "And": [26, 27], "nan": [26, 128], "unit_mul": 26, "fiff_unitm_non": 26, "cal": 26, "fiffv_eeg_ch": 26, "coil_typ": 26, "fiffv_coil_eeg": 26, "107": 26, "fiff_unit_v": 26, "coord_fram": 26, "fiffv_coord_head": 26, "scanno": 26, "logno": 26, "target_from": 26, "miss": [26, 32, 83, 86, 88, 90, 92, 93, 94, 95, 97, 103, 140], "manual": [26, 27, 29, 138], "716": [26, 33], "plot_basic_training_epoch": [26, 33], "push": [27, 67, 119], "produc": [27, 29, 32, 99], "neighbour": 27, "simultan": [27, 88, 89], "sub": [27, 140], "afterward": [27, 29, 83, 86, 90, 111], "implicitli": [27, 29, 32], "timestep": 27, "user": [27, 67, 119, 135, 137, 138, 140], "mostli": 27, "runtim": 27, "rule": [27, 67, 119], "mathemat": 27, "neighbourhood": 27, "At": [27, 69], "redund": 27, "lead": [27, 29, 67, 111, 119], "gradient": [27, 140], "likelihood": [27, 67], "typic": [27, 67, 105, 119], "locat": [27, 68], "anyth": [27, 67], "runtimewarn": 27, "config": [27, 68], "mne_datasets_bnci_path": 27, "set_config": 27, "get_config": 27, "urllib3": 27, "connectionpool": 27, "1061": 27, "insecurerequestwarn": 27, "unverifi": 27, "request": [27, 111, 135], "host": 27, "lampx": 27, "tugraz": 27, "certif": 27, "verif": 27, "readthedoc": 27, "en": 27, "advanc": [27, 137], "19k": 27, "6kb": 27, "8k": 27, "143kb": 27, "3k": 27, "309kb": 27, "209k": 27, "539kb": 27, "432k": 27, "889k": 27, "87mb": 27, "61mb": 27, "62m": 27, "3mb": 27, "7mb": 27, "9mb": 27, "2mb": 27, "5mb": 27, "6mb": 27, "111gb": 27, "3kb": 27, "1k": 27, "280kb": 27, "193k": 27, "499kb": 27, "409k": 27, "943kb": 27, "841k": 27, "80mb": 27, "71m": 27, "49mb": 27, "77mb": 27, "53m": 27, "39m": 27, "1mb": 27, "0mb": 27, "112gb": 27, "0x7f4b834a3730": 27, "definit": [27, 67, 119], "torchinfo": [27, 28, 29, 32, 91, 140], "tabl": [27, 28, 29, 30, 32, 83, 91, 140], "804": 27, "dens": [27, 91, 97, 98], "explicit": [27, 127], "deep4": [27, 28, 140], "nll_loss": 27, "2778": [27, 28], "5658": 27, "2535": [27, 28], "5302": 27, "0047": 27, "3090": 27, "4417": 27, "2604": 27, "4977": 27, "8131": 27, "percent": [27, 28], "misclass": [27, 28], "assign": [27, 28, 131], "train_misclass": [27, 28], "valid_misclass": [27, 28], "misclassif": [27, 28], "get_ylim": [27, 28], "room": [27, 28], "matric": [27, 28, 47, 48, 49, 67, 119], "label_dict": [27, 28], "i_class": [27, 28], "window_kwarg": [27, 28, 70], "kv": [27, 28], "conf": [27, 28], "640x480": [27, 28], "m\u00fcller": [27, 28, 29, 30], "aertsen": [27, 28, 29, 30], "birbaum": [27, 28, 29, 30], "braun": [27, 28, 29, 30], "brunner": [27, 28, 29, 30], "leeb": [27, 28, 29, 30], "mehr": [27, 28, 29, 30], "mueller": [27, 28, 29, 30], "putz": [27, 28, 29, 30], "nolt": [27, 28, 29, 30], "2012": [27, 28, 29, 30], "review": [27, 28, 29, 30], "frontier": [27, 28, 29, 30, 34], "neurosci": [27, 28, 29, 30, 34], "burgard": [27, 28, 29, 30, 34], "hum": [27, 28, 29, 30], "5420": [27, 28, 29, 30, 31], "670": [27, 33], "774": 27, "plot_bcic_iv_2a_moabb_crop": [27, 33], "classic": 28, "benefici": 28, "5950": [28, 29], "6092": 28, "2852": 28, "2708": 28, "4424": 28, "1554": 28, "3333": 28, "2141": 28, "7939": 28, "1438": 28, "3438": 28, "1842": 28, "4346": 28, "1380": 28, "jayaram": [28, 29, 30], "vinai": [28, 29, 30], "alexandr": [28, 29, 30, 34], "barach": [28, 29, 30], "trustworthi": [28, 29, 30], "066011": [28, 29, 30], "207": [28, 33], "461": [28, 140], "plot_bcic_iv_2a_moabb_tri": [28, 33], "properli": [29, 107, 110, 111], "exclus": [29, 32], "elabor": [29, 32], "feel": [29, 32], "free": [29, 32], "distinguish": 29, "scheme": [29, 32, 111, 140], "answer": [29, 32], "reliabl": [29, 32], "sound": [29, 32], "divis": [29, 32, 97, 99, 116], "But": [29, 32], "stori": [29, 32], "learnabl": 29, "connect": [29, 30, 83, 86, 90, 97, 103], "bias": 29, "capac": [29, 30], "ml": [29, 32], "degre": [29, 32, 46, 47, 48, 49, 63], "freedom": [29, 32], "kept": [29, 32], "leakag": [29, 32], "memor": [29, 32], "longer": [29, 32, 67, 119], "independ": [29, 32, 41, 59, 107, 140], "never": [29, 32], "explicitli": [29, 32, 107, 108, 111], "recogn": [29, 32], "behind": [29, 32], "alwai": [29, 32, 34, 53, 67, 119], "readabl": [29, 32, 107], "reiniti": [29, 32], "rescal": [29, 30], "varianc": [29, 30, 116], "0x7f4b8671df00": 29, "One": [29, 30, 69, 88, 89], "demarc": [29, 30], "stimulu": [29, 30], "trial_stop_offset_second": [29, 30], "0test": 29, "matter": [29, 32, 75, 76], "distinct": [29, 32], "previous": [29, 32], "credibl": [29, 32], "test_acc": [29, 32], "8074": 29, "3661": 29, "6473": 29, "patch": 29, "font_scal": 29, "plot_simple_train_test": 29, "all_dataset": 29, "bd_cmap": 29, "3a6190": 29, "683e00": 29, "ddf2ff": 29, "2196f3": 29, "ndataset": 29, "nsplit": 29, "invert_yaxi": 29, "ncol": 29, "bbox_to_anchor": 29, "set_xlim": 29, "risk": [29, 45, 62, 129], "tweak": 29, "until": [29, 69], "realli": 29, "unreli": 29, "ratio": 29, "leav": [29, 140], "empti": [29, 67, 107, 111], "x_train": 29, "train_indic": 29, "val_indic": 29, "indices_": 29, "train_subset": 29, "val_subset": 29, "meaning": 29, "3435": 29, "3505": 29, "2759": [29, 30], "2667": 29, "4574": 29, "3478": 29, "1789": 29, "0686": 29, "3389": [29, 34], "compact": [29, 92, 93], "plot_train_valid_test": 29, "n_train": 29, "n_val": 29, "n_test": 29, "suffici": 29, "compens": [29, 107], "unseen": 29, "holdout": 29, "highli": 29, "cross_val_scor": 29, "splitter": 29, "train_val_split": 29, "By": [29, 30, 31, 45, 67, 119], "processor": [29, 30], "cv_result": 29, "3870": 29, "2082": 29, "4359": 29, "3957": 29, "1560": 29, "2123": 29, "2870": [29, 31], "2641": 29, "2266": 29, "2685": 29, "4000": 29, "3003": 29, "2485": 29, "4087": [29, 30], "1477": 29, "2331": 29, "2727": 29, "2076": 29, "2101": 29, "2900": 29, "1233": 29, "2207": 29, "4242": 29, "1577": 29, "2315": 29, "4286": 29, "0504": 29, "2528": 29, "plot_k_fold": 29, "fraction": [29, 31], "ii": 29, "tr_idx": 29, "val_idx": 29, "n_train2": 29, "rotat": [29, 46, 47, 48, 49, 63, 134], "verticalalign": 29, "horizontalalign": 29, "transax": 29, "earli": 29, "rough": 29, "quickli": 29, "messi": 29, "jointli": 29, "analog": [29, 127], "grid": [29, 30], "tupl": [29, 30, 45, 53, 62, 67, 71, 74, 91, 104, 110, 117, 119, 122, 134], "00625": [29, 30], "000625": 29, "best_paramet": 29, "2826": 29, "5258": 29, "0063": [29, 30], "3872": 29, "4053": 29, "2698": 29, "4826": 29, "2205": 29, "2474": 29, "5130": [29, 30], "1218": 29, "2898": 29, "4375": 29, "2991": 29, "5982": 29, "4688": 29, "1161": 29, "6150": 29, "replac": [29, 51, 65, 140], "227": [29, 33], "plot_how_train_test_and_tun": [29, 33], "sensit": [30, 69, 134], "hyeperparamet": 30, "signific": 30, "discrimin": 30, "pathologi": 30, "playbook": 30, "googl": 30, "0x7f4b813d4550": 30, "functool": 30, "partial": 30, "analyz": 30, "initialis": [30, 119], "slice": [30, 107, 108, 112, 113], "fine": 30, "learning_r": 30, "0000625": 30, "module__drop_prob": 30, "got": 30, "5304": 30, "0774": 30, "1724": 30, "1025": 30, "8791": 30, "6174": 30, "1537": 30, "2069": 30, "8708": 30, "8253": 30, "3565": 30, "5936": 30, "3103": 30, "3167": 30, "8444": 30, "1784": 30, "3448": 30, "8563": 30, "8485": 30, "2348": 30, "5185": 30, "0333": 30, "8203": 30, "4272": 30, "3804": 30, "8199": 30, "6046": 30, "8912": 30, "8471": 30, "3911": 30, "7741": 30, "8443": 30, "7828": 30, "9762": 30, "8749": 30, "5826": 30, "1250": 30, "5760": 30, "8846": 30, "2609": 30, "5664": 30, "3793": 30, "1116": 30, "8640": 30, "4696": 30, "4854": 30, "4483": 30, "7445": 30, "8790": 30, "2261": 30, "7070": 30, "1473": 30, "8548": 30, "2435": 30, "6492": 30, "8568": 30, "8457": 30, "2783": 30, "5837": 30, "4035": 30, "8156": 30, "2696": 30, "5464": 30, "1272": 30, "8200": 30, "1099": 30, "2198": 30, "8494": 30, "4783": 30, "8860": 30, "9008": 30, "8582": 30, "1420": 30, "4138": 30, "5099": 30, "8220": 30, "3903": 30, "8248": 30, "8493": 30, "8818": 30, "9960": 30, "3377": 30, "8916": 30, "2516": 30, "5049": 30, "8759": 30, "1913": 30, "1263": 30, "0233": 30, "8622": 30, "2739": 30, "2403": 30, "2586": 30, "1546": 30, "7999": 30, "7535": 30, "9382": 30, "7757": 30, "pivot": 30, "heatmap": 30, "pivot_t": 30, "param_optimizer__lr": 30, "param_module__drop_prob": 30, "fmt": 30, "3f": 30, "cmap": 30, "ylgnbu": 30, "cbar": 30, "model_build": [30, 32], "plot_hyperparameter_tuning_with_scikit": [30, 33], "332": 30, "constructor": 30, "numer": [30, 113], "sequenc": [30, 35, 40, 67, 100, 102, 119, 120, 123, 130, 138, 140], "varun": 30, "godbol": 30, "georg": 30, "dahl": 30, "justin": 30, "gilmer": 30, "christoph": 30, "shallu": 30, "zachari": 30, "nado": 30, "tuning_playbook": 30, "961": [30, 33], "sara": [31, 140], "sedlar": [31, 140], "n_fake_rec": 31, "sinusoid": 31, "gaussian": [31, 43, 60], "nois": [31, 43, 60, 69], "n_fake_ch": 31, "fake_dur": 31, "fake_sfreq": 31, "basedataset": [31, 35, 70, 77, 81, 118, 140], "create_mne_dummy_raw": 31, "fake_regression_dataset": 31, "n_fake_target": 31, "fake_data_split": 31, "target_subset": 31, "sin": 31, "pi": [31, 41, 59], "_data": 31, "expand_dim": 31, "fake_descript": 31, "n_fake_chan": 31, "2999": 31, "990": 31, "model_nam": 31, "deepconvnet": 31, "unknown": [31, 127], "610": 31, "minim": [31, 45, 62, 129, 135], "mse": 31, "ground": [31, 69, 72], "truth": 31, "period": 31, "schedul": [31, 32], "optimizer_lr": 31, "optimizer_weight_decai": 31, "neg_root_mean_squared_error": 31, "train_neg_root_mean_squared_error": 31, "valid_neg_root_mean_squared_error": 31, "2505": 31, "0922": 31, "9275": 31, "0010": 31, "9601": 31, "1497": 31, "2980": 31, "5382": 31, "2746": 31, "3129": 31, "0412": 31, "2603": 31, "4996": 31, "root": [31, 139], "squar": [31, 96, 119], "rmse": 31, "0x7f4b82667b50": 31, "versu": 31, "trend": 31, "y_estim": 31, "ravel": 31, "y_gt": 31, "to_numpi": [31, 125, 126, 127], "polyfit": 31, "poly1d": 31, "kingma": 31, "diederik": 31, "jimmi": 31, "ba": 31, "stochast": 31, "1412": 31, "6980": 31, "2014": [31, 69], "reddi": 31, "sashank": 31, "satyen": 31, "kale": 31, "sanjiv": 31, "kumar": 31, "beyond": [31, 45, 62, 129], "1904": 31, "09237": 31, "plot_regress": [31, 33], "goal": [32, 88, 89, 90], "percept": 32, "adjustmenty": 32, "third": 32, "0x7f4b814601f0": 32, "real": 32, "world": 32, "updat": [32, 67, 68, 70, 71, 77, 80, 113, 117, 119, 138, 140], "tqdm": 32, "train_one_epoch": 32, "loss_fn": 32, "print_batch_stat": 32, "progress_bar": 32, "disabl": [32, 67, 107, 119], "batch_idx": 32, "argmax": 32, "sum": [32, 140], "6f": 32, "accumul": 32, "doesn": [32, 67, 68, 119], "test_model": 32, "n_batch": [32, 124, 128], "test_loss": 32, "batch_loss": 32, "nnloss": 32, "seamlessli": 32, "train_load": 32, "test_load": 32, "test_accuraci": 32, "784639": 32, "97it": 32, "497504": 32, "06it": 32, "544960": 32, "22it": 32, "552846": 32, "32it": 32, "648800": 32, "75it": 32, "46it": 32, "067186": 32, "31it": 32, "475584": 32, "224932": 32, "30it": 32, "333470": 32, "520719": 32, "27it": 32, "324378": 32, "605750": 32, "460681": 32, "50it": 32, "178580": 32, "232657": 32, "40it": 32, "294503": 32, "35it": 32, "144602": 32, "89it": 32, "64it": 32, "412761": 32, "21it": 32, "751282": 32, "26it": 32, "565452": 32, "29it": 32, "667822": 32, "836633": 32, "646790": 32, "262205": 32, "nice": 32, "interfac": [32, 34, 88, 89, 92, 93], "previou": [32, 140], "torchmetr": 32, "litmodul": 32, "lightningmodul": 32, "training_step": 32, "y_hat": 32, "test_step": 32, "multiclass": 32, "num_class": 32, "log_dict": 32, "configure_optim": 32, "trainer": 32, "lit_model": 32, "tpu": 32, "ipu": 32, "hpu": 32, "connector": 32, "logger_connector": 32, "tensorboardx": 32, "conflict": [32, 67, 119], "ecosystem": 32, "logger": 32, "csvlogger": 32, "unless": [32, 119], "tensorboard": 32, "pip": [32, 137, 138, 139, 140], "instal": [32, 67, 107, 110, 119, 140], "extra": [32, 140], "lightning_log": 32, "189": 32, "data_connector": 32, "441": 32, "train_dataload": 32, "fit_loop": 32, "293": 32, "interv": [32, 72, 113], "log_every_n_step": 32, "81it": 32, "v_num": 32, "01it": 32, "15it": 32, "14it": 32, "28it": 32, "37it": 32, "41it": 32, "62it": 32, "61it": 32, "checkpoint_connector": 32, "145": 32, "ckpt_path": 32, "silenc": 32, "restor": [32, 67], "state": [32, 120, 121, 122, 123], "version_0": 32, "ckpt": 32, "test_dataload": 32, "74it": 32, "77it": 32, "76it": 32, "3402777910232544": 32, "509909749031067": 32, "203": [32, 33], "545": [32, 33], "plot_train_in_pure_pytorch_and_pytorch_lightn": [32, 33], "497": [33, 140], "auto_examples_model_build": 33, "535": [33, 140], "773": 33, "scientif": 34, "softwar": [34, 135], "canon": 34, "hbm23730": 34, "robin": [34, 140], "tibor": [34, 140], "jost": 34, "tobia": 34, "dominiqu": 34, "josef": 34, "martin": [34, 140], "katharina": 34, "michael": 34, "frank": 34, "wolfram": 34, "tonio": 34, "issn": 34, "1097": 34, "0193": 34, "url": 34, "keyword": [34, 35, 73, 105, 107, 108, 109, 110, 111, 117], "electroencephalographi": 34, "interpret": [34, 39, 56, 107, 108, 119], "built": [34, 135], "zenodo": 34, "ask": [34, 69], "fnin": 34, "2013": 34, "00267": 34, "luessi": 34, "larson": 34, "eric": 34, "deni": [34, 140], "strohmeier": 34, "brodbeck": 34, "christian": 34, "goj": 34, "roman": 34, "ja": 34, "mainak": 34, "brook": 34, "teon": 34, "parkkonen": 34, "lauri": 34, "h\u00e4m\u00e4l\u00e4inen": 34, "matti": 34, "volum": 34, "267": 34, "frontiersin": 34, "453x": 34, "appropri": [34, 138], "kwarg": [35, 67, 91, 109, 119, 125, 126, 127], "max_freq": 36, "band": [36, 54, 107, 117, 140], "desir": [36, 46, 54, 63, 69, 105, 111], "suggest": [36, 39, 43, 46, 47, 48, 49, 51, 54, 56, 60, 63, 80, 113], "distanc": [36, 54, 69], "admiss": 36, "1hz": 36, "nyquist": 36, "cheng": [36, 43, 51, 54, 60, 65], "goh": [36, 43, 51, 54, 60, 65], "dogrusoz": [36, 43, 51, 54, 60, 65], "tuzel": [36, 43, 51, 54, 60, 65], "azemi": [36, 43, 51, 54, 60, 65], "awar": [36, 43, 51, 54, 60, 65], "biosign": [36, 43, 51, 54, 60, 65], "04871": [36, 43, 51, 54, 60, 65], "mohsenvand": [36, 43, 51, 54, 60, 65], "izadi": [36, 43, 51, 54, 60, 65], "mae": [36, 43, 51, 54, 60, 65], "electroencephalogram": [36, 43, 51, 54, 60, 65], "health": [36, 43, 51, 54, 60, 65], "238": [36, 43, 51, 54, 60, 65], "253": [36, 43, 51, 54, 60, 65], "pmlr": [36, 43, 51, 54, 60, 65], "get_augmentation_param": [36, 37, 38, 39, 41, 42, 43, 45, 46, 51, 53, 140], "freqs_to_notch": [36, 54], "greater": [36, 54], "static": [36, 37, 38, 39, 41, 42, 43, 44, 45, 46, 50, 51, 52, 68], "cmsaugment": [37, 38, 55, 57], "polici": [37, 38, 55, 57], "proba_drop": 37, "eras": 37, "saeed": [37, 38, 55, 57], "grangier": [37, 38, 55, 57], "pietquin": [37, 38, 55, 57], "zeghidour": [37, 38, 55, 57], "heterogen": [37, 38, 55, 57], "differenti": [37, 38, 55, 57], "reorder": [37, 38, 55, 57], "2010": [37, 38, 55, 57, 72], "13694": [37, 38, 55, 57], "p_shuffl": [38, 57], "permut": [38, 39, 45, 56, 57, 62], "carri": [38, 57, 69], "ordered_ch_nam": [39, 47, 48, 49], "invert": 39, "side": [39, 107], "nomenclatur": 39, "deiss": [39, 56], "biswal": [39, 56], "jin": [39, 56], "sun": [39, 56], "westov": [39, 56], "hamlet": [39, 56], "co": [39, 56], "techniqu": [39, 56, 107, 111], "1803": [39, 56, 100], "09702": [39, 56], "accord": [39, 56, 111], "channel_indep": [41, 59], "ft": [41, 59, 83], "surrog": [41, 59], "perturb": [41, 59], "uniformli": [41, 45, 46, 47, 48, 49, 59, 120], "schwabed": [41, 59], "snyder": [41, 59], "cakmak": [41, 59], "nemati": [41, 59], "clifford": [41, 59], "address": [41, 59], "imbal": [41, 59, 74], "noisi": [41, 59], "fourier": [41, 59], "1806": [41, 59], "08675": [41, 59], "magnitud": [41, 51], "cliffordlab": [41, 59], "tf": [41, 59], "draw": [41, 59], "maximum": [42, 46, 47, 48, 49, 83, 112], "absolut": 42, "delta_freq": [42, 58], "amplitud": [42, 58, 112, 113, 140], "white": [43, 60], "deviat": [43, 60], "wang": [43, 60], "zhong": [43, 60], "jiang": [43, 60], "liu": [43, 60, 86], "emot": [43, 60], "recognit": [43, 60], "confer": [43, 45, 46, 47, 48, 49, 60, 62, 63], "multimedia": [43, 60], "beta_per_sampl": 45, "drawn": 45, "beta": 45, "hongyi": [45, 62, 129], "zhang": [45, 62, 90, 129], "moustapha": [45, 62, 129], "ciss": [45, 62, 129], "yann": [45, 62, 129], "dauphin": [45, 62, 129], "david": [45, 62, 129], "lopez": [45, 62, 129], "paz": [45, 62, 129], "empir": [45, 62, 100, 129], "iclr": [45, 62], "onlin": [45, 62, 84, 88, 89, 95, 96, 129, 134], "1710": [45, 62, 129], "09412": [45, 62, 129], "facebookresearch": [45, 62, 129], "cifar10": [45, 62, 129], "interpol": [45, 46, 47, 48, 49, 62, 63], "lam": [45, 62], "idx_perm": [45, 62], "sensors_positions_matrix": [46, 63], "max_degre": [46, 47, 48, 49], "spherical_splin": [46, 47, 48, 49, 63], "angl": [46, 47, 48, 49, 63, 134], "3d": [46, 63, 140], "cartesian": [46, 63], "coordin": [46, 63], "ten_twenty_montag": [46, 63], "make_standard_montag": [46, 63], "standard_1020": [46, 63], "get_posit": [46, 63], "ch_po": [46, 63], "spheric": [46, 47, 48, 49, 63], "spline": [46, 47, 48, 49, 63], "scipi": [46, 47, 48, 49, 63, 67, 107, 110, 119], "rbf": [46, 47, 48, 49, 63], "quadrat": [46, 47, 48, 49, 63], "krell": [46, 47, 48, 49, 63], "kim": [46, 47, 48, 49, 63, 90], "electroencephalograph": [46, 47, 48, 49, 63], "39th": [46, 47, 48, 49, 63], "annual": [46, 47, 48, 49, 63], "medicin": [46, 47, 48, 49, 63], "biologi": [46, 47, 48, 49, 63], "societi": [46, 47, 48, 49, 63], "embc": [46, 47, 48, 49, 63], "471": [46, 47, 48, 49, 63], "474": [46, 47, 48, 49, 63], "element": [46, 51, 63], "montag": [47, 48, 49, 69], "flip": [50, 52, 64, 66], "sign": [50, 64], "smoothli": [51, 65], "Will": 51, "mask_start_per_sampl": [51, 65], "resp": 53, "uniform": 53, "arg": [67, 91, 119], "iterator_train__drop_last": [67, 119, 140], "uninstanti": [67, 119], "get_loss": 67, "classes_": 67, "attributeerror": 67, "sgd": [67, 119], "outcom": [67, 119], "keyboard": [67, 119], "interrupt": [67, 119], "mini": [67, 119], "iterator_train__batch_s": [67, 119], "iterator_test__batch_s": [67, 119], "iterator_valid": [67, 119], "incom": [67, 119], "__len__": [67, 119], "deal": [67, 119], "box": [67, 119], "dataset__": [67, 119], "initialz": [67, 119], "dataset_train": [67, 119, 125, 126, 127], "dataset_valid": [67, 119, 125, 126, 127], "get_default_callback": [67, 119], "resolv": [67, 119], "suffix": [67, 119], "epochscoring_1": [67, 119], "print_log": [67, 119], "callbacks__print_log__keys_ignor": [67, 119], "predict_nonlinear": [67, 119], "pickleabl": [67, 119], "accept": [67, 80, 102, 113, 119], "predict_proba": [67, 119, 140], "whatev": [67, 119], "anywher": [67, 119], "notabl": [67, 119], "unaffect": [67, 119], "warm_start": [67, 119], "cold": [67, 119], "warm": [67, 119], "summari": [67, 91, 101, 119], "regardless": [67, 119], "acceler": [67, 119], "sent": [67, 119], "unmodifi": [67, 119], "compil": [67, 119], "volta": [67, 119], "amper": [67, 119], "dunder": [67, 119], "notat": [67, 119], "compile__dynam": [67, 119], "dynam": [67, 119], "use_cach": [67, 119, 125, 126], "overrid": [67, 68, 119], "cach": [67, 119], "batchscor": [67, 119], "certain": [67, 119], "situat": [67, 119], "tight": [67, 119], "cumbersom": [67, 119], "global": [67, 119, 127], "honor": [67, 119], "prefer": [67, 119], "model_evalu": [67, 119], "prefixes_": [67, 119], "special": [67, 119], "neuralnet": [67, 119], "optimizer__momentum": [67, 119], "popul": [67, 119, 140], "cuda_dependent_attributes_": [67, 119], "whose": [67, 80, 113, 119], "unpickl": [67, 119], "expand": [67, 103, 119], "initialized_": [67, 119], "criterion_": [67, 119], "callbacks_": [67, 119], "_modul": [67, 119], "_criteria": [67, 119], "_optim": [67, 119], "get_iter": [67, 119], "drop_index": [67, 119], "iterator_test": [67, 119], "spars": [67, 119], "csr": [67, 119], "y_proba": [67, 119], "trial_predict": [67, 119, 130], "n_trial": [67, 78, 119, 130], "n_predict": [67, 119, 124, 128, 130], "trial_label": [67, 119, 130], "n_target": [67, 119, 130], "bbci": 68, "de": 68, "desc_4": 68, "pdf": 68, "force_upd": 68, "mne_datasets_": 68, "_path": 68, "forc": 68, "iia": 69, "r382d436f3223": 69, "cue": [69, 72], "imag": [69, 88, 89], "inat": 69, "movement": [69, 72], "compris": 69, "288": [69, 140], "sit": 69, "comfort": 69, "armchair": 69, "front": 69, "screen": 69, "fixat": 69, "acoust": 69, "tone": 69, "arrow": [69, 72], "down": [69, 97, 103, 110, 132], "foot": 69, "prompt": [69, 135], "disappear": 69, "twenti": 69, "agcl": 69, "inter": [69, 72], "monopolarli": 69, "mastoid": [69, 111], "amplifi": 69, "\u03bcv": 69, "notch": 69, "suppress": [69, 107], "raw_preproc_kwarg": 70, "window_preproc_kwarg": 70, "old": [70, 118, 140], "datapoint": 70, "gamma": 72, "subj": 72, "500hz": 72, "r5e478952091a": 72, "cover": [72, 134], "cortex": 72, "healthi": [72, 74], "963": 72, "divid": [72, 78, 79, 80, 112], "rest": [72, 111], "approx": 72, "880": 72, "except": [72, 74], "acquir": 72, "lab": 72, "invas": 72, "2008": [72, 85], "darva": 72, "direct": [72, 135], "grai": 72, "back": 72, "had": [72, 88, 89, 91], "clench": 72, "toe": 72, "downward": 72, "tap": 72, "leftward": 72, "rightward": 72, "relax": 72, "upward": 72, "littl": 72, "proxim": 72, "muscular": 72, "volv": 72, "pace": 72, "maintain": 72, "pseudo": 72, "ideal": 72, "260": 72, "stimuli": 72, "bci2000": 72, "schalk": 72, "2004": 72, "approv": 72, "ethic": 72, "committe": 72, "freiburg": 72, "dataset_kwarg": 73, "load_eeg_onli": 74, "content": 74, "edfx": 74, "overnight": 74, "auto_tutori": 74, "plot_sleep": 74, "eog": [74, 103], "emg": 74, "temperatur": 74, "respir": 74, "3h": 74, "parent": [75, 76], "ascend": [75, 76], "preserv": [75, 76], "physician": [75, 76], "c_tuab": 76, "i_window_in_tri": [77, 121, 131], "i_start_in_tri": [77, 121], "i_stop_in_tri": [77, 121, 131], "applic": [77, 107], "drop_bad_window": [80, 113], "accepted_bads_ratio": [80, 113], "onset": [80, 113], "fall": [80, 113], "outsid": [80, 113], "proport": [80, 88, 89, 113], "withinconsist": 80, "exceed": [80, 113], "pathlib": 81, "concat_dataset": [81, 82], "conv_block_n_filt": 83, "conv_block_kernel_length_1": 83, "conv_block_kernel_length_2": 83, "conv_block_pool_size_1": 83, "conv_block_pool_size_2": 83, "conv_block_depth_mult": 83, "conv_block_dropout": 83, "att_head_dim": 83, "att_num_head": 83, "att_dropout": 83, "tcn_depth": 83, "tcn_kernel_s": 83, "tcn_n_filter": 83, "tcn_dropout": 83, "tcn_activ": 83, "max_norm_const": 83, "input_size_": [83, 97, 98, 99, 103], "offici": [83, 138], "tensorflow": 83, "block": [83, 88, 89, 90, 100, 103], "denot": 83, "kc": 83, "p2": 83, "depthwis": [83, 88, 89], "pc": 83, "head": [83, 86, 99, 121], "dh": 83, "1_": 83, "pa": 83, "residu": [83, 94], "kt": 83, "slid": 83, "feed": [83, 99], "logit": 83, "contrari": 83, "constraint": 83, "impos": 83, "altaheri": 83, "muhammad": 83, "alsulaiman": 83, "physic": 83, "industri": 83, "informat": 83, "tii": 83, "3197419": 83, "overridden": [83, 86, 90], "subclass": [83, 86, 90], "recip": [83, 86, 90], "care": [83, 86, 90], "regist": [83, 86, 90], "hook": [83, 86, 90, 140], "latter": [83, 86, 90], "silent": [83, 86, 90], "first_conv_nonlin": 84, "first_pool_nonlin": 84, "later_conv_nonlin": 84, "later_pool_nonlin": 84, "supratak": 85, "bidirect": 85, "supratak2017": 85, "dong": 85, "wu": 85, "guo": 85, "1998": 85, "att_depth": 86, "att_head": 86, "att_drop_prob": 86, "final_fc_length": 86, "2440": 86, "return_featur": 86, "conform": 86, "methodolog": 86, "song2022": 86, "conformercod": 86, "tradit": 86, "n_timestep": 86, "compos": 86, "patchembed": 86, "transformerencod": 86, "classificationhead": 86, "recombin": 86, "song": [86, 140], "zheng": 86, "q": 86, "gao": 86, "710": 86, "719": 86, "ieeexplor": 86, "9991178": 86, "eeyhsong": 86, "get_fc_siz": 86, "in_channel": [87, 88, 89, 90], "itnet": [87, 140], "incept": [87, 88, 89, 90, 140], "salami": 87, "salami2022": 87, "abbassalami": 87, "guarante": [87, 88, 89, 90, 92, 93], "reimplement": [87, 88, 89, 90, 92, 93], "andreu": 87, "perez": 87, "gillmeist": 87, "3161489": 87, "scales_samples_": [88, 89], "125": [88, 89, 98], "n_filter": [88, 89, 90, 100], "depth_multipli": [88, 89], "pooling_s": [88, 89], "erp": [88, 89], "AND": 88, "WILL": 88, "BE": 88, "IN": 88, "THE": 88, "OF": 88, "santamaria2020": [88, 89], "inceptionnet": [88, 89, 90], "largest": [88, 89], "associ": [88, 89], "winner": [88, 89], "beetl": [88, 89], "neurip": [88, 89], "r15fdf33b022f": 88, "santamaria": [88, 89], "vazquez": [88, 89], "martinez": [88, 89], "cagig": [88, 89], "vaquerizo": [88, 89], "villar": [88, 89], "hornero": [88, 89], "assist": [88, 89], "3048106": [88, 89], "grifcc": [88, 89], "r37c4761d4e92": 89, "n_conv": 90, "kernel_unit_": 90, "input_window_": 90, "vision": 90, "wide": 90, "branch": 90, "1d": 90, "bose": 90, "eskandarian": 90, "accur": 90, "robust": 90, "046014": 90, "mixin": 91, "output_shap": [91, 104], "get_torchinfo_statist": 91, "col_nam": 91, "input_s": 91, "num_param": 91, "row_set": 91, "modelstatist": 91, "load_state_dict": 91, "state_dict": 91, "intermedi": 91, "bug": 91, "second_kernel_s": 92, "third_kernel_s": [92, 93], "eegnet": [92, 93], "lawhern": [92, 93], "2016": 92, "solon": [92, 93], "waytowich": [92, 93], "gordon": [92, 93], "hung": [92, 93], "lanc": [92, 93], "1611": [92, 93], "08024": [92, 93], "f2": 93, "kernel_length": 93, "v4": 93, "eegnet4": 93, "final_pool_length": [94, 140], "n_first_filt": 94, "n_layers_per_block": 94, "first_filter_length": 94, "batch_norm_epsilon": 94, "conv_weight_init_fn": 94, "hybrid": 95, "safe_log": 96, "n_conv_chan": 97, "n_group": 97, "max_pool_s": 97, "blanco": 97, "blanco2020": 97, "seven": 97, "group": 97, "fernandez": 97, "rivero": 97, "pazo": 97, "soft": 97, "4067": 97, "4079": 97, "1007": 97, "s00500": 97, "04174": 97, "time_conv_size_": [98, 103], "max_pool_size_": 98, "pad_size_": 98, "half": [98, 107], "n_tce": 99, "d_model": 99, "d_ff": 99, "n_attn_head": 99, "after_reduced_cnn_s": 99, "multi": 99, "resolut": 99, "mrcnn": 99, "recalibr": 99, "tce": 99, "mechan": [99, 140], "captur": 99, "among": 99, "100hz": 99, "125hz": 99, "shh": 99, "unintend": 99, "clone": [99, 140], "positionwisefeedforward": 99, "emadeldeen24": 99, "attnsleep": 99, "sleepdata": 99, "n_block": 100, "n_in_chan": 100, "bai": 100, "bai2018": 100, "locuslab": 100, "kolter": 100, "koltun": 100, "recurr": 100, "01271": 100, "s_growth": 101, "t_filter": 101, "temp_lay": 101, "spat_lay": 101, "temp_span": 101, "thinker": [101, 140], "invari": [101, 140], "densenet": 101, "kosta": 101, "growth": 101, "densefilt": 101, "percentag": 101, "temp_len": 101, "spoclab": 101, "ca": 101, "thinkerinvari": 101, "rudzicz": 101, "across": [101, 111, 120, 124], "peopl": 101, "eng": 101, "056008": 101, "2552": 101, "abb7a7": 101, "stager": 102, "middl": 102, "seq_len": 102, "n_time_filt": 103, "complexity_factor": 103, "0703125": 103, "ensure_odd_conv_s": 103, "autoencod": 103, "shrink": 103, "fewer": [103, 107], "2x2": 103, "halv": 103, "ne": 103, "subsequ": 105, "time_as_index": 105, "first_samp": 105, "last_samp": 105, "exce": 105, "exclud": [105, 107, 108, 111], "on_miss": [106, 112, 113], "emit": 106, "evok": [106, 107, 108, 111], "reorder_channel": 106, "drop_channel": 106, "filter_length": 107, "l_trans_bandwidth": 107, "h_trans_bandwidth": 107, "iir_param": 107, "fir_window": 107, "fir_design": 107, "skip_by_annot": 107, "bad_acq_skip": 107, "reflect_limit": [107, 110], "iir": 107, "meg0111": [107, 108], "meg2623": [107, 108], "reciproc": 107, "shortest": 107, "firwin2": 107, "5500m": 107, "doubl": 107, "cupi": [107, 110], "filtfilt": 107, "4th": 107, "butterworth": 107, "construct_iir_filt": 107, "symmetr": 107, "construct": [107, 111], "delai": [107, 140], "twice": 107, "minimum": 107, "weaker": 107, "lfilter": 107, "hann": 107, "blackman": 107, "concatenate_raw": 107, "acquisit": 107, "reflect": [107, 110], "mirror": [107, 110], "create_filt": 107, "savgol_filt": 107, "notch_filt": 107, "filter_data": 107, "apply_funct": 109, "raw_or_epoch": 109, "npad": 110, "boxcar": 110, "joint": 111, "virtual": 111, "infin": 111, "footcit": 111, "yao2001": 111, "apply_proj": 111, "seeg": 111, "projector": 111, "set_bipolar_refer": 111, "bipolar": 111, "m1": 111, "m2": 111, "concatdataset": 112, "ie": 112, "winddow_size_sampl": 112, "exactli": 113, "inconsist": 113, "demeanin": 115, "exponent": [115, 116], "m_t": [115, 116], "mathrm": [115, 116], "factornew": [115, 116], "cdot": [115, 116], "x_t": [115, 116], "m_": [115, 116], "deman": 115, "_t": [115, 116], "demean": 115, "Then": 116, "v_t": 116, "v_": 116, "sqrt": 116, "stabil": 116, "frequency_band": 117, "drop_original_sign": 117, "order_by_frequency_band": 117, "mne_filter_kwarg": 117, "unfilt": 117, "cz_4": 117, "o1_4": 117, "cz_8": 117, "o1_8": 117, "fileexistserror": 118, "n_sequenc": [120, 123], "inspir": 120, "perslev2021": 120, "recordingsampl": [120, 122, 123], "randomst": [120, 121, 122, 123], "sample_class": 120, "rec_ind": [120, 121], "session_t": 121, "run_0": 121, "multiindex": 121, "sample_record": 121, "sample_window": 121, "tau_max": 122, "banville2020": 122, "file_id": 123, "ensembl": [123, 140], "loss_funct": [124, 128], "target_extractor": [125, 126, 127], "on_epoch_end": [125, 126, 127], "on_batch_end": 126, "recomput": 127, "slightli": 127, "scorer": 127, "signatur": 127, "scalar": 127, "wors": 127, "tri": 127, "timeseri": 128, "window_len": 128, "mixup": [129, 140], "duplic": [131, 140], "2darrai": 131, "preds_per_tri": 131, "lack": 132, "pythonhashse": 132, "forum": 132, "ai": 132, "solv": [132, 140], "31628": 132, "use_deterministic_algorithm": 132, "linearsegmentedcolormap": 134, "textcolor": 134, "vmin": 134, "vmax": 134, "fontweight": 134, "rotate_row_label": 134, "rotate_col_label": 134, "with_f1_scor": 134, "norm_ax": 134, "rotate_precis": 134, "class_names_fonts": 134, "font": 134, "bold": 134, "heavi": 134, "ultrabold": 134, "ultralight": 134, "hard": 135, "happen": [135, 140], "mistak": 135, "corrupt": 135, "irregular": 135, "chat": 135, "bear": 135, "tracker": 135, "sure": 135, "ve": 135, "shell": 135, "__version__": [135, 139], "latest": [135, 138, 139], "replic": 135, "link": [135, 140], "anonym": 135, "portion": 135, "persist": 135, "smallest": 135, "past": 135, "backtick": 135, "contributor": [135, 139], "snippet": 135, "toolbox": 136, "electrophysiolog": 136, "fetcher": 136, "neuroscientist": 136, "who": 136, "neurophysiolog": 136, "pypi": 137, "repositori": 137, "beginn": 137, "familiar": 137, "instruct": 137, "contribut": [137, 139], "braincod": 138, "command": [138, 139], "nvidia": 138, "driver": 138, "cuda_path": 138, "troubleshoot": 138, "thing": 139, "enter": 139, "git": 139, "cd": 139, "repo": 139, "zipbal": 139, "master": 139, "egg": 139, "edit": 139, "verifi": 139, "guidelin": 139, "whats_new": 140, "incompat": 140, "429": 140, "431": 140, "mohammad": 140, "javad": 140, "oskar": 140, "st\u00f8rmer": 140, "417": 140, "454": 140, "yonghao": 140, "einop": 140, "466": 140, "467": 140, "marco": 140, "zamboni": 140, "refactor": 140, "conda": 140, "yml": 140, "ci": 140, "479": 140, "action": 140, "489": 140, "485": 140, "490": 140, "487": 140, "473": 140, "488": 140, "495": 140, "sylvain": 140, "chevalli": 140, "494": 140, "bruna": 140, "lope": 140, "491": 140, "enforc": 140, "env": 140, "505": 140, "friendli": 140, "\u015bliwowski": 140, "shallowfbcsp": 140, "503": 140, "sampler": 140, "504": 140, "th\u00e9o": 140, "dropchannel": 140, "seteegrefer": 140, "514": 140, "517": 140, "523": 140, "remi": 140, "delboui": 140, "524": 140, "529": 140, "528": 140, "539": 140, "541": 140, "hint": 140, "551": 140, "valentin": 140, "ioven": 140, "pyproject": 140, "toml": 140, "553": 140, "commit": 140, "556": 140, "e231": 140, "whitespac": 140, "untrac": 140, "flake8": 140, "transposit": 140, "_frequency_shift": 140, "446": 140, "matthieu": 140, "terri": 140, "451": 140, "465": 140, "wrong": 140, "538": 140, "546": 140, "397": 140, "flag": 140, "513": 140, "390": 140, "ghaith": 140, "bouallegu": 140, "371": 140, "389": 140, "exemplifi": 140, "349": 140, "unifi": 140, "378": 140, "wimpff": 140, "391": 140, "406": 140, "recoding_id": 140, "402": 140, "ft_surrog": 140, "409": 140, "get_param": 140, "388": 140, "alex": 140, "413": 140, "zscore": 140, "mnepreproc": 140, "numpypreproc": 140, "415": 140, "411": 140, "263": 140, "ann": 140, "kathrin": 140, "kiessner": 140, "henrik": 140, "bonsmann": 140, "vytauta": 140, "jankauska": 140, "274": 140, "254": 140, "thoma": 140, "287": 140, "aggregate_proba": 140, "312": 140, "balancedsequencesampl": 140, "277": 140, "318": 140, "261": 140, "cloneabl": 140, "347": 140, "353": 140, "333": 140, "365": 140, "367": 140, "mismatch": 140, "327": 140, "propag": 140, "favour": 140, "292": 140, "199": 140, "198": 140, "178": 140, "138": 140, "147": 140, "realiz": 140, "filterbank": 140, "158": 140, "159": 140, "timecrop": 140, "164": 140, "185": 140, "282": 140, "341": 140, "accident": 140, "167": 140, "compute_amplitude_gradi": 140, "4d": 140, "166": 140, "incorrect": 140, "146": 140, "169": 140, "window_s": 140, "148": 140, "171": 140, "155": 140, "223": 140, "favor": 140}, "objects": {"": [[0, 0, 0, "-", "braindecode"]], "braindecode.augmentation": [[35, 1, 1, "", "AugmentedDataLoader"], [36, 1, 1, "", "BandstopFilter"], [37, 1, 1, "", "ChannelsDropout"], [38, 1, 1, "", "ChannelsShuffle"], [39, 1, 1, "", "ChannelsSymmetry"], [40, 1, 1, "", "Compose"], [41, 1, 1, "", "FTSurrogate"], [42, 1, 1, "", "FrequencyShift"], [43, 1, 1, "", "GaussianNoise"], [44, 1, 1, "", "IdentityTransform"], [45, 1, 1, "", "Mixup"], [46, 1, 1, "", "SensorsRotation"], [47, 1, 1, "", "SensorsXRotation"], [48, 1, 1, "", "SensorsYRotation"], [49, 1, 1, "", "SensorsZRotation"], [50, 1, 1, "", "SignFlip"], [51, 1, 1, "", "SmoothTimeMask"], [52, 1, 1, "", "TimeReverse"], [53, 1, 1, "", "Transform"]], "braindecode.augmentation.BandstopFilter": [[36, 2, 1, "", "get_augmentation_params"], [36, 2, 1, "", "operation"]], "braindecode.augmentation.ChannelsDropout": [[37, 2, 1, "", "get_augmentation_params"], [37, 2, 1, "", "operation"]], "braindecode.augmentation.ChannelsShuffle": [[38, 2, 1, "", "get_augmentation_params"], [38, 2, 1, "", "operation"]], "braindecode.augmentation.ChannelsSymmetry": [[39, 2, 1, "", "get_augmentation_params"], [39, 2, 1, "", "operation"]], "braindecode.augmentation.Compose": [[40, 2, 1, "", "forward"]], "braindecode.augmentation.FTSurrogate": [[41, 2, 1, "", "get_augmentation_params"], [41, 2, 1, "", "operation"]], "braindecode.augmentation.FrequencyShift": [[42, 2, 1, "", "get_augmentation_params"], [42, 2, 1, "", "operation"]], "braindecode.augmentation.GaussianNoise": [[43, 2, 1, "", "get_augmentation_params"], [43, 2, 1, "", "operation"]], "braindecode.augmentation.IdentityTransform": [[44, 2, 1, "", "operation"]], "braindecode.augmentation.Mixup": [[45, 2, 1, "", "get_augmentation_params"], [45, 2, 1, "", "operation"]], "braindecode.augmentation.SensorsRotation": [[46, 2, 1, "", "get_augmentation_params"], [46, 2, 1, "", "operation"]], "braindecode.augmentation.SignFlip": [[50, 2, 1, "", "operation"]], "braindecode.augmentation.SmoothTimeMask": [[51, 2, 1, "", "get_augmentation_params"], [51, 2, 1, "", "operation"]], "braindecode.augmentation.TimeReverse": [[52, 2, 1, "", "operation"]], "braindecode.augmentation.Transform": [[53, 2, 1, "", "forward"], [53, 2, 1, "", "get_augmentation_params"]], "braindecode.augmentation.functional": [[54, 3, 1, "", "bandstop_filter"], [55, 3, 1, "", "channels_dropout"], [56, 3, 1, "", "channels_permute"], [57, 3, 1, "", "channels_shuffle"], [58, 3, 1, "", "frequency_shift"], [59, 3, 1, "", "ft_surrogate"], [60, 3, 1, "", "gaussian_noise"], [61, 3, 1, "", "identity"], [62, 3, 1, "", "mixup"], [63, 3, 1, "", "sensors_rotation"], [64, 3, 1, "", "sign_flip"], [65, 3, 1, "", "smooth_time_mask"], [66, 3, 1, "", "time_reverse"]], "braindecode.classifier": [[67, 1, 1, "", "EEGClassifier"]], "braindecode.classifier.EEGClassifier": [[67, 4, 1, "", "_criteria"], [67, 4, 1, "", "_modules"], [67, 4, 1, "", "_optimizers"], [67, 4, 1, "", "callbacks_"], [67, 4, 1, "", "classes_"], [67, 4, 1, "", "criterion_"], [67, 4, 1, "", "cuda_dependent_attributes_"], [67, 2, 1, "", "get_iterator"], [67, 2, 1, "", "get_loss"], [67, 4, 1, "", "initialized_"], [67, 4, 1, "", "module_"], [67, 2, 1, "", "predict"], [67, 2, 1, "", "predict_proba"], [67, 2, 1, "", "predict_trials"], [67, 4, 1, "", "prefixes_"]], "braindecode.datasets": [[68, 1, 1, "", "BCICompetitionIVDataset4"], [69, 1, 1, "", "BNCI2014001"], [70, 1, 1, "", "BaseConcatDataset"], [71, 1, 1, "", "BaseDataset"], [72, 1, 1, "", "HGD"], [73, 1, 1, "", "MOABBDataset"], [74, 1, 1, "", "SleepPhysionet"], [75, 1, 1, "", "TUH"], [76, 1, 1, "", "TUHAbnormal"], [77, 1, 1, "", "WindowsDataset"], [78, 3, 1, "", "create_from_X_y"], [79, 3, 1, "", "create_from_mne_epochs"], [80, 3, 1, "", "create_from_mne_raw"]], "braindecode.datasets.BCICompetitionIVDataset4": [[68, 2, 1, "", "download"]], "braindecode.datasets.BaseConcatDataset": [[70, 2, 1, "", "get_metadata"], [70, 2, 1, "", "save"], [70, 2, 1, "", "set_description"], [70, 2, 1, "", "split"]], "braindecode.datasets.BaseDataset": [[71, 2, 1, "", "set_description"]], "braindecode.datasets.WindowsDataset": [[77, 2, 1, "", "set_description"]], "braindecode.datautil": [[81, 3, 1, "", "load_concat_dataset"], [82, 3, 1, "", "save_concat_dataset"]], "braindecode.models": [[83, 1, 1, "", "ATCNet"], [84, 1, 1, "", "Deep4Net"], [85, 1, 1, "", "DeepSleepNet"], [86, 1, 1, "", "EEGConformer"], [87, 1, 1, "", "EEGITNet"], [88, 1, 1, "", "EEGInception"], [89, 1, 1, "", "EEGInceptionERP"], [90, 1, 1, "", "EEGInceptionMI"], [91, 1, 1, "", "EEGModuleMixin"], [92, 1, 1, "", "EEGNetv1"], [93, 1, 1, "", "EEGNetv4"], [94, 1, 1, "", "EEGResNet"], [95, 1, 1, "", "HybridNet"], [96, 1, 1, "", "ShallowFBCSPNet"], [97, 1, 1, "", "SleepStagerBlanco2020"], [98, 1, 1, "", "SleepStagerChambon2018"], [99, 1, 1, "", "SleepStagerEldele2021"], [100, 1, 1, "", "TCN"], [101, 1, 1, "", "TIDNet"], [102, 1, 1, "", "TimeDistributed"], [103, 1, 1, "", "USleep"], [104, 3, 1, "", "get_output_shape"]], "braindecode.models.ATCNet": [[83, 2, 1, "", "forward"]], "braindecode.models.DeepSleepNet": [[85, 2, 1, "", "forward"]], "braindecode.models.EEGConformer": [[86, 2, 1, "", "forward"], [86, 2, 1, "", "get_fc_size"]], "braindecode.models.EEGInceptionMI": [[90, 2, 1, "", "forward"]], "braindecode.models.EEGModuleMixin": [[91, 2, 1, "", "get_output_shape"], [91, 2, 1, "", "get_torchinfo_statistics"], [91, 2, 1, "", "load_state_dict"], [91, 2, 1, "", "to_dense_prediction_model"]], "braindecode.models.HybridNet": [[95, 2, 1, "", "forward"]], "braindecode.models.SleepStagerBlanco2020": [[97, 2, 1, "", "forward"]], "braindecode.models.SleepStagerChambon2018": [[98, 2, 1, "", "forward"]], "braindecode.models.SleepStagerEldele2021": [[99, 2, 1, "", "forward"]], "braindecode.models.TCN": [[100, 2, 1, "", "forward"]], "braindecode.models.TIDNet": [[101, 2, 1, "", "forward"]], "braindecode.models.TimeDistributed": [[102, 2, 1, "", "forward"]], "braindecode.models.USleep": [[103, 2, 1, "", "forward"]], "braindecode.preprocessing": [[105, 1, 1, "", "Crop"], [106, 1, 1, "", "DropChannels"], [107, 1, 1, "", "Filter"], [108, 1, 1, "", "Pick"], [109, 1, 1, "", "Preprocessor"], [110, 1, 1, "", "Resample"], [111, 1, 1, "", "SetEEGReference"], [112, 3, 1, "", "create_fixed_length_windows"], [113, 3, 1, "", "create_windows_from_events"], [114, 3, 1, "", "create_windows_from_target_channels"], [115, 3, 1, "", "exponential_moving_demean"], [116, 3, 1, "", "exponential_moving_standardize"], [117, 3, 1, "", "filterbank"], [118, 3, 1, "", "preprocess"]], "braindecode.preprocessing.Preprocessor": [[109, 2, 1, "", "apply"]], "braindecode.regressor": [[119, 1, 1, "", "EEGRegressor"]], "braindecode.regressor.EEGRegressor": [[119, 4, 1, "", "_criteria"], [119, 4, 1, "", "_modules"], [119, 4, 1, "", "_optimizers"], [119, 4, 1, "", "callbacks_"], [119, 4, 1, "", "criterion_"], [119, 4, 1, "", "cuda_dependent_attributes_"], [119, 2, 1, "", "fit"], [119, 2, 1, "", "get_iterator"], [119, 4, 1, "", "initialized_"], [119, 4, 1, "", "module_"], [119, 2, 1, "", "predict_proba"], [119, 2, 1, "", "predict_trials"], [119, 4, 1, "", "prefixes_"]], "braindecode.samplers": [[120, 1, 1, "", "BalancedSequenceSampler"], [121, 1, 1, "", "RecordingSampler"], [122, 1, 1, "", "RelativePositioningSampler"], [123, 1, 1, "", "SequenceSampler"]], "braindecode.samplers.BalancedSequenceSampler": [[120, 2, 1, "", "sample_class"]], "braindecode.samplers.RecordingSampler": [[121, 4, 1, "", "info"], [121, 4, 1, "", "n_recordings"], [121, 2, 1, "", "sample_recording"], [121, 2, 1, "", "sample_window"]], "braindecode.samplers.RelativePositioningSampler": [[122, 2, 1, "", "presample"]], "braindecode.samplers.SequenceSampler": [[123, 4, 1, "", "file_ids"], [123, 4, 1, "", "info"]], "braindecode.training": [[124, 1, 1, "", "CroppedLoss"], [125, 1, 1, "", "CroppedTimeSeriesEpochScoring"], [126, 1, 1, "", "CroppedTrialEpochScoring"], [127, 1, 1, "", "PostEpochTrainScoring"], [128, 1, 1, "", "TimeSeriesLoss"], [129, 3, 1, "", "mixup_criterion"], [130, 3, 1, "", "predict_trials"], [131, 3, 1, "", "trial_preds_from_window_preds"]], "braindecode.training.CroppedLoss": [[124, 2, 1, "", "forward"]], "braindecode.training.CroppedTimeSeriesEpochScoring": [[125, 2, 1, "", "on_epoch_end"]], "braindecode.training.CroppedTrialEpochScoring": [[126, 2, 1, "", "on_batch_end"], [126, 2, 1, "", "on_epoch_end"]], "braindecode.training.PostEpochTrainScoring": [[127, 2, 1, "", "on_epoch_end"]], "braindecode.training.TimeSeriesLoss": [[128, 2, 1, "", "forward"]], "braindecode.util": [[132, 3, 1, "", "set_random_seeds"]], "braindecode.visualization": [[133, 3, 1, "", "compute_amplitude_gradients"], [134, 3, 1, "", "plot_confusion_matrix"]]}, "objtypes": {"0": "py:module", "1": "py:class", "2": "py:method", "3": "py:function", "4": "py:attribute"}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "class", "Python class"], "2": ["py", "method", "Python method"], "3": ["py", "function", "Python function"], "4": ["py", "attribute", "Python attribute"]}, "titleterms": {"api": [0, 140], "refer": [0, 4, 5, 9, 10, 11, 26, 27, 28, 29, 30, 31, 135], "classifi": [0, 67], "regressor": [0, 119], "model": [0, 2, 3, 4, 5, 8, 9, 10, 11, 22, 24, 25, 26, 27, 28, 29, 30, 31, 32, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104], "train": [0, 1, 2, 3, 4, 5, 8, 9, 10, 11, 22, 24, 25, 26, 27, 28, 29, 30, 31, 32, 124, 125, 126, 127, 128, 129, 130, 131], "dataset": [0, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 17, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30, 31, 32, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80], "preprocess": [0, 2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 32, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118], "data": [0, 3, 4, 12, 15, 22, 24, 26, 27, 28, 29, 31], "util": [0, 29, 132], "sampler": [0, 5, 9, 10, 11, 120, 121, 122, 123], "augment": [0, 3, 4, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66], "visual": [0, 3, 5, 29, 133, 134], "advanc": [1, 24], "neural": [1, 24, 30, 31], "network": [1, 9, 11, 24, 30, 31], "strategi": [1, 24], "finger": [2, 8], "flexion": [2, 8], "crop": [2, 27, 105], "decod": [2, 8, 27, 28], "bcic": [2, 3, 4, 8, 27], "iv": [2, 3, 4, 8, 27], "4": [2, 8], "ecog": [2, 8], "load": [2, 3, 4, 5, 8, 9, 10, 11, 14, 15, 18, 21, 24, 26, 27, 28, 29, 30, 32], "prepar": [2, 8, 28], "split": [2, 3, 4, 5, 8, 9, 10, 11, 21, 27, 28, 29, 30, 32], "test": [2, 5, 8, 29, 31, 32, 139], "creat": [2, 3, 4, 5, 8, 9, 10, 11, 12, 22, 27, 28, 29, 30, 32], "cut": [2, 8, 12, 27, 32], "comput": [2, 6, 8, 12, 13, 23, 27, 28, 30, 32, 33], "window": [2, 3, 4, 5, 8, 9, 10, 11, 12, 22, 27, 28, 29, 30, 31, 32], "plot": [2, 4, 8, 9, 10, 11, 27, 28, 30], "result": [2, 4, 5, 8, 9, 10, 11, 27, 28, 30], "2a": [3, 4, 27], "thi": [3, 4, 5, 12, 21, 26, 27, 28, 29, 30, 32], "exampl": [3, 4, 5, 7, 12, 17, 18, 19, 20, 21, 24, 26, 27, 28, 29, 30, 32, 35, 37, 40, 41, 42, 50, 51, 53, 68, 70, 71, 73, 74, 75, 76, 78, 79, 80, 81, 84, 91, 96, 98, 99, 102, 103, 104, 109, 112, 113, 114, 116, 118, 121, 122, 123, 124, 125, 126, 128, 132, 134], "cover": [3, 4, 5, 12, 21, 26, 27, 28, 29, 30, 32], "extract": [3, 4, 5, 9, 10, 11, 28, 29, 30], "valid": [3, 4, 5, 8, 9, 10, 11, 28, 29, 30], "defin": [3, 4, 29, 31, 32], "transform": [3, 4, 32, 53], "manipul": 3, "one": 3, "session": 3, "an": [3, 4], "eegclassifi": [3, 4, 67], "desir": [3, 4], "manual": 3, "compos": [3, 40], "set": [3, 5, 28], "level": 3, "search": 4, "best": [4, 30], "list": 4, "analys": 4, "fit": 4, "self": 5, "supervis": 5, "learn": [5, 26, 30], "eeg": [5, 12, 22, 28], "rel": 5, "posit": 5, "raw": [5, 32], "record": [5, 12], "inspect": 5, "pretext": 5, "task": 5, "perform": 5, "us": [5, 9, 10, 11, 12, 35, 37, 40, 41, 42, 50, 51, 53, 68, 70, 71, 73, 74, 75, 76, 78, 79, 80, 81, 84, 91, 96, 98, 99, 102, 103, 104, 109, 112, 113, 114, 116, 118, 121, 122, 123, 124, 125, 126, 128, 132, 134], "represent": 5, "sleep": [5, 9, 10, 11], "stage": [5, 9, 10, 11], "conclus": 5, "time": [6, 13, 23, 33], "appli": [7, 24], "real": [7, 24], "world": [7, 24], "physionet": [9, 10, 11], "chambon2018": 9, "sequenc": [9, 10, 11], "eldele2021": 10, "u": 11, "process": 12, "big": 12, "resourc": 12, "tuh": [12, 22, 75], "corpu": [12, 22], "tuhmock": 12, "select": 12, "combin": 12, "step": 12, "benchmark": [14, 16], "eager": 14, "lazi": 14, "organ": [15, 24], "parallel": 16, "serial": 16, "custom": 17, "save": 18, "mne": [19, 26, 34], "moabb": 20, "By": 21, "descript": 21, "inform": 21, "row": 21, "index": 21, "observ": 21, "multipl": 22, "discret": 22, "target": 22, "templ": 22, "univers": 22, "hospit": 22, "explor": [22, 26], "dataload": 22, "basic": [24, 25, 28], "build": [24, 25], "simpl": [26, 29], "epoch": 26, "find": 26, "you": [26, 30], "want": 26, "braindecod": [26, 32, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 139], "onlin": 26, "document": 26, "examin": 26, "your": [26, 29, 32, 139], "own": 26, "scikit": [26, 30], "compat": 26, "paramet": 27, "confus": [27, 28], "matrix": [27, 28], "brain": 28, "how": [29, 32, 34, 135], "tune": [29, 30], "why": [29, 30, 32], "should": [29, 32], "i": [29, 32, 135, 139], "care": [29, 32], "about": [29, 32], "evalu": [29, 31, 32], "etc": [29, 32], "option": [29, 32], "1": [29, 32, 140], "let": 29, "": [29, 140], "first": 29, "function": [29, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66], "2": [29, 32], "val": 29, "second": 29, "3": 29, "k": 29, "fold": 29, "cross": 29, "third": 29, "hyperparamet": [29, 30], "do": [30, 135], "need": 30, "get": [30, 135], "convolut": 31, "regress": 31, "fake": 31, "gener": 31, "cnn": 31, "choos": 31, "between": 31, "gpu": 31, "cpu": 31, "processor": 31, "pytorch": 32, "structur": 32, "offlin": 32, "pure": 32, "loop": 32, "lightn": 32, "cite": [34, 135], "other": 34, "algorithm": 34, "augmenteddataload": 35, "bandstopfilt": 36, "channelsdropout": 37, "channelsshuffl": 38, "channelssymmetri": 39, "ftsurrog": 41, "frequencyshift": 42, "gaussiannois": 43, "identitytransform": 44, "mixup": [45, 62], "sensorsrot": 46, "sensorsxrot": 47, "sensorsyrot": 48, "sensorszrot": 49, "signflip": 50, "smoothtimemask": 51, "timerevers": 52, "bandstop_filt": 54, "channels_dropout": 55, "channels_permut": 56, "channels_shuffl": 57, "frequency_shift": 58, "ft_surrog": 59, "gaussian_nois": 60, "ident": 61, "sensors_rot": 63, "sign_flip": 64, "smooth_time_mask": 65, "time_revers": 66, "bcicompetitionivdataset4": 68, "bnci2014001": 69, "summari": [69, 72], "baseconcatdataset": 70, "basedataset": 71, "hgd": 72, "moabbdataset": 73, "sleepphysionet": 74, "tuhabnorm": 76, "windowsdataset": 77, "create_from_x_i": 78, "create_from_mne_epoch": 79, "create_from_mne_raw": 80, "datautil": [81, 82], "load_concat_dataset": 81, "save_concat_dataset": 82, "atcnet": 83, "deep4net": 84, "deepsleepnet": 85, "eegconform": 86, "eegitnet": 87, "eegincept": 88, "eeginceptionerp": 89, "eeginceptionmi": 90, "eegmodulemixin": 91, "eegnetv1": 92, "eegnetv4": 93, "eegresnet": 94, "hybridnet": 95, "shallowfbcspnet": 96, "sleepstagerblanco2020": 97, "sleepstagerchambon2018": 98, "sleepstagereldele2021": 99, "tcn": 100, "tidnet": 101, "timedistribut": 102, "usleep": 103, "get_output_shap": 104, "dropchannel": 106, "filter": 107, "pick": 108, "preprocessor": 109, "resampl": 110, "seteegrefer": 111, "create_fixed_length_window": 112, "create_windows_from_ev": 113, "create_windows_from_target_channel": 114, "exponential_moving_demean": 115, "exponential_moving_standard": 116, "filterbank": 117, "eegregressor": 119, "balancedsequencesampl": 120, "recordingsampl": 121, "relativepositioningsampl": 122, "sequencesampl": 123, "croppedloss": 124, "croppedtimeseriesepochscor": 125, "croppedtrialepochscor": 126, "postepochtrainscor": 127, "timeseriesloss": 128, "mixup_criterion": 129, "predict_tri": 130, "trial_preds_from_window_pr": 131, "set_random_se": 132, "compute_amplitude_gradi": 133, "plot_confusion_matrix": 134, "frequent": 135, "ask": 135, "question": 135, "faq": 135, "help": 135, "can": 135, "t": 135, "python": 135, "work": [135, 139], "still": 135, "think": 135, "found": 135, "bug": [135, 140], "what": [135, 140], "homepag": 136, "instal": [137, 138, 139], "from": [138, 139], "pypi": 138, "sourc": 139, "clone": 139, "repositori": 139, "github": 139, "new": 140, "current": 140, "0": 140, "9": 140, "dev0": 140, "enhanc": 140, "chang": 140, "8": 140, "11": 140, "2022": 140, "7": 140, "10": 140, "version": 140, "6": 140, "2021": 140, "12": 140, "06": 140, "5": 140, "07": 140, "14": 140, "author": 140}, "envversion": {"sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.todo": 2, "sphinx.ext.intersphinx": 1, "sphinx": 60}, "alltitles": {"API Reference": [[0, "api-reference"]], "Classifier": [[0, "classifier"]], "Regressor": [[0, "regressor"]], "Models": [[0, "models"]], "Training": [[0, "training"], [2, "training"], [5, "training"], [8, "training"], [9, "training"], [10, "training"], [11, "training"], [27, "training"], [30, "training"]], "Datasets": [[0, "datasets"]], "Preprocessing": [[0, "preprocessing"], [2, "preprocessing"], [3, "preprocessing"], [4, "preprocessing"], [5, "preprocessing"], [8, "preprocessing"], [9, "preprocessing"], [10, "preprocessing"], [11, "preprocessing"], [12, "preprocessing"], [28, "preprocessing"], [30, "preprocessing"]], "Data Utils": [[0, "data-utils"]], "Samplers": [[0, "samplers"]], "Augmentation": [[0, "augmentation"]], "Utils": [[0, "utils"]], "Visualization": [[0, "visualization"]], "Advanced neural network training strategies": [[1, "advanced-neural-network-training-strategies"], [24, "advanced-neural-network-training-strategies"]], "Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset": [[2, "fingers-flexion-cropped-decoding-on-bcic-iv-4-ecog-dataset"]], "Loading and preparing the dataset": [[2, "loading-and-preparing-the-dataset"], [8, "loading-and-preparing-the-dataset"]], "Loading": [[2, "loading"], [3, "loading"], [4, "loading"], [8, "loading"], [9, "loading"], [10, "loading"], [11, "loading"], [30, "loading"]], "Split dataset into train and test": [[2, "split-dataset-into-train-and-test"], [29, "split-dataset-into-train-and-test"], [32, "split-dataset-into-train-and-test"]], "Create model": [[2, "create-model"], [3, "create-model"], [4, "create-model"], [8, "create-model"], [9, "create-model"], [10, "create-model"], [11, "create-model"], [29, "create-model"], [30, "create-model"]], "Cut Compute Windows": [[2, "cut-compute-windows"], [8, "cut-compute-windows"], [12, "cut-compute-windows"], [32, "cut-compute-windows"]], "Plot Results": [[2, "plot-results"], [8, "plot-results"], [27, "plot-results"]], "Data Augmentation on BCIC IV 2a Dataset": [[3, "data-augmentation-on-bcic-iv-2a-dataset"]], "This example covers:": [[3, "this-example-covers"], [4, "this-example-covers"], [5, "this-example-covers"], [12, "this-example-covers"], [21, "this-example-covers"], [26, "this-example-covers"], [27, "this-example-covers"], [28, "this-example-covers"], [29, "this-example-covers"], [30, "this-example-covers"], [32, "this-example-covers"]], "Loading and preprocessing the dataset": [[3, "loading-and-preprocessing-the-dataset"], [4, "loading-and-preprocessing-the-dataset"], [5, "loading-and-preprocessing-the-dataset"], [9, "loading-and-preprocessing-the-dataset"], [10, "loading-and-preprocessing-the-dataset"], [11, "loading-and-preprocessing-the-dataset"], [27, "loading-and-preprocessing-the-dataset"], [30, "loading-and-preprocessing-the-dataset"]], "Extracting windows": [[3, "extracting-windows"], [4, "extracting-windows"], [5, "extracting-windows"]], "Split dataset into train and valid": [[3, "split-dataset-into-train-and-valid"], [4, "split-dataset-into-train-and-valid"], [9, "split-dataset-into-train-and-valid"], [10, "split-dataset-into-train-and-valid"], [11, "split-dataset-into-train-and-valid"], [30, "split-dataset-into-train-and-valid"]], "Defining a Transform": [[3, "defining-a-transform"]], "Manipulating one session and visualizing the transformed data": [[3, "manipulating-one-session-and-visualizing-the-transformed-data"]], "Training a model with data augmentation": [[3, "training-a-model-with-data-augmentation"], [4, "training-a-model-with-data-augmentation"]], "Create an EEGClassifier with the desired augmentation": [[3, "create-an-eegclassifier-with-the-desired-augmentation"], [4, "create-an-eegclassifier-with-the-desired-augmentation"]], "Manually composing Transforms": [[3, "manually-composing-transforms"]], "Setting the data augmentation at the Dataset level": [[3, "setting-the-data-augmentation-at-the-dataset-level"]], "Searching the best data augmentation on BCIC IV 2a Dataset": [[4, "searching-the-best-data-augmentation-on-bcic-iv-2a-dataset"]], "Data Augmentation": [[4, null]], "Defining a list of transforms": [[4, "defining-a-list-of-transforms"]], "Analysing the best fit": [[4, "analysing-the-best-fit"]], "Plot results": [[4, "plot-results"], [9, "plot-results"], [10, "plot-results"], [11, "plot-results"]], "References": [[4, "references"], [5, "references"], [9, "references"], [10, "references"], [11, "references"], [26, "references"], [27, "references"], [28, "references"], [29, "references"], [30, "references"], [31, "references"], [135, "references"]], "Self-supervised learning on EEG with relative positioning": [[5, "self-supervised-learning-on-eeg-with-relative-positioning"]], "Self-supervised learning": [[5, null]], "Loading the raw recordings": [[5, "loading-the-raw-recordings"]], "Preprocessing windows": [[5, "preprocessing-windows"]], "Splitting dataset into train, valid and test sets": [[5, "splitting-dataset-into-train-valid-and-test-sets"]], "Creating samplers": [[5, "creating-samplers"]], "Creating the model": [[5, "creating-the-model"]], "Visualizing the results": [[5, "visualizing-the-results"]], "Inspecting pretext task performance": [[5, "inspecting-pretext-task-performance"]], "Using the learned representation for sleep staging": [[5, "using-the-learned-representation-for-sleep-staging"]], "Conclusion": [[5, "conclusion"]], "Computation times": [[6, "computation-times"], [13, "computation-times"], [23, "computation-times"], [33, "computation-times"]], "Applied examples on real-world datasets": [[7, "applied-examples-on-real-world-datasets"], [24, "applied-examples-on-real-world-datasets"]], "Fingers flexion decoding on BCIC IV 4 ECoG Dataset": [[8, "fingers-flexion-decoding-on-bcic-iv-4-ecog-dataset"]], "Split dataset into train, valid, and test": [[8, "split-dataset-into-train-valid-and-test"]], "Sleep staging on the Sleep Physionet dataset using Chambon2018 network": [[9, "sleep-staging-on-the-sleep-physionet-dataset-using-chambon2018-network"]], "Extract windows": [[9, "extract-windows"], [10, "extract-windows"], [11, "extract-windows"]], "Window preprocessing": [[9, "window-preprocessing"], [10, "window-preprocessing"]], "Create sequence samplers": [[9, "create-sequence-samplers"], [10, "create-sequence-samplers"], [11, "create-sequence-samplers"]], "Sleep staging on the Sleep Physionet dataset using Eldele2021": [[10, "sleep-staging-on-the-sleep-physionet-dataset-using-eldele2021"]], "Sleep staging on the Sleep Physionet dataset using U-Sleep network": [[11, "sleep-staging-on-the-sleep-physionet-dataset-using-u-sleep-network"]], "Process a big data EEG resource (TUH EEG Corpus)": [[12, "process-a-big-data-eeg-resource-tuh-eeg-corpus"]], "Creating the dataset using TUHMock": [[12, "creating-the-dataset-using-tuhmock"]], "Selecting recordings": [[12, "selecting-recordings"]], "Combining preprocessing steps": [[12, "combining-preprocessing-steps"]], "Benchmarking eager and lazy loading": [[14, "benchmarking-eager-and-lazy-loading"]], "Loading and organizing data": [[15, "loading-and-organizing-data"], [24, "loading-and-organizing-data"]], "Benchmarking preprocessing with parallelization and serialization": [[16, "benchmarking-preprocessing-with-parallelization-and-serialization"]], "Custom Dataset Example": [[17, "custom-dataset-example"]], "Load and save dataset example": [[18, "load-and-save-dataset-example"]], "MNE Dataset Example": [[19, "mne-dataset-example"]], "MOABB Dataset Example": [[20, "moabb-dataset-example"]], "Split Dataset Example": [[21, "split-dataset-example"]], "Loading the dataset": [[21, "loading-the-dataset"], [28, "loading-the-dataset"]], "Splitting": [[21, "splitting"]], "By description information": [[21, "by-description-information"]], "By row index": [[21, "by-row-index"]], "Observation": [[21, "observation"]], "Multiple discrete targets with the TUH EEG Corpus": [[22, "multiple-discrete-targets-with-the-tuh-eeg-corpus"]], "Creating Temple University Hospital (TUH) EEG Corpus Dataset": [[22, "creating-temple-university-hospital-tuh-eeg-corpus-dataset"]], "Exploring Data": [[22, "exploring-data"]], "Creating Windows": [[22, "creating-windows"]], "Exploring Windows": [[22, "exploring-windows"]], "DataLoader for Model Training": [[22, "dataloader-for-model-training"]], "Exploring DataLoader": [[22, "exploring-dataloader"]], "Examples": [[24, "examples"]], "Basic model building and training": [[24, "basic-model-building-and-training"], [25, "basic-model-building-and-training"]], "Simple training on MNE epochs": [[26, "simple-training-on-mne-epochs"]], "Finding the model you want": [[26, "finding-the-model-you-want"]], "Exploring the braindecode online documentation": [[26, "exploring-the-braindecode-online-documentation"]], "Examining the model": [[26, "examining-the-model"]], "Loading your own data with MNE": [[26, "loading-your-own-data-with-mne"]], "Training your model (scikit-learn compatible)": [[26, "training-your-model-scikit-learn-compatible"]], "Cropped Decoding on BCIC IV 2a Dataset": [[27, "cropped-decoding-on-bcic-iv-2a-dataset"]], "Create model and compute windowing parameters": [[27, "create-model-and-compute-windowing-parameters"]], "Cut the data into windows": [[27, "cut-the-data-into-windows"]], "Split the dataset": [[27, "split-the-dataset"]], "Plot Confusion Matrix": [[27, "plot-confusion-matrix"]], "Basic Brain Decoding on EEG Data": [[28, "basic-brain-decoding-on-eeg-data"]], "Loading and preparing the data": [[28, "loading-and-preparing-the-data"]], "Extracting Compute Windows": [[28, "extracting-compute-windows"]], "Splitting the dataset into training and validation sets": [[28, "splitting-the-dataset-into-training-and-validation-sets"]], "Creating a model": [[28, "creating-a-model"]], "Model Training": [[28, "model-training"]], "Plotting Results": [[28, "plotting-results"]], "Plotting a  Confusion Matrix": [[28, "plotting-a-confusion-matrix"]], "How to train, test and tune your model?": [[29, "how-to-train-test-and-tune-your-model"]], "Why should I care about model evaluation?": [[29, "why-should-i-care-about-model-evaluation"], [32, "why-should-i-care-about-model-evaluation"]], "Loading and preprocessing of data, defining a model, etc.": [[29, "loading-and-preprocessing-of-data-defining-a-model-etc"]], "Loading data": [[29, "loading-data"]], "Preprocessing data": [[29, "preprocessing-data"]], "Extraction of the Windows": [[29, "extraction-of-the-windows"], [30, "extraction-of-the-windows"]], "How to train and evaluate your model": [[29, "how-to-train-and-evaluate-your-model"], [32, "how-to-train-and-evaluate-your-model"]], "Option 1: Simple Train-Test Split": [[29, "option-1-simple-train-test-split"]], "Let\u2019s visualize the first option with a util function.": [[29, "let-s-visualize-the-first-option-with-a-util-function"]], "Option 2: Train-Val-Test Split": [[29, "option-2-train-val-test-split"]], "Let\u2019s visualize the second option with a util function.": [[29, "let-s-visualize-the-second-option-with-a-util-function"]], "Option 3: k-Fold Cross Validation": [[29, "option-3-k-fold-cross-validation"]], "Let\u2019s visualize the third option with a util function.": [[29, "let-s-visualize-the-third-option-with-a-util-function"]], "How to tune your hyperparameters": [[29, "how-to-tune-your-hyperparameters"]], "Option 1: Train-Val-Test Split": [[29, "option-1-train-val-test-split"]], "Option 2: k-Fold Cross Validation": [[29, "option-2-k-fold-cross-validation"]], "Hyperparameter tuning with scikit-learn": [[30, "hyperparameter-tuning-with-scikit-learn"]], "Why do you need to tune the neural networks model?": [[30, null]], "Extraction of the Compute Windows": [[30, "extraction-of-the-compute-windows"]], "Plotting the results": [[30, "plotting-the-results"]], "Get the best hyperparameters": [[30, "get-the-best-hyperparameters"]], "Convolutional neural network regression model on fake data.": [[31, "convolutional-neural-network-regression-model-on-fake-data"]], "Fake regression data": [[31, "fake-regression-data"]], "Generating fake regression dataset": [[31, "generating-fake-regression-dataset"]], "Defining a CNN regression model": [[31, "defining-a-cnn-regression-model"]], "Choosing between GPU and CPU processors": [[31, "choosing-between-gpu-and-cpu-processors"]], "Data windowing": [[31, "data-windowing"]], "Model training": [[31, "model-training"]], "Model evaluation": [[31, "model-evaluation"]], "Model testing": [[31, "model-testing"]], "Training a Braindecode model in PyTorch": [[32, "training-a-braindecode-model-in-pytorch"]], "Loading, preprocessing, defining a model, etc.": [[32, "loading-preprocessing-defining-a-model-etc"]], "Loading the Dataset Structure": [[32, "loading-the-dataset-structure"]], "Preprocessing, the offline transformation of the raw dataset": [[32, "preprocessing-the-offline-transformation-of-the-raw-dataset"]], "Create Pytorch model": [[32, "create-pytorch-model"]], "Option 1: Pure PyTorch training loop": [[32, "option-1-pure-pytorch-training-loop"]], "Option 2: Train it with PyTorch Lightning": [[32, "option-2-train-it-with-pytorch-lightning"]], "How to cite Braindecode": [[34, "how-to-cite-braindecode"]], "Citing the Braindecode": [[34, "citing-the-braindecode"]], "Citing the MNE": [[34, "citing-the-mne"]], "Citing other algorithms": [[34, "citing-other-algorithms"]], "braindecode.augmentation.AugmentedDataLoader": [[35, "braindecode-augmentation-augmenteddataloader"]], "Examples using braindecode.augmentation.AugmentedDataLoader": [[35, "examples-using-braindecode-augmentation-augmenteddataloader"]], "braindecode.augmentation.BandstopFilter": [[36, "braindecode-augmentation-bandstopfilter"]], "braindecode.augmentation.ChannelsDropout": [[37, "braindecode-augmentation-channelsdropout"]], "Examples using braindecode.augmentation.ChannelsDropout": [[37, "examples-using-braindecode-augmentation-channelsdropout"]], "braindecode.augmentation.ChannelsShuffle": [[38, "braindecode-augmentation-channelsshuffle"]], "braindecode.augmentation.ChannelsSymmetry": [[39, "braindecode-augmentation-channelssymmetry"]], "braindecode.augmentation.Compose": [[40, "braindecode-augmentation-compose"]], "Examples using braindecode.augmentation.Compose": [[40, "examples-using-braindecode-augmentation-compose"]], "braindecode.augmentation.FTSurrogate": [[41, "braindecode-augmentation-ftsurrogate"]], "Examples using braindecode.augmentation.FTSurrogate": [[41, "examples-using-braindecode-augmentation-ftsurrogate"]], "braindecode.augmentation.FrequencyShift": [[42, "braindecode-augmentation-frequencyshift"]], "Examples using braindecode.augmentation.FrequencyShift": [[42, "examples-using-braindecode-augmentation-frequencyshift"]], "braindecode.augmentation.GaussianNoise": [[43, "braindecode-augmentation-gaussiannoise"]], "braindecode.augmentation.IdentityTransform": [[44, "braindecode-augmentation-identitytransform"]], "braindecode.augmentation.Mixup": [[45, "braindecode-augmentation-mixup"]], "braindecode.augmentation.SensorsRotation": [[46, "braindecode-augmentation-sensorsrotation"]], "braindecode.augmentation.SensorsXRotation": [[47, "braindecode-augmentation-sensorsxrotation"]], "braindecode.augmentation.SensorsYRotation": [[48, "braindecode-augmentation-sensorsyrotation"]], "braindecode.augmentation.SensorsZRotation": [[49, "braindecode-augmentation-sensorszrotation"]], "braindecode.augmentation.SignFlip": [[50, "braindecode-augmentation-signflip"]], "Examples using braindecode.augmentation.SignFlip": [[50, "examples-using-braindecode-augmentation-signflip"]], "braindecode.augmentation.SmoothTimeMask": [[51, "braindecode-augmentation-smoothtimemask"]], "Examples using braindecode.augmentation.SmoothTimeMask": [[51, "examples-using-braindecode-augmentation-smoothtimemask"]], "braindecode.augmentation.TimeReverse": [[52, "braindecode-augmentation-timereverse"]], "braindecode.augmentation.Transform": [[53, "braindecode-augmentation-transform"]], "Examples using braindecode.augmentation.Transform": [[53, "examples-using-braindecode-augmentation-transform"]], "braindecode.augmentation.functional.bandstop_filter": [[54, "braindecode-augmentation-functional-bandstop-filter"]], "braindecode.augmentation.functional.channels_dropout": [[55, "braindecode-augmentation-functional-channels-dropout"]], "braindecode.augmentation.functional.channels_permute": [[56, "braindecode-augmentation-functional-channels-permute"]], "braindecode.augmentation.functional.channels_shuffle": [[57, "braindecode-augmentation-functional-channels-shuffle"]], "braindecode.augmentation.functional.frequency_shift": [[58, "braindecode-augmentation-functional-frequency-shift"]], "braindecode.augmentation.functional.ft_surrogate": [[59, "braindecode-augmentation-functional-ft-surrogate"]], "braindecode.augmentation.functional.gaussian_noise": [[60, "braindecode-augmentation-functional-gaussian-noise"]], "braindecode.augmentation.functional.identity": [[61, "braindecode-augmentation-functional-identity"]], "braindecode.augmentation.functional.mixup": [[62, "braindecode-augmentation-functional-mixup"]], "braindecode.augmentation.functional.sensors_rotation": [[63, "braindecode-augmentation-functional-sensors-rotation"]], "braindecode.augmentation.functional.sign_flip": [[64, "braindecode-augmentation-functional-sign-flip"]], "braindecode.augmentation.functional.smooth_time_mask": [[65, "braindecode-augmentation-functional-smooth-time-mask"]], "braindecode.augmentation.functional.time_reverse": [[66, "braindecode-augmentation-functional-time-reverse"]], "braindecode.classifier.EEGClassifier": [[67, "braindecode-classifier-eegclassifier"]], "braindecode.datasets.BCICompetitionIVDataset4": [[68, "braindecode-datasets-bcicompetitionivdataset4"]], "Examples using braindecode.datasets.BCICompetitionIVDataset4": [[68, "examples-using-braindecode-datasets-bcicompetitionivdataset4"]], "braindecode.datasets.BNCI2014001": [[69, "braindecode-datasets-bnci2014001"]], "Dataset summary": [[69, null], [72, null]], "braindecode.datasets.BaseConcatDataset": [[70, "braindecode-datasets-baseconcatdataset"]], "Examples using braindecode.datasets.BaseConcatDataset": [[70, "examples-using-braindecode-datasets-baseconcatdataset"]], "braindecode.datasets.BaseDataset": [[71, "braindecode-datasets-basedataset"]], "Examples using braindecode.datasets.BaseDataset": [[71, "examples-using-braindecode-datasets-basedataset"]], "braindecode.datasets.HGD": [[72, "braindecode-datasets-hgd"]], "braindecode.datasets.MOABBDataset": [[73, "braindecode-datasets-moabbdataset"]], "Examples using braindecode.datasets.MOABBDataset": [[73, "examples-using-braindecode-datasets-moabbdataset"]], "braindecode.datasets.SleepPhysionet": [[74, "braindecode-datasets-sleepphysionet"]], "Examples using braindecode.datasets.SleepPhysionet": [[74, "examples-using-braindecode-datasets-sleepphysionet"]], "braindecode.datasets.TUH": [[75, "braindecode-datasets-tuh"]], "Examples using braindecode.datasets.TUH": [[75, "examples-using-braindecode-datasets-tuh"]], "braindecode.datasets.TUHAbnormal": [[76, "braindecode-datasets-tuhabnormal"]], "Examples using braindecode.datasets.TUHAbnormal": [[76, "examples-using-braindecode-datasets-tuhabnormal"]], "braindecode.datasets.WindowsDataset": [[77, "braindecode-datasets-windowsdataset"]], "braindecode.datasets.create_from_X_y": [[78, "braindecode-datasets-create-from-x-y"]], "Examples using braindecode.datasets.create_from_X_y": [[78, "examples-using-braindecode-datasets-create-from-x-y"]], "braindecode.datasets.create_from_mne_epochs": [[79, "braindecode-datasets-create-from-mne-epochs"]], "Examples using braindecode.datasets.create_from_mne_epochs": [[79, "examples-using-braindecode-datasets-create-from-mne-epochs"]], "braindecode.datasets.create_from_mne_raw": [[80, "braindecode-datasets-create-from-mne-raw"]], "Examples using braindecode.datasets.create_from_mne_raw": [[80, "examples-using-braindecode-datasets-create-from-mne-raw"]], "braindecode.datautil.load_concat_dataset": [[81, "braindecode-datautil-load-concat-dataset"]], "Examples using braindecode.datautil.load_concat_dataset": [[81, "examples-using-braindecode-datautil-load-concat-dataset"]], "braindecode.datautil.save_concat_dataset": [[82, "braindecode-datautil-save-concat-dataset"]], "braindecode.models.ATCNet": [[83, "braindecode-models-atcnet"]], "braindecode.models.Deep4Net": [[84, "braindecode-models-deep4net"]], "Examples using braindecode.models.Deep4Net": [[84, "examples-using-braindecode-models-deep4net"]], "braindecode.models.DeepSleepNet": [[85, "braindecode-models-deepsleepnet"]], "braindecode.models.EEGConformer": [[86, "braindecode-models-eegconformer"]], "braindecode.models.EEGITNet": [[87, "braindecode-models-eegitnet"]], "braindecode.models.EEGInception": [[88, "braindecode-models-eeginception"]], "braindecode.models.EEGInceptionERP": [[89, "braindecode-models-eeginceptionerp"]], "braindecode.models.EEGInceptionMI": [[90, "braindecode-models-eeginceptionmi"]], "braindecode.models.EEGModuleMixin": [[91, "braindecode-models-eegmodulemixin"]], "Examples using braindecode.models.EEGModuleMixin": [[91, "examples-using-braindecode-models-eegmodulemixin"]], "braindecode.models.EEGNetv1": [[92, "braindecode-models-eegnetv1"]], "braindecode.models.EEGNetv4": [[93, "braindecode-models-eegnetv4"]], "braindecode.models.EEGResNet": [[94, "braindecode-models-eegresnet"]], "braindecode.models.HybridNet": [[95, "braindecode-models-hybridnet"]], "braindecode.models.ShallowFBCSPNet": [[96, "braindecode-models-shallowfbcspnet"]], "Examples using braindecode.models.ShallowFBCSPNet": [[96, "examples-using-braindecode-models-shallowfbcspnet"]], "braindecode.models.SleepStagerBlanco2020": [[97, "braindecode-models-sleepstagerblanco2020"]], "braindecode.models.SleepStagerChambon2018": [[98, "braindecode-models-sleepstagerchambon2018"]], "Examples using braindecode.models.SleepStagerChambon2018": [[98, "examples-using-braindecode-models-sleepstagerchambon2018"]], "braindecode.models.SleepStagerEldele2021": [[99, "braindecode-models-sleepstagereldele2021"]], "Examples using braindecode.models.SleepStagerEldele2021": [[99, "examples-using-braindecode-models-sleepstagereldele2021"]], "braindecode.models.TCN": [[100, "braindecode-models-tcn"]], "braindecode.models.TIDNet": [[101, "braindecode-models-tidnet"]], "braindecode.models.TimeDistributed": [[102, "braindecode-models-timedistributed"]], "Examples using braindecode.models.TimeDistributed": [[102, "examples-using-braindecode-models-timedistributed"]], "braindecode.models.USleep": [[103, "braindecode-models-usleep"]], "Examples using braindecode.models.USleep": [[103, "examples-using-braindecode-models-usleep"]], "braindecode.models.get_output_shape": [[104, "braindecode-models-get-output-shape"]], "Examples using braindecode.models.get_output_shape": [[104, "examples-using-braindecode-models-get-output-shape"]], "braindecode.preprocessing.Crop": [[105, "braindecode-preprocessing-crop"]], "braindecode.preprocessing.DropChannels": [[106, "braindecode-preprocessing-dropchannels"]], "braindecode.preprocessing.Filter": [[107, "braindecode-preprocessing-filter"]], "braindecode.preprocessing.Pick": [[108, "braindecode-preprocessing-pick"]], "braindecode.preprocessing.Preprocessor": [[109, "braindecode-preprocessing-preprocessor"]], "Examples using braindecode.preprocessing.Preprocessor": [[109, "examples-using-braindecode-preprocessing-preprocessor"]], "braindecode.preprocessing.Resample": [[110, "braindecode-preprocessing-resample"]], "braindecode.preprocessing.SetEEGReference": [[111, "braindecode-preprocessing-seteegreference"]], "braindecode.preprocessing.create_fixed_length_windows": [[112, "braindecode-preprocessing-create-fixed-length-windows"]], "Examples using braindecode.preprocessing.create_fixed_length_windows": [[112, "examples-using-braindecode-preprocessing-create-fixed-length-windows"]], "braindecode.preprocessing.create_windows_from_events": [[113, "braindecode-preprocessing-create-windows-from-events"]], "Examples using braindecode.preprocessing.create_windows_from_events": [[113, "examples-using-braindecode-preprocessing-create-windows-from-events"]], "braindecode.preprocessing.create_windows_from_target_channels": [[114, "braindecode-preprocessing-create-windows-from-target-channels"]], "Examples using braindecode.preprocessing.create_windows_from_target_channels": [[114, "examples-using-braindecode-preprocessing-create-windows-from-target-channels"]], "braindecode.preprocessing.exponential_moving_demean": [[115, "braindecode-preprocessing-exponential-moving-demean"]], "braindecode.preprocessing.exponential_moving_standardize": [[116, "braindecode-preprocessing-exponential-moving-standardize"]], "Examples using braindecode.preprocessing.exponential_moving_standardize": [[116, "examples-using-braindecode-preprocessing-exponential-moving-standardize"]], "braindecode.preprocessing.filterbank": [[117, "braindecode-preprocessing-filterbank"]], "braindecode.preprocessing.preprocess": [[118, "braindecode-preprocessing-preprocess"]], "Examples using braindecode.preprocessing.preprocess": [[118, "examples-using-braindecode-preprocessing-preprocess"]], "braindecode.regressor.EEGRegressor": [[119, "braindecode-regressor-eegregressor"]], "braindecode.samplers.BalancedSequenceSampler": [[120, "braindecode-samplers-balancedsequencesampler"]], "braindecode.samplers.RecordingSampler": [[121, "braindecode-samplers-recordingsampler"]], "Examples using braindecode.samplers.RecordingSampler": [[121, "examples-using-braindecode-samplers-recordingsampler"]], "braindecode.samplers.RelativePositioningSampler": [[122, "braindecode-samplers-relativepositioningsampler"]], "Examples using braindecode.samplers.RelativePositioningSampler": [[122, "examples-using-braindecode-samplers-relativepositioningsampler"]], "braindecode.samplers.SequenceSampler": [[123, "braindecode-samplers-sequencesampler"]], "Examples using braindecode.samplers.SequenceSampler": [[123, "examples-using-braindecode-samplers-sequencesampler"]], "braindecode.training.CroppedLoss": [[124, "braindecode-training-croppedloss"]], "Examples using braindecode.training.CroppedLoss": [[124, "examples-using-braindecode-training-croppedloss"]], "braindecode.training.CroppedTimeSeriesEpochScoring": [[125, "braindecode-training-croppedtimeseriesepochscoring"]], "Examples using braindecode.training.CroppedTimeSeriesEpochScoring": [[125, "examples-using-braindecode-training-croppedtimeseriesepochscoring"]], "braindecode.training.CroppedTrialEpochScoring": [[126, "braindecode-training-croppedtrialepochscoring"]], "Examples using braindecode.training.CroppedTrialEpochScoring": [[126, "examples-using-braindecode-training-croppedtrialepochscoring"]], "braindecode.training.PostEpochTrainScoring": [[127, "braindecode-training-postepochtrainscoring"]], "braindecode.training.TimeSeriesLoss": [[128, "braindecode-training-timeseriesloss"]], "Examples using braindecode.training.TimeSeriesLoss": [[128, "examples-using-braindecode-training-timeseriesloss"]], "braindecode.training.mixup_criterion": [[129, "braindecode-training-mixup-criterion"]], "braindecode.training.predict_trials": [[130, "braindecode-training-predict-trials"]], "braindecode.training.trial_preds_from_window_preds": [[131, "braindecode-training-trial-preds-from-window-preds"]], "braindecode.util.set_random_seeds": [[132, "braindecode-util-set-random-seeds"]], "Examples using braindecode.util.set_random_seeds": [[132, "examples-using-braindecode-util-set-random-seeds"]], "braindecode.visualization.compute_amplitude_gradients": [[133, "braindecode-visualization-compute-amplitude-gradients"]], "braindecode.visualization.plot_confusion_matrix": [[134, "braindecode-visualization-plot-confusion-matrix"]], "Examples using braindecode.visualization.plot_confusion_matrix": [[134, "examples-using-braindecode-visualization-plot-confusion-matrix"]], "Frequently Asked Questions (FAQ)": [[135, "frequently-asked-questions-faq"]], "How do I cite Braindecode?": [[135, "how-do-i-cite-braindecode"]], "Help! I can\u2019t get Python and Braindecode working!": [[135, "help-i-can-t-get-python-and-braindecode-working"]], "I still can\u2019t get it to work!": [[135, "i-still-can-t-get-it-to-work"]], "I think I found a bug, what do I do?": [[135, "i-think-i-found-a-bug-what-do-i-do"]], "Braindecode Homepage": [[136, "braindecode-homepage"]], "Installation": [[137, "installation"]], "Installing from PyPI": [[138, "installing-from-pypi"]], "Installing from sources": [[139, "installing-from-sources"]], "Clone the repository from GitHub": [[139, "clone-the-repository-from-github"]], "Installing Braindecode from the source": [[139, "installing-braindecode-from-the-source"]], "Testing if your installation is working": [[139, "testing-if-your-installation-is-working"]], "What\u2019s new": [[140, "what-s-new"]], "Current 0.9 (dev0)": [[140, "current-0-9-dev0"]], "Enhancements": [[140, "enhancements"], [140, "id1"], [140, "id8"], [140, "id11"], [140, "id14"]], "Bugs": [[140, "bugs"], [140, "id6"], [140, "id9"], [140, "id12"], [140, "id15"]], "API changes": [[140, "api-changes"], [140, "id7"], [140, "id10"], [140, "id13"], [140, "id16"]], "Current 0.8 (11-2022)": [[140, "current-0-8-11-2022"]], "Current 0.7 (10-2022)": [[140, "current-0-7-10-2022"]], "Version 0.6 (2021-12-06)": [[140, "version-0-6-2021-12-06"]], "Version 0.5.1 (2021-07-14)": [[140, "version-0-5-1-2021-07-14"]], "Authors": [[140, "authors"]]}, "indexentries": {"braindecode": [[0, "module-braindecode"]], "module": [[0, "module-braindecode"]], "augmenteddataloader (class in braindecode.augmentation)": [[35, "braindecode.augmentation.AugmentedDataLoader"]], "bandstopfilter (class in braindecode.augmentation)": [[36, "braindecode.augmentation.BandstopFilter"]], "get_augmentation_params() (braindecode.augmentation.bandstopfilter method)": [[36, "braindecode.augmentation.BandstopFilter.get_augmentation_params"]], "operation() (braindecode.augmentation.bandstopfilter static method)": [[36, "braindecode.augmentation.BandstopFilter.operation"]], "channelsdropout (class in braindecode.augmentation)": [[37, "braindecode.augmentation.ChannelsDropout"]], "get_augmentation_params() (braindecode.augmentation.channelsdropout method)": [[37, "braindecode.augmentation.ChannelsDropout.get_augmentation_params"]], "operation() (braindecode.augmentation.channelsdropout static method)": [[37, "braindecode.augmentation.ChannelsDropout.operation"]], "channelsshuffle (class in braindecode.augmentation)": [[38, "braindecode.augmentation.ChannelsShuffle"]], "get_augmentation_params() (braindecode.augmentation.channelsshuffle method)": [[38, "braindecode.augmentation.ChannelsShuffle.get_augmentation_params"]], "operation() (braindecode.augmentation.channelsshuffle static method)": [[38, "braindecode.augmentation.ChannelsShuffle.operation"]], "channelssymmetry (class in braindecode.augmentation)": [[39, "braindecode.augmentation.ChannelsSymmetry"]], "get_augmentation_params() (braindecode.augmentation.channelssymmetry method)": [[39, "braindecode.augmentation.ChannelsSymmetry.get_augmentation_params"]], "operation() (braindecode.augmentation.channelssymmetry static method)": [[39, "braindecode.augmentation.ChannelsSymmetry.operation"]], "compose (class in braindecode.augmentation)": [[40, "braindecode.augmentation.Compose"]], "forward() (braindecode.augmentation.compose method)": [[40, "braindecode.augmentation.Compose.forward"]], "ftsurrogate (class in braindecode.augmentation)": [[41, "braindecode.augmentation.FTSurrogate"]], "get_augmentation_params() (braindecode.augmentation.ftsurrogate method)": [[41, "braindecode.augmentation.FTSurrogate.get_augmentation_params"]], "operation() (braindecode.augmentation.ftsurrogate static method)": [[41, "braindecode.augmentation.FTSurrogate.operation"]], "frequencyshift (class in braindecode.augmentation)": [[42, "braindecode.augmentation.FrequencyShift"]], "get_augmentation_params() (braindecode.augmentation.frequencyshift method)": [[42, "braindecode.augmentation.FrequencyShift.get_augmentation_params"]], "operation() (braindecode.augmentation.frequencyshift static method)": [[42, "braindecode.augmentation.FrequencyShift.operation"]], "gaussiannoise (class in braindecode.augmentation)": [[43, "braindecode.augmentation.GaussianNoise"]], "get_augmentation_params() (braindecode.augmentation.gaussiannoise method)": [[43, "braindecode.augmentation.GaussianNoise.get_augmentation_params"]], "operation() (braindecode.augmentation.gaussiannoise static method)": [[43, "braindecode.augmentation.GaussianNoise.operation"]], "identitytransform (class in braindecode.augmentation)": [[44, "braindecode.augmentation.IdentityTransform"]], "operation() (braindecode.augmentation.identitytransform static method)": [[44, "braindecode.augmentation.IdentityTransform.operation"]], "mixup (class in braindecode.augmentation)": [[45, "braindecode.augmentation.Mixup"]], "get_augmentation_params() (braindecode.augmentation.mixup method)": [[45, "braindecode.augmentation.Mixup.get_augmentation_params"]], "operation() (braindecode.augmentation.mixup static method)": [[45, "braindecode.augmentation.Mixup.operation"]], "sensorsrotation (class in braindecode.augmentation)": [[46, "braindecode.augmentation.SensorsRotation"]], "get_augmentation_params() (braindecode.augmentation.sensorsrotation method)": [[46, "braindecode.augmentation.SensorsRotation.get_augmentation_params"]], "operation() (braindecode.augmentation.sensorsrotation static method)": [[46, "braindecode.augmentation.SensorsRotation.operation"]], "sensorsxrotation (class in braindecode.augmentation)": [[47, "braindecode.augmentation.SensorsXRotation"]], "sensorsyrotation (class in braindecode.augmentation)": [[48, "braindecode.augmentation.SensorsYRotation"]], "sensorszrotation (class in braindecode.augmentation)": [[49, "braindecode.augmentation.SensorsZRotation"]], "signflip (class in braindecode.augmentation)": [[50, "braindecode.augmentation.SignFlip"]], "operation() (braindecode.augmentation.signflip static method)": [[50, "braindecode.augmentation.SignFlip.operation"]], "smoothtimemask (class in braindecode.augmentation)": [[51, "braindecode.augmentation.SmoothTimeMask"]], "get_augmentation_params() (braindecode.augmentation.smoothtimemask method)": [[51, "braindecode.augmentation.SmoothTimeMask.get_augmentation_params"]], "operation() (braindecode.augmentation.smoothtimemask static method)": [[51, "braindecode.augmentation.SmoothTimeMask.operation"]], "timereverse (class in braindecode.augmentation)": [[52, "braindecode.augmentation.TimeReverse"]], "operation() (braindecode.augmentation.timereverse static method)": [[52, "braindecode.augmentation.TimeReverse.operation"]], "transform (class in braindecode.augmentation)": [[53, "braindecode.augmentation.Transform"]], "forward() (braindecode.augmentation.transform method)": [[53, "braindecode.augmentation.Transform.forward"]], "get_augmentation_params() (braindecode.augmentation.transform method)": [[53, "braindecode.augmentation.Transform.get_augmentation_params"]], "bandstop_filter() (in module braindecode.augmentation.functional)": [[54, "braindecode.augmentation.functional.bandstop_filter"]], "channels_dropout() (in module braindecode.augmentation.functional)": [[55, "braindecode.augmentation.functional.channels_dropout"]], "channels_permute() (in module braindecode.augmentation.functional)": [[56, "braindecode.augmentation.functional.channels_permute"]], "channels_shuffle() (in module braindecode.augmentation.functional)": [[57, "braindecode.augmentation.functional.channels_shuffle"]], "frequency_shift() (in module braindecode.augmentation.functional)": [[58, "braindecode.augmentation.functional.frequency_shift"]], "ft_surrogate() (in module braindecode.augmentation.functional)": [[59, "braindecode.augmentation.functional.ft_surrogate"]], "gaussian_noise() (in module braindecode.augmentation.functional)": [[60, "braindecode.augmentation.functional.gaussian_noise"]], "identity() (in module braindecode.augmentation.functional)": [[61, "braindecode.augmentation.functional.identity"]], "mixup() (in module braindecode.augmentation.functional)": [[62, "braindecode.augmentation.functional.mixup"]], "sensors_rotation() (in module braindecode.augmentation.functional)": [[63, "braindecode.augmentation.functional.sensors_rotation"]], "sign_flip() (in module braindecode.augmentation.functional)": [[64, "braindecode.augmentation.functional.sign_flip"]], "smooth_time_mask() (in module braindecode.augmentation.functional)": [[65, "braindecode.augmentation.functional.smooth_time_mask"]], "time_reverse() (in module braindecode.augmentation.functional)": [[66, "braindecode.augmentation.functional.time_reverse"]], "eegclassifier (class in braindecode.classifier)": [[67, "braindecode.classifier.EEGClassifier"]], "_criteria (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier._criteria"]], "_modules (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier._modules"]], "_optimizers (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier._optimizers"]], "callbacks_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.callbacks_"]], "classes_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.classes_"]], "criterion_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.criterion_"]], "cuda_dependent_attributes_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.cuda_dependent_attributes_"]], "get_iterator() (braindecode.classifier.eegclassifier method)": [[67, "braindecode.classifier.EEGClassifier.get_iterator"]], "get_loss() (braindecode.classifier.eegclassifier method)": [[67, "braindecode.classifier.EEGClassifier.get_loss"]], "initialized_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.initialized_"]], "module_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.module_"]], "predict() (braindecode.classifier.eegclassifier method)": [[67, "braindecode.classifier.EEGClassifier.predict"]], "predict_proba() (braindecode.classifier.eegclassifier method)": [[67, "braindecode.classifier.EEGClassifier.predict_proba"]], "predict_trials() (braindecode.classifier.eegclassifier method)": [[67, "braindecode.classifier.EEGClassifier.predict_trials"]], "prefixes_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.prefixes_"]], "bcicompetitionivdataset4 (class in braindecode.datasets)": [[68, "braindecode.datasets.BCICompetitionIVDataset4"]], "download() (braindecode.datasets.bcicompetitionivdataset4 static method)": [[68, "braindecode.datasets.BCICompetitionIVDataset4.download"]], "bnci2014001 (class in braindecode.datasets)": [[69, "braindecode.datasets.BNCI2014001"]], "baseconcatdataset (class in braindecode.datasets)": [[70, "braindecode.datasets.BaseConcatDataset"]], "get_metadata() (braindecode.datasets.baseconcatdataset method)": [[70, "braindecode.datasets.BaseConcatDataset.get_metadata"]], "save() (braindecode.datasets.baseconcatdataset method)": [[70, "braindecode.datasets.BaseConcatDataset.save"]], "set_description() (braindecode.datasets.baseconcatdataset method)": [[70, "braindecode.datasets.BaseConcatDataset.set_description"]], "split() (braindecode.datasets.baseconcatdataset method)": [[70, "braindecode.datasets.BaseConcatDataset.split"]], "basedataset (class in braindecode.datasets)": [[71, "braindecode.datasets.BaseDataset"]], "set_description() (braindecode.datasets.basedataset method)": [[71, "braindecode.datasets.BaseDataset.set_description"]], "hgd (class in braindecode.datasets)": [[72, "braindecode.datasets.HGD"]], "moabbdataset (class in braindecode.datasets)": [[73, "braindecode.datasets.MOABBDataset"]], "sleepphysionet (class in braindecode.datasets)": [[74, "braindecode.datasets.SleepPhysionet"]], "tuh (class in braindecode.datasets)": [[75, "braindecode.datasets.TUH"]], "tuhabnormal (class in braindecode.datasets)": [[76, "braindecode.datasets.TUHAbnormal"]], "windowsdataset (class in braindecode.datasets)": [[77, "braindecode.datasets.WindowsDataset"]], "set_description() (braindecode.datasets.windowsdataset method)": [[77, "braindecode.datasets.WindowsDataset.set_description"]], "create_from_x_y() (in module braindecode.datasets)": [[78, "braindecode.datasets.create_from_X_y"]], "create_from_mne_epochs() (in module braindecode.datasets)": [[79, "braindecode.datasets.create_from_mne_epochs"]], "create_from_mne_raw() (in module braindecode.datasets)": [[80, "braindecode.datasets.create_from_mne_raw"]], "load_concat_dataset() (in module braindecode.datautil)": [[81, "braindecode.datautil.load_concat_dataset"]], "save_concat_dataset() (in module braindecode.datautil)": [[82, "braindecode.datautil.save_concat_dataset"]], "atcnet (class in braindecode.models)": [[83, "braindecode.models.ATCNet"]], "forward() (braindecode.models.atcnet method)": [[83, "braindecode.models.ATCNet.forward"]], "deep4net (class in braindecode.models)": [[84, "braindecode.models.Deep4Net"]], "deepsleepnet (class in braindecode.models)": [[85, "braindecode.models.DeepSleepNet"]], "forward() (braindecode.models.deepsleepnet method)": [[85, "braindecode.models.DeepSleepNet.forward"]], "eegconformer (class in braindecode.models)": [[86, "braindecode.models.EEGConformer"]], "forward() (braindecode.models.eegconformer method)": [[86, "braindecode.models.EEGConformer.forward"]], "get_fc_size() (braindecode.models.eegconformer method)": [[86, "braindecode.models.EEGConformer.get_fc_size"]], "eegitnet (class in braindecode.models)": [[87, "braindecode.models.EEGITNet"]], "eeginception (class in braindecode.models)": [[88, "braindecode.models.EEGInception"]], "eeginceptionerp (class in braindecode.models)": [[89, "braindecode.models.EEGInceptionERP"]], "eeginceptionmi (class in braindecode.models)": [[90, "braindecode.models.EEGInceptionMI"]], "forward() (braindecode.models.eeginceptionmi method)": [[90, "braindecode.models.EEGInceptionMI.forward"]], "eegmodulemixin (class in braindecode.models)": [[91, "braindecode.models.EEGModuleMixin"]], "get_output_shape() (braindecode.models.eegmodulemixin method)": [[91, "braindecode.models.EEGModuleMixin.get_output_shape"]], "get_torchinfo_statistics() (braindecode.models.eegmodulemixin method)": [[91, "braindecode.models.EEGModuleMixin.get_torchinfo_statistics"]], "load_state_dict() (braindecode.models.eegmodulemixin method)": [[91, "braindecode.models.EEGModuleMixin.load_state_dict"]], "to_dense_prediction_model() (braindecode.models.eegmodulemixin method)": [[91, "braindecode.models.EEGModuleMixin.to_dense_prediction_model"]], "eegnetv1 (class in braindecode.models)": [[92, "braindecode.models.EEGNetv1"]], "eegnetv4 (class in braindecode.models)": [[93, "braindecode.models.EEGNetv4"]], "eegresnet (class in braindecode.models)": [[94, "braindecode.models.EEGResNet"]], "hybridnet (class in braindecode.models)": [[95, "braindecode.models.HybridNet"]], "forward() (braindecode.models.hybridnet method)": [[95, "braindecode.models.HybridNet.forward"]], "shallowfbcspnet (class in braindecode.models)": [[96, "braindecode.models.ShallowFBCSPNet"]], "sleepstagerblanco2020 (class in braindecode.models)": [[97, "braindecode.models.SleepStagerBlanco2020"]], "forward() (braindecode.models.sleepstagerblanco2020 method)": [[97, "braindecode.models.SleepStagerBlanco2020.forward"]], "sleepstagerchambon2018 (class in braindecode.models)": [[98, "braindecode.models.SleepStagerChambon2018"]], "forward() (braindecode.models.sleepstagerchambon2018 method)": [[98, "braindecode.models.SleepStagerChambon2018.forward"]], "sleepstagereldele2021 (class in braindecode.models)": [[99, "braindecode.models.SleepStagerEldele2021"]], "forward() (braindecode.models.sleepstagereldele2021 method)": [[99, "braindecode.models.SleepStagerEldele2021.forward"]], "tcn (class in braindecode.models)": [[100, "braindecode.models.TCN"]], "forward() (braindecode.models.tcn method)": [[100, "braindecode.models.TCN.forward"]], "tidnet (class in braindecode.models)": [[101, "braindecode.models.TIDNet"]], "forward() (braindecode.models.tidnet method)": [[101, "braindecode.models.TIDNet.forward"]], "timedistributed (class in braindecode.models)": [[102, "braindecode.models.TimeDistributed"]], "forward() (braindecode.models.timedistributed method)": [[102, "braindecode.models.TimeDistributed.forward"]], "usleep (class in braindecode.models)": [[103, "braindecode.models.USleep"]], "forward() (braindecode.models.usleep method)": [[103, "braindecode.models.USleep.forward"]], "get_output_shape() (in module braindecode.models)": [[104, "braindecode.models.get_output_shape"]], "crop (class in braindecode.preprocessing)": [[105, "braindecode.preprocessing.Crop"]], "dropchannels (class in braindecode.preprocessing)": [[106, "braindecode.preprocessing.DropChannels"]], "filter (class in braindecode.preprocessing)": [[107, "braindecode.preprocessing.Filter"]], "pick (class in braindecode.preprocessing)": [[108, "braindecode.preprocessing.Pick"]], "preprocessor (class in braindecode.preprocessing)": [[109, "braindecode.preprocessing.Preprocessor"]], "apply() (braindecode.preprocessing.preprocessor method)": [[109, "braindecode.preprocessing.Preprocessor.apply"]], "resample (class in braindecode.preprocessing)": [[110, "braindecode.preprocessing.Resample"]], "seteegreference (class in braindecode.preprocessing)": [[111, "braindecode.preprocessing.SetEEGReference"]], "create_fixed_length_windows() (in module braindecode.preprocessing)": [[112, "braindecode.preprocessing.create_fixed_length_windows"]], "create_windows_from_events() (in module braindecode.preprocessing)": [[113, "braindecode.preprocessing.create_windows_from_events"]], "create_windows_from_target_channels() (in module braindecode.preprocessing)": [[114, "braindecode.preprocessing.create_windows_from_target_channels"]], "exponential_moving_demean() (in module braindecode.preprocessing)": [[115, "braindecode.preprocessing.exponential_moving_demean"]], "exponential_moving_standardize() (in module braindecode.preprocessing)": [[116, "braindecode.preprocessing.exponential_moving_standardize"]], "filterbank() (in module braindecode.preprocessing)": [[117, "braindecode.preprocessing.filterbank"]], "preprocess() (in module braindecode.preprocessing)": [[118, "braindecode.preprocessing.preprocess"]], "eegregressor (class in braindecode.regressor)": [[119, "braindecode.regressor.EEGRegressor"]], "_criteria (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor._criteria"]], "_modules (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor._modules"]], "_optimizers (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor._optimizers"]], "callbacks_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.callbacks_"]], "criterion_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.criterion_"]], "cuda_dependent_attributes_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.cuda_dependent_attributes_"]], "fit() (braindecode.regressor.eegregressor method)": [[119, "braindecode.regressor.EEGRegressor.fit"]], "get_iterator() (braindecode.regressor.eegregressor method)": [[119, "braindecode.regressor.EEGRegressor.get_iterator"]], "initialized_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.initialized_"]], "module_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.module_"]], "predict_proba() (braindecode.regressor.eegregressor method)": [[119, "braindecode.regressor.EEGRegressor.predict_proba"]], "predict_trials() (braindecode.regressor.eegregressor method)": [[119, "braindecode.regressor.EEGRegressor.predict_trials"]], "prefixes_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.prefixes_"]], "balancedsequencesampler (class in braindecode.samplers)": [[120, "braindecode.samplers.BalancedSequenceSampler"]], "sample_class() (braindecode.samplers.balancedsequencesampler method)": [[120, "braindecode.samplers.BalancedSequenceSampler.sample_class"]], "recordingsampler (class in braindecode.samplers)": [[121, "braindecode.samplers.RecordingSampler"]], "info (braindecode.samplers.recordingsampler attribute)": [[121, "braindecode.samplers.RecordingSampler.info"]], "n_recordings (braindecode.samplers.recordingsampler attribute)": [[121, "braindecode.samplers.RecordingSampler.n_recordings"]], "sample_recording() (braindecode.samplers.recordingsampler method)": [[121, "braindecode.samplers.RecordingSampler.sample_recording"]], "sample_window() (braindecode.samplers.recordingsampler method)": [[121, "braindecode.samplers.RecordingSampler.sample_window"]], "relativepositioningsampler (class in braindecode.samplers)": [[122, "braindecode.samplers.RelativePositioningSampler"]], "presample() (braindecode.samplers.relativepositioningsampler method)": [[122, "braindecode.samplers.RelativePositioningSampler.presample"]], "sequencesampler (class in braindecode.samplers)": [[123, "braindecode.samplers.SequenceSampler"]], "file_ids (braindecode.samplers.sequencesampler attribute)": [[123, "braindecode.samplers.SequenceSampler.file_ids"]], "info (braindecode.samplers.sequencesampler attribute)": [[123, "braindecode.samplers.SequenceSampler.info"]], "croppedloss (class in braindecode.training)": [[124, "braindecode.training.CroppedLoss"]], "forward() (braindecode.training.croppedloss method)": [[124, "braindecode.training.CroppedLoss.forward"]], "croppedtimeseriesepochscoring (class in braindecode.training)": [[125, "braindecode.training.CroppedTimeSeriesEpochScoring"]], "on_epoch_end() (braindecode.training.croppedtimeseriesepochscoring method)": [[125, "braindecode.training.CroppedTimeSeriesEpochScoring.on_epoch_end"]], "croppedtrialepochscoring (class in braindecode.training)": [[126, "braindecode.training.CroppedTrialEpochScoring"]], "on_batch_end() (braindecode.training.croppedtrialepochscoring method)": [[126, "braindecode.training.CroppedTrialEpochScoring.on_batch_end"]], "on_epoch_end() (braindecode.training.croppedtrialepochscoring method)": [[126, "braindecode.training.CroppedTrialEpochScoring.on_epoch_end"]], "postepochtrainscoring (class in braindecode.training)": [[127, "braindecode.training.PostEpochTrainScoring"]], "on_epoch_end() (braindecode.training.postepochtrainscoring method)": [[127, "braindecode.training.PostEpochTrainScoring.on_epoch_end"]], "timeseriesloss (class in braindecode.training)": [[128, "braindecode.training.TimeSeriesLoss"]], "forward() (braindecode.training.timeseriesloss method)": [[128, "braindecode.training.TimeSeriesLoss.forward"]], "mixup_criterion() (in module braindecode.training)": [[129, "braindecode.training.mixup_criterion"]], "predict_trials() (in module braindecode.training)": [[130, "braindecode.training.predict_trials"]], "trial_preds_from_window_preds() (in module braindecode.training)": [[131, "braindecode.training.trial_preds_from_window_preds"]], "set_random_seeds() (in module braindecode.util)": [[132, "braindecode.util.set_random_seeds"]], "compute_amplitude_gradients() (in module braindecode.visualization)": [[133, "braindecode.visualization.compute_amplitude_gradients"]], "plot_confusion_matrix() (in module braindecode.visualization)": [[134, "braindecode.visualization.plot_confusion_matrix"]]}})
\ No newline at end of file
+Search.setIndex({"docnames": ["api", "auto_examples/advanced_training/index", "auto_examples/advanced_training/plot_bcic_iv_4_ecog_cropped", "auto_examples/advanced_training/plot_data_augmentation", "auto_examples/advanced_training/plot_data_augmentation_search", "auto_examples/advanced_training/plot_relative_positioning", "auto_examples/advanced_training/sg_execution_times", "auto_examples/applied_examples/index", "auto_examples/applied_examples/plot_bcic_iv_4_ecog_trial", "auto_examples/applied_examples/plot_sleep_staging_chambon2018", "auto_examples/applied_examples/plot_sleep_staging_eldele2021", "auto_examples/applied_examples/plot_sleep_staging_usleep", "auto_examples/applied_examples/plot_tuh_eeg_corpus", "auto_examples/applied_examples/sg_execution_times", "auto_examples/datasets_io/benchmark_lazy_eager_loading", "auto_examples/datasets_io/index", "auto_examples/datasets_io/plot_benchmark_preprocessing", "auto_examples/datasets_io/plot_custom_dataset_example", "auto_examples/datasets_io/plot_load_save_datasets", "auto_examples/datasets_io/plot_mne_dataset_example", "auto_examples/datasets_io/plot_moabb_dataset_example", "auto_examples/datasets_io/plot_split_dataset", "auto_examples/datasets_io/plot_tuh_discrete_multitarget", "auto_examples/datasets_io/sg_execution_times", "auto_examples/index", "auto_examples/model_building/index", "auto_examples/model_building/plot_basic_training_epochs", "auto_examples/model_building/plot_bcic_iv_2a_moabb_cropped", "auto_examples/model_building/plot_bcic_iv_2a_moabb_trial", "auto_examples/model_building/plot_how_train_test_and_tune", "auto_examples/model_building/plot_hyperparameter_tuning_with_scikit-learn", "auto_examples/model_building/plot_regression", "auto_examples/model_building/plot_train_in_pure_pytorch_and_pytorch_lightning", "auto_examples/model_building/sg_execution_times", "cite", "generated/braindecode.augmentation.AugmentedDataLoader", "generated/braindecode.augmentation.BandstopFilter", "generated/braindecode.augmentation.ChannelsDropout", "generated/braindecode.augmentation.ChannelsShuffle", "generated/braindecode.augmentation.ChannelsSymmetry", "generated/braindecode.augmentation.Compose", "generated/braindecode.augmentation.FTSurrogate", "generated/braindecode.augmentation.FrequencyShift", "generated/braindecode.augmentation.GaussianNoise", "generated/braindecode.augmentation.IdentityTransform", "generated/braindecode.augmentation.Mixup", "generated/braindecode.augmentation.SensorsRotation", "generated/braindecode.augmentation.SensorsXRotation", "generated/braindecode.augmentation.SensorsYRotation", "generated/braindecode.augmentation.SensorsZRotation", "generated/braindecode.augmentation.SignFlip", "generated/braindecode.augmentation.SmoothTimeMask", "generated/braindecode.augmentation.TimeReverse", "generated/braindecode.augmentation.Transform", "generated/braindecode.augmentation.functional.bandstop_filter", "generated/braindecode.augmentation.functional.channels_dropout", "generated/braindecode.augmentation.functional.channels_permute", "generated/braindecode.augmentation.functional.channels_shuffle", "generated/braindecode.augmentation.functional.frequency_shift", "generated/braindecode.augmentation.functional.ft_surrogate", "generated/braindecode.augmentation.functional.gaussian_noise", "generated/braindecode.augmentation.functional.identity", "generated/braindecode.augmentation.functional.mixup", "generated/braindecode.augmentation.functional.sensors_rotation", "generated/braindecode.augmentation.functional.sign_flip", "generated/braindecode.augmentation.functional.smooth_time_mask", "generated/braindecode.augmentation.functional.time_reverse", "generated/braindecode.classifier.EEGClassifier", "generated/braindecode.datasets.BCICompetitionIVDataset4", "generated/braindecode.datasets.BNCI2014001", "generated/braindecode.datasets.BaseConcatDataset", "generated/braindecode.datasets.BaseDataset", "generated/braindecode.datasets.HGD", "generated/braindecode.datasets.MOABBDataset", "generated/braindecode.datasets.SleepPhysionet", "generated/braindecode.datasets.TUH", "generated/braindecode.datasets.TUHAbnormal", "generated/braindecode.datasets.WindowsDataset", "generated/braindecode.datasets.create_from_X_y", "generated/braindecode.datasets.create_from_mne_epochs", "generated/braindecode.datasets.create_from_mne_raw", "generated/braindecode.datautil.load_concat_dataset", "generated/braindecode.datautil.save_concat_dataset", "generated/braindecode.models.ATCNet", "generated/braindecode.models.Deep4Net", "generated/braindecode.models.DeepSleepNet", "generated/braindecode.models.EEGConformer", "generated/braindecode.models.EEGITNet", "generated/braindecode.models.EEGInception", "generated/braindecode.models.EEGInceptionERP", "generated/braindecode.models.EEGInceptionMI", "generated/braindecode.models.EEGModuleMixin", "generated/braindecode.models.EEGNetv1", "generated/braindecode.models.EEGNetv4", "generated/braindecode.models.EEGResNet", "generated/braindecode.models.HybridNet", "generated/braindecode.models.ShallowFBCSPNet", "generated/braindecode.models.SleepStagerBlanco2020", "generated/braindecode.models.SleepStagerChambon2018", "generated/braindecode.models.SleepStagerEldele2021", "generated/braindecode.models.TCN", "generated/braindecode.models.TIDNet", "generated/braindecode.models.TimeDistributed", "generated/braindecode.models.USleep", "generated/braindecode.models.get_output_shape", "generated/braindecode.preprocessing.Crop", "generated/braindecode.preprocessing.DropChannels", "generated/braindecode.preprocessing.Filter", "generated/braindecode.preprocessing.Pick", "generated/braindecode.preprocessing.Preprocessor", "generated/braindecode.preprocessing.Resample", "generated/braindecode.preprocessing.SetEEGReference", "generated/braindecode.preprocessing.create_fixed_length_windows", "generated/braindecode.preprocessing.create_windows_from_events", "generated/braindecode.preprocessing.create_windows_from_target_channels", "generated/braindecode.preprocessing.exponential_moving_demean", "generated/braindecode.preprocessing.exponential_moving_standardize", "generated/braindecode.preprocessing.filterbank", "generated/braindecode.preprocessing.preprocess", "generated/braindecode.regressor.EEGRegressor", "generated/braindecode.samplers.BalancedSequenceSampler", "generated/braindecode.samplers.RecordingSampler", "generated/braindecode.samplers.RelativePositioningSampler", "generated/braindecode.samplers.SequenceSampler", "generated/braindecode.training.CroppedLoss", "generated/braindecode.training.CroppedTimeSeriesEpochScoring", "generated/braindecode.training.CroppedTrialEpochScoring", "generated/braindecode.training.PostEpochTrainScoring", "generated/braindecode.training.TimeSeriesLoss", "generated/braindecode.training.mixup_criterion", "generated/braindecode.training.predict_trials", "generated/braindecode.training.trial_preds_from_window_preds", "generated/braindecode.util.set_random_seeds", "generated/braindecode.visualization.compute_amplitude_gradients", "generated/braindecode.visualization.plot_confusion_matrix", "help", "index", "install/install", "install/install_pip", "install/install_source", "whats_new"], "filenames": ["api.rst", "auto_examples/advanced_training/index.rst", "auto_examples/advanced_training/plot_bcic_iv_4_ecog_cropped.rst", "auto_examples/advanced_training/plot_data_augmentation.rst", "auto_examples/advanced_training/plot_data_augmentation_search.rst", "auto_examples/advanced_training/plot_relative_positioning.rst", "auto_examples/advanced_training/sg_execution_times.rst", "auto_examples/applied_examples/index.rst", "auto_examples/applied_examples/plot_bcic_iv_4_ecog_trial.rst", "auto_examples/applied_examples/plot_sleep_staging_chambon2018.rst", "auto_examples/applied_examples/plot_sleep_staging_eldele2021.rst", "auto_examples/applied_examples/plot_sleep_staging_usleep.rst", "auto_examples/applied_examples/plot_tuh_eeg_corpus.rst", "auto_examples/applied_examples/sg_execution_times.rst", "auto_examples/datasets_io/benchmark_lazy_eager_loading.rst", "auto_examples/datasets_io/index.rst", "auto_examples/datasets_io/plot_benchmark_preprocessing.rst", "auto_examples/datasets_io/plot_custom_dataset_example.rst", "auto_examples/datasets_io/plot_load_save_datasets.rst", "auto_examples/datasets_io/plot_mne_dataset_example.rst", "auto_examples/datasets_io/plot_moabb_dataset_example.rst", "auto_examples/datasets_io/plot_split_dataset.rst", "auto_examples/datasets_io/plot_tuh_discrete_multitarget.rst", "auto_examples/datasets_io/sg_execution_times.rst", "auto_examples/index.rst", "auto_examples/model_building/index.rst", "auto_examples/model_building/plot_basic_training_epochs.rst", "auto_examples/model_building/plot_bcic_iv_2a_moabb_cropped.rst", "auto_examples/model_building/plot_bcic_iv_2a_moabb_trial.rst", "auto_examples/model_building/plot_how_train_test_and_tune.rst", "auto_examples/model_building/plot_hyperparameter_tuning_with_scikit-learn.rst", "auto_examples/model_building/plot_regression.rst", "auto_examples/model_building/plot_train_in_pure_pytorch_and_pytorch_lightning.rst", "auto_examples/model_building/sg_execution_times.rst", "cite.rst", "generated/braindecode.augmentation.AugmentedDataLoader.rst", "generated/braindecode.augmentation.BandstopFilter.rst", "generated/braindecode.augmentation.ChannelsDropout.rst", "generated/braindecode.augmentation.ChannelsShuffle.rst", "generated/braindecode.augmentation.ChannelsSymmetry.rst", "generated/braindecode.augmentation.Compose.rst", "generated/braindecode.augmentation.FTSurrogate.rst", "generated/braindecode.augmentation.FrequencyShift.rst", "generated/braindecode.augmentation.GaussianNoise.rst", "generated/braindecode.augmentation.IdentityTransform.rst", "generated/braindecode.augmentation.Mixup.rst", "generated/braindecode.augmentation.SensorsRotation.rst", "generated/braindecode.augmentation.SensorsXRotation.rst", "generated/braindecode.augmentation.SensorsYRotation.rst", "generated/braindecode.augmentation.SensorsZRotation.rst", "generated/braindecode.augmentation.SignFlip.rst", "generated/braindecode.augmentation.SmoothTimeMask.rst", "generated/braindecode.augmentation.TimeReverse.rst", "generated/braindecode.augmentation.Transform.rst", "generated/braindecode.augmentation.functional.bandstop_filter.rst", "generated/braindecode.augmentation.functional.channels_dropout.rst", "generated/braindecode.augmentation.functional.channels_permute.rst", "generated/braindecode.augmentation.functional.channels_shuffle.rst", "generated/braindecode.augmentation.functional.frequency_shift.rst", "generated/braindecode.augmentation.functional.ft_surrogate.rst", "generated/braindecode.augmentation.functional.gaussian_noise.rst", "generated/braindecode.augmentation.functional.identity.rst", "generated/braindecode.augmentation.functional.mixup.rst", "generated/braindecode.augmentation.functional.sensors_rotation.rst", "generated/braindecode.augmentation.functional.sign_flip.rst", "generated/braindecode.augmentation.functional.smooth_time_mask.rst", "generated/braindecode.augmentation.functional.time_reverse.rst", "generated/braindecode.classifier.EEGClassifier.rst", "generated/braindecode.datasets.BCICompetitionIVDataset4.rst", "generated/braindecode.datasets.BNCI2014001.rst", "generated/braindecode.datasets.BaseConcatDataset.rst", "generated/braindecode.datasets.BaseDataset.rst", "generated/braindecode.datasets.HGD.rst", "generated/braindecode.datasets.MOABBDataset.rst", "generated/braindecode.datasets.SleepPhysionet.rst", "generated/braindecode.datasets.TUH.rst", "generated/braindecode.datasets.TUHAbnormal.rst", "generated/braindecode.datasets.WindowsDataset.rst", "generated/braindecode.datasets.create_from_X_y.rst", "generated/braindecode.datasets.create_from_mne_epochs.rst", "generated/braindecode.datasets.create_from_mne_raw.rst", "generated/braindecode.datautil.load_concat_dataset.rst", "generated/braindecode.datautil.save_concat_dataset.rst", "generated/braindecode.models.ATCNet.rst", "generated/braindecode.models.Deep4Net.rst", "generated/braindecode.models.DeepSleepNet.rst", "generated/braindecode.models.EEGConformer.rst", "generated/braindecode.models.EEGITNet.rst", "generated/braindecode.models.EEGInception.rst", "generated/braindecode.models.EEGInceptionERP.rst", "generated/braindecode.models.EEGInceptionMI.rst", "generated/braindecode.models.EEGModuleMixin.rst", "generated/braindecode.models.EEGNetv1.rst", "generated/braindecode.models.EEGNetv4.rst", "generated/braindecode.models.EEGResNet.rst", "generated/braindecode.models.HybridNet.rst", "generated/braindecode.models.ShallowFBCSPNet.rst", "generated/braindecode.models.SleepStagerBlanco2020.rst", "generated/braindecode.models.SleepStagerChambon2018.rst", "generated/braindecode.models.SleepStagerEldele2021.rst", "generated/braindecode.models.TCN.rst", "generated/braindecode.models.TIDNet.rst", "generated/braindecode.models.TimeDistributed.rst", "generated/braindecode.models.USleep.rst", "generated/braindecode.models.get_output_shape.rst", "generated/braindecode.preprocessing.Crop.rst", "generated/braindecode.preprocessing.DropChannels.rst", "generated/braindecode.preprocessing.Filter.rst", "generated/braindecode.preprocessing.Pick.rst", "generated/braindecode.preprocessing.Preprocessor.rst", "generated/braindecode.preprocessing.Resample.rst", "generated/braindecode.preprocessing.SetEEGReference.rst", "generated/braindecode.preprocessing.create_fixed_length_windows.rst", "generated/braindecode.preprocessing.create_windows_from_events.rst", "generated/braindecode.preprocessing.create_windows_from_target_channels.rst", "generated/braindecode.preprocessing.exponential_moving_demean.rst", "generated/braindecode.preprocessing.exponential_moving_standardize.rst", "generated/braindecode.preprocessing.filterbank.rst", "generated/braindecode.preprocessing.preprocess.rst", "generated/braindecode.regressor.EEGRegressor.rst", "generated/braindecode.samplers.BalancedSequenceSampler.rst", "generated/braindecode.samplers.RecordingSampler.rst", "generated/braindecode.samplers.RelativePositioningSampler.rst", "generated/braindecode.samplers.SequenceSampler.rst", "generated/braindecode.training.CroppedLoss.rst", "generated/braindecode.training.CroppedTimeSeriesEpochScoring.rst", "generated/braindecode.training.CroppedTrialEpochScoring.rst", "generated/braindecode.training.PostEpochTrainScoring.rst", "generated/braindecode.training.TimeSeriesLoss.rst", "generated/braindecode.training.mixup_criterion.rst", "generated/braindecode.training.predict_trials.rst", "generated/braindecode.training.trial_preds_from_window_preds.rst", "generated/braindecode.util.set_random_seeds.rst", "generated/braindecode.visualization.compute_amplitude_gradients.rst", "generated/braindecode.visualization.plot_confusion_matrix.rst", "help.rst", "index.rst", "install/install.rst", "install/install_pip.rst", "install/install_source.rst", "whats_new.rst"], "titles": ["API Reference", "Advanced neural network training strategies", "Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset", "Data Augmentation on BCIC IV 2a Dataset", "Searching the best data augmentation on BCIC IV 2a Dataset", "Self-supervised learning on EEG with relative positioning", "Computation times", "Applied examples on real-world datasets", "Fingers flexion decoding on BCIC IV 4 ECoG Dataset", "Sleep staging on the Sleep Physionet dataset using Chambon2018 network", "Sleep staging on the Sleep Physionet dataset using Eldele2021", "Sleep staging on the Sleep Physionet dataset using U-Sleep network", "Process a big data EEG resource (TUH EEG Corpus)", "Computation times", "Benchmarking eager and lazy loading", "Loading and organizing data", "Benchmarking preprocessing with parallelization and serialization", "Custom Dataset Example", "Load and save dataset example", "MNE Dataset Example", "MOABB Dataset Example", "Split Dataset Example", "Multiple discrete targets with the TUH EEG Corpus", "Computation times", "Examples", "Basic model building and training", "Simple training on MNE epochs", "Cropped Decoding on BCIC IV 2a Dataset", "Basic Brain Decoding on EEG Data", "How to train, test and tune your model?", "Hyperparameter tuning with scikit-learn", "Convolutional neural network regression model on fake data.", "Training a Braindecode model in PyTorch", "Computation times", "How to cite Braindecode", "braindecode.augmentation.AugmentedDataLoader", "braindecode.augmentation.BandstopFilter", "braindecode.augmentation.ChannelsDropout", "braindecode.augmentation.ChannelsShuffle", "braindecode.augmentation.ChannelsSymmetry", "braindecode.augmentation.Compose", "braindecode.augmentation.FTSurrogate", "braindecode.augmentation.FrequencyShift", "braindecode.augmentation.GaussianNoise", "braindecode.augmentation.IdentityTransform", "braindecode.augmentation.Mixup", "braindecode.augmentation.SensorsRotation", "braindecode.augmentation.SensorsXRotation", "braindecode.augmentation.SensorsYRotation", "braindecode.augmentation.SensorsZRotation", "braindecode.augmentation.SignFlip", "braindecode.augmentation.SmoothTimeMask", "braindecode.augmentation.TimeReverse", "braindecode.augmentation.Transform", "braindecode.augmentation.functional.bandstop_filter", "braindecode.augmentation.functional.channels_dropout", "braindecode.augmentation.functional.channels_permute", "braindecode.augmentation.functional.channels_shuffle", "braindecode.augmentation.functional.frequency_shift", "braindecode.augmentation.functional.ft_surrogate", "braindecode.augmentation.functional.gaussian_noise", "braindecode.augmentation.functional.identity", "braindecode.augmentation.functional.mixup", "braindecode.augmentation.functional.sensors_rotation", "braindecode.augmentation.functional.sign_flip", "braindecode.augmentation.functional.smooth_time_mask", "braindecode.augmentation.functional.time_reverse", "braindecode.classifier.EEGClassifier", "braindecode.datasets.BCICompetitionIVDataset4", "braindecode.datasets.BNCI2014001", "braindecode.datasets.BaseConcatDataset", "braindecode.datasets.BaseDataset", "braindecode.datasets.HGD", "braindecode.datasets.MOABBDataset", "braindecode.datasets.SleepPhysionet", "braindecode.datasets.TUH", "braindecode.datasets.TUHAbnormal", "braindecode.datasets.WindowsDataset", "braindecode.datasets.create_from_X_y", "braindecode.datasets.create_from_mne_epochs", "braindecode.datasets.create_from_mne_raw", "braindecode.datautil.load_concat_dataset", "braindecode.datautil.save_concat_dataset", "braindecode.models.ATCNet", "braindecode.models.Deep4Net", "braindecode.models.DeepSleepNet", "braindecode.models.EEGConformer", "braindecode.models.EEGITNet", "braindecode.models.EEGInception", "braindecode.models.EEGInceptionERP", "braindecode.models.EEGInceptionMI", "braindecode.models.EEGModuleMixin", "braindecode.models.EEGNetv1", "braindecode.models.EEGNetv4", "braindecode.models.EEGResNet", "braindecode.models.HybridNet", "braindecode.models.ShallowFBCSPNet", "braindecode.models.SleepStagerBlanco2020", "braindecode.models.SleepStagerChambon2018", "braindecode.models.SleepStagerEldele2021", "braindecode.models.TCN", "braindecode.models.TIDNet", "braindecode.models.TimeDistributed", "braindecode.models.USleep", "braindecode.models.get_output_shape", "braindecode.preprocessing.Crop", "braindecode.preprocessing.DropChannels", "braindecode.preprocessing.Filter", "braindecode.preprocessing.Pick", "braindecode.preprocessing.Preprocessor", "braindecode.preprocessing.Resample", "braindecode.preprocessing.SetEEGReference", "braindecode.preprocessing.create_fixed_length_windows", "braindecode.preprocessing.create_windows_from_events", "braindecode.preprocessing.create_windows_from_target_channels", "braindecode.preprocessing.exponential_moving_demean", "braindecode.preprocessing.exponential_moving_standardize", "braindecode.preprocessing.filterbank", "braindecode.preprocessing.preprocess", "braindecode.regressor.EEGRegressor", "braindecode.samplers.BalancedSequenceSampler", "braindecode.samplers.RecordingSampler", "braindecode.samplers.RelativePositioningSampler", "braindecode.samplers.SequenceSampler", "braindecode.training.CroppedLoss", "braindecode.training.CroppedTimeSeriesEpochScoring", "braindecode.training.CroppedTrialEpochScoring", "braindecode.training.PostEpochTrainScoring", "braindecode.training.TimeSeriesLoss", "braindecode.training.mixup_criterion", "braindecode.training.predict_trials", "braindecode.training.trial_preds_from_window_preds", "braindecode.util.set_random_seeds", "braindecode.visualization.compute_amplitude_gradients", "braindecode.visualization.plot_confusion_matrix", "Frequently Asked Questions (FAQ)", "Braindecode", "Installation", "Installing from PyPI", "Installing from sources", "What\u2019s new"], "terms": {"thi": [0, 2, 8, 9, 10, 11, 14, 16, 17, 18, 19, 20, 22, 31, 47, 48, 49, 67, 68, 69, 70, 72, 74, 75, 76, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 111, 113, 115, 116, 119, 121, 127, 132, 135, 139, 140], "i": [0, 2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 20, 21, 22, 26, 27, 28, 30, 31, 34, 36, 40, 41, 42, 45, 46, 51, 53, 54, 58, 59, 62, 63, 65, 67, 68, 69, 70, 71, 72, 73, 77, 78, 79, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 109, 110, 111, 112, 113, 118, 119, 122, 127, 131, 132, 136, 137, 138, 140], "class": [0, 3, 4, 5, 9, 10, 11, 12, 14, 18, 20, 21, 26, 27, 28, 29, 30, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 59, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 105, 106, 107, 108, 109, 110, 111, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 134, 140], "camelcas": 0, "name": [0, 2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 20, 21, 22, 26, 29, 30, 32, 39, 67, 69, 70, 71, 72, 73, 78, 81, 106, 107, 108, 109, 111, 119, 125, 126, 127, 140], "function": [0, 2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 20, 22, 26, 27, 28, 30, 31, 32, 34, 41, 53, 67, 70, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 105, 109, 111, 113, 119, 125, 126, 127, 132, 140], "underscore_cas": 0, "braindecod": [0, 2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 25, 27, 28, 29, 30, 31, 33, 137, 138, 140], "base": [0, 2, 3, 4, 5, 8, 9, 10, 12, 16, 18, 20, 21, 26, 27, 28, 29, 30, 31, 32, 35, 43, 45, 60, 62, 67, 69, 70, 83, 85, 86, 87, 88, 89, 90, 92, 93, 99, 105, 107, 108, 112, 113, 119, 121, 129, 140], "datautil": [0, 5, 18, 77, 140], "exampl": [1, 2, 8, 9, 10, 11, 14, 15, 16, 22, 23, 25, 31, 36, 38, 39, 43, 44, 45, 46, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 111, 135, 140], "explain": [1, 4, 24, 27, 87], "more": [1, 2, 3, 4, 5, 8, 9, 10, 11, 16, 18, 20, 21, 22, 24, 26, 27, 28, 29, 30, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 101, 103, 105, 106, 107, 108, 110, 111, 118, 119, 132, 139, 140], "topic": [1, 24, 34], "finger": [1, 6, 7, 13, 24, 68, 70, 72, 91, 96, 104, 109, 112, 114, 116, 118, 125, 126, 128, 132, 140], "flexion": [1, 6, 7, 13, 24, 68, 70, 91, 96, 104, 109, 112, 114, 116, 118, 125, 126, 128, 132, 140], "crop": [1, 6, 8, 10, 11, 12, 16, 20, 24, 25, 29, 30, 31, 32, 33, 67, 68, 70, 73, 74, 77, 91, 96, 104, 109, 112, 113, 116, 118, 119, 124, 125, 126, 128, 130, 132, 134, 140], "decod": [1, 3, 4, 6, 7, 11, 13, 20, 22, 24, 25, 26, 29, 30, 31, 32, 33, 34, 67, 68, 70, 73, 78, 84, 86, 91, 95, 96, 103, 104, 109, 112, 113, 114, 116, 118, 119, 124, 125, 126, 128, 130, 132, 134, 136, 140], "bcic": [1, 6, 7, 13, 20, 24, 25, 29, 32, 33, 35, 37, 40, 41, 42, 50, 51, 53, 68, 70, 73, 91, 96, 104, 109, 112, 113, 114, 116, 118, 124, 125, 126, 128, 132, 134, 140], "iv": [1, 6, 7, 13, 20, 21, 24, 25, 26, 28, 29, 30, 32, 33, 35, 37, 40, 41, 42, 50, 51, 53, 68, 70, 73, 83, 90, 91, 96, 104, 109, 112, 113, 114, 116, 118, 124, 125, 126, 128, 132, 134, 140], "4": [1, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 28, 29, 30, 31, 32, 33, 68, 69, 70, 72, 83, 84, 86, 87, 88, 89, 90, 91, 92, 93, 96, 98, 101, 103, 104, 109, 112, 114, 116, 117, 118, 120, 121, 125, 126, 128, 132], "ecog": [1, 6, 7, 13, 24, 68, 70, 91, 96, 104, 109, 111, 112, 114, 116, 118, 125, 126, 128, 132, 136, 140], "dataset": [1, 6, 13, 14, 15, 16, 23, 25, 26, 33, 35, 37, 40, 41, 42, 50, 51, 53, 67, 81, 83, 90, 91, 96, 98, 99, 102, 103, 104, 109, 112, 113, 114, 116, 118, 119, 121, 123, 124, 125, 126, 128, 130, 132, 133, 134, 135, 136, 138, 139, 140], "data": [1, 2, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 17, 18, 19, 21, 25, 30, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 53, 57, 60, 62, 63, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 80, 81, 84, 86, 91, 96, 104, 105, 107, 108, 109, 110, 111, 112, 113, 115, 116, 118, 119, 124, 129, 132, 134, 135, 136, 140], "augment": [1, 6, 24, 70, 73, 86, 91, 96, 109, 113, 116, 118, 132, 136, 140], "2a": [1, 6, 20, 21, 24, 25, 26, 28, 29, 30, 32, 33, 35, 37, 40, 41, 42, 50, 51, 53, 70, 73, 83, 90, 91, 96, 109, 113, 116, 118, 124, 132, 134, 140], "search": [1, 6, 24, 29, 30, 35, 37, 41, 51, 53, 67, 70, 73, 91, 96, 109, 113, 116, 118, 119, 132, 135, 140], "best": [1, 6, 24, 32, 35, 37, 41, 51, 53, 70, 73, 91, 96, 109, 113, 116, 118, 132], "self": [1, 4, 6, 11, 24, 32, 67, 70, 74, 83, 86, 91, 98, 109, 113, 118, 119, 121, 122, 123, 132, 135, 140], "supervis": [1, 4, 6, 24, 29, 32, 70, 74, 91, 98, 109, 113, 118, 121, 122, 132, 140], "learn": [1, 2, 3, 4, 6, 8, 9, 10, 11, 24, 25, 27, 28, 29, 31, 32, 33, 34, 36, 37, 38, 39, 43, 45, 51, 54, 55, 56, 57, 60, 62, 65, 67, 70, 73, 74, 84, 88, 89, 91, 95, 96, 98, 99, 109, 113, 116, 118, 119, 121, 122, 132, 134, 136, 138, 140], "eeg": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 20, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 69, 70, 72, 73, 74, 75, 76, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 108, 109, 111, 112, 113, 116, 118, 121, 122, 129, 132, 134, 136, 140], "rel": [1, 6, 24, 29, 30, 70, 74, 91, 98, 109, 113, 118, 121, 122, 132], "posit": [1, 6, 24, 27, 36, 46, 47, 48, 49, 51, 54, 63, 65, 70, 74, 91, 98, 109, 113, 118, 121, 122, 131, 132], "go": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 105], "end": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 34, 67, 90, 105, 110, 112, 113, 119, 125, 126, 127, 140], "download": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 68, 75, 76, 138], "full": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 132], "code": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 83, 86, 87, 88, 89, 99, 100, 101, 135, 137, 139, 140], "tutori": [2, 3, 4, 5, 8, 9, 10, 11, 22, 24, 26, 27, 28, 29, 30, 32, 139, 140], "show": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 19, 20, 21, 26, 28, 29, 30, 31, 32, 72, 91, 140], "you": [2, 3, 4, 5, 8, 9, 11, 12, 16, 17, 18, 19, 21, 22, 24, 27, 28, 29, 32, 34, 67, 119, 127, 135, 137, 138, 139], "how": [2, 3, 4, 5, 8, 9, 10, 11, 12, 17, 18, 19, 20, 21, 22, 24, 25, 26, 27, 28, 30, 31, 33, 67, 70, 73, 91, 96, 105, 109, 111, 113, 116, 118, 119, 132, 140], "deep": [2, 3, 4, 5, 8, 9, 10, 11, 14, 26, 27, 28, 29, 30, 31, 32, 34, 43, 60, 84, 88, 89, 95, 96, 98, 99, 101, 134, 136, 138], "bci": [2, 4, 8, 21, 26, 27, 28, 29, 30, 41, 59, 68, 69, 83, 90, 101], "competit": [2, 4, 8, 11, 14, 21, 26, 27, 28, 29, 30, 68, 69, 88, 89], "us": [2, 3, 4, 7, 8, 13, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 34, 36, 38, 39, 43, 45, 46, 47, 48, 49, 52, 55, 57, 59, 60, 63, 67, 69, 72, 77, 83, 86, 87, 88, 89, 90, 92, 94, 95, 97, 100, 101, 105, 107, 108, 110, 111, 119, 127, 130, 135, 138, 139, 140], "mode": [2, 24, 32, 67, 84, 107, 110, 119, 127, 139, 140], "For": [2, 4, 5, 8, 14, 26, 27, 28, 29, 32, 67, 103, 107, 111, 119, 121, 127, 129, 132, 136, 137, 138, 139], "we": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 20, 21, 22, 24, 26, 27, 28, 29, 30, 32, 34, 72, 86, 119, 132, 135, 138, 139], "predict": [2, 4, 5, 8, 9, 10, 11, 27, 28, 31, 67, 71, 91, 102, 119, 124, 125, 126, 127, 128, 129, 130, 131, 140], "5": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 33, 67, 69, 83, 84, 85, 86, 88, 89, 90, 96, 97, 98, 99, 103, 119], "regress": [2, 5, 8, 24, 25, 30, 33, 70, 71, 84, 91, 96, 104, 112, 119, 124, 132, 140], "target": [2, 4, 5, 8, 9, 10, 15, 17, 18, 20, 23, 24, 27, 28, 29, 31, 45, 53, 62, 67, 68, 70, 71, 75, 77, 78, 80, 81, 112, 113, 119, 120, 121, 124, 125, 128, 129, 130, 134, 140], "correspond": [2, 5, 8, 12, 21, 29, 30, 31, 36, 39, 67, 68, 69, 70, 77, 78, 80, 111, 113, 118, 119, 120, 128], "each": [2, 4, 8, 9, 10, 11, 12, 14, 16, 17, 19, 21, 22, 26, 29, 30, 31, 35, 36, 37, 41, 46, 50, 52, 54, 55, 59, 63, 64, 66, 67, 68, 69, 70, 72, 74, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 110, 112, 113, 119, 121, 123, 125, 126, 127, 131], "The": [2, 3, 4, 5, 8, 10, 11, 12, 14, 16, 18, 20, 21, 26, 27, 29, 30, 31, 32, 35, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 51, 58, 67, 69, 71, 72, 77, 83, 86, 88, 89, 90, 92, 93, 94, 95, 97, 99, 103, 105, 106, 107, 108, 110, 111, 117, 119, 129, 130, 134, 137, 139], "were": [2, 8, 9, 11, 14, 19, 26, 30, 69, 70, 72, 86, 97, 107, 140], "record": [2, 4, 8, 9, 10, 11, 14, 16, 21, 22, 26, 31, 68, 69, 72, 74, 75, 76, 80, 84, 85, 86, 87, 88, 91, 92, 93, 94, 96, 97, 98, 99, 100, 111, 112, 113, 120, 121, 122, 140], "time": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 52, 66, 67, 68, 70, 74, 77, 83, 84, 85, 86, 87, 88, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 115, 116, 119, 120, 124, 125, 128, 131, 140], "seri": [2, 4, 5, 8, 9, 10, 29, 30, 31, 67, 71, 77, 80, 97, 98, 119, 121, 125, 140], "25": [2, 4, 5, 8, 9, 11, 12, 13, 14, 16, 27, 29, 31, 32, 69, 83, 84, 85, 86, 88, 89, 92, 93, 96, 98, 107], "hz": [2, 3, 4, 5, 8, 9, 11, 16, 27, 29, 30, 31, 36, 42, 54, 58, 69, 83, 86, 90, 103, 107], "so": [2, 5, 8, 9, 10, 11, 14, 16, 18, 26, 27, 28, 29, 30, 32, 36, 39, 67, 103, 112, 117, 119, 140], "an": [2, 5, 8, 10, 12, 14, 18, 19, 20, 21, 22, 26, 27, 29, 30, 32, 40, 46, 47, 48, 49, 53, 67, 69, 71, 72, 77, 80, 83, 84, 85, 87, 88, 89, 90, 91, 94, 95, 96, 97, 98, 99, 100, 102, 103, 106, 107, 109, 110, 111, 113, 119, 121, 127, 135, 136, 140], "author": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 31, 34, 86, 87, 88, 89, 90, 92, 93], "maciej": [2, 8, 140], "sliwowski": [2, 8], "maciek": [2, 8], "gmail": [2, 5, 8, 9, 10, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 31], "com": [2, 3, 5, 8, 9, 10, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 31, 75, 76, 139], "moham": [2, 8, 140], "fattouh": [2, 8, 140], "mo": [2, 8], "licens": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 31], "bsd": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 31], "3": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 30, 31, 32, 43, 45, 46, 60, 62, 63, 67, 68, 69, 72, 74, 83, 84, 88, 89, 90, 91, 94, 97, 101, 119, 120, 121, 130, 137, 140], "claus": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26], "first": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 19, 20, 26, 27, 28, 30, 39, 51, 65, 67, 70, 74, 75, 76, 83, 84, 86, 96, 99, 107, 110, 111, 113, 119, 135, 139], "In": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 18, 20, 21, 26, 27, 28, 29, 30, 32, 36, 43, 45, 46, 47, 48, 49, 51, 54, 60, 62, 63, 65, 67, 69, 107, 108, 111, 119, 132], "avail": [2, 3, 4, 8, 9, 10, 11, 12, 14, 16, 19, 22, 26, 27, 28, 29, 30, 32, 68, 74, 86, 88, 89, 99, 112, 113, 120, 121], "part": [2, 8, 16, 17, 19, 28, 29, 32, 37, 38, 51, 55, 57, 65, 86, 88, 89], "librari": [2, 3, 4, 8, 24, 26, 28, 29, 30, 34, 68, 139], "http": [2, 4, 5, 8, 12, 26, 27, 28, 29, 30, 34, 45, 62, 67, 68, 74, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 99, 100, 101, 103, 119, 129, 132, 134, 139], "searchwork": [2, 8, 68], "stanford": [2, 8, 68], "edu": [2, 4, 8, 68], "view": [2, 4, 8, 22, 68], "zk881ps0522": [2, 8, 68], "contain": [2, 5, 8, 12, 14, 16, 18, 21, 22, 26, 31, 35, 36, 37, 38, 39, 41, 42, 43, 45, 46, 51, 54, 62, 63, 65, 67, 68, 70, 73, 74, 77, 111, 112, 113, 119, 120, 121, 122, 128, 129, 135, 140], "signal": [2, 3, 4, 5, 8, 9, 10, 11, 12, 18, 20, 26, 28, 29, 30, 31, 35, 36, 37, 38, 41, 42, 46, 47, 48, 49, 51, 54, 55, 57, 58, 59, 63, 65, 69, 71, 74, 78, 79, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 110, 111, 112, 113, 117, 119, 122, 140], "differ": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 18, 21, 26, 27, 28, 29, 30, 69, 88, 89, 90, 103, 122, 137], "than": [2, 5, 8, 9, 10, 11, 12, 14, 16, 27, 32, 36, 54, 67, 80, 107, 113, 119, 140], "standard": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 32, 35, 43, 46, 47, 48, 49, 60, 63, 111, 116, 140], "setup": [2, 4, 8, 27, 137], "multipl": [2, 3, 4, 8, 9, 10, 14, 15, 16, 21, 23, 24, 27, 29, 30, 67, 70, 75, 90, 102, 103, 107, 111, 112, 117, 119, 130, 140], "trial": [2, 3, 4, 8, 19, 21, 27, 28, 29, 30, 31, 32, 67, 69, 72, 78, 80, 113, 119, 125, 126, 130, 131, 140], "usual": [2, 3, 4, 8, 16, 29, 32, 67, 119], "one": [2, 4, 8, 9, 10, 11, 14, 16, 20, 26, 27, 29, 30, 32, 40, 45, 51, 65, 67, 69, 70, 83, 86, 90, 91, 103, 111, 112, 113, 119, 120, 121, 122, 135], "per": [2, 4, 5, 8, 9, 10, 11, 27, 45, 51, 65, 69, 72, 74, 90, 101, 111, 140], "here": [2, 3, 4, 5, 8, 10, 11, 12, 21, 22, 24, 26, 27, 28, 29, 30, 32, 42, 58, 80, 90, 113], "chang": [2, 5, 8, 14, 18, 31, 44, 67, 111, 119, 127, 139], "ar": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 19, 20, 22, 24, 26, 27, 28, 29, 30, 31, 32, 34, 36, 45, 62, 67, 70, 77, 78, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 107, 108, 111, 112, 113, 117, 119, 122, 124, 128, 135, 137, 138, 139, 140], "sampl": [2, 3, 4, 5, 8, 9, 10, 14, 16, 17, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 41, 42, 45, 46, 47, 48, 49, 51, 54, 57, 58, 59, 65, 67, 69, 71, 72, 74, 78, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 112, 113, 120, 121, 122, 123, 129, 135, 140], "frequenc": [2, 3, 4, 8, 11, 12, 16, 17, 26, 27, 28, 29, 30, 31, 32, 36, 42, 54, 58, 72, 78, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 110, 117, 120, 140], "equal": [2, 8, 32, 78, 79, 80, 91, 104, 112], "If": [2, 8, 14, 18, 19, 22, 26, 29, 30, 32, 34, 36, 45, 67, 68, 69, 70, 72, 73, 74, 75, 76, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 108, 109, 110, 111, 112, 113, 117, 118, 119, 120, 122, 123, 127, 128, 129, 130, 135, 139], "pleas": [2, 3, 4, 5, 8, 11, 12, 22, 26, 27, 28, 29, 30, 32, 68, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 117, 139, 140], "cite": [2, 8, 68], "1": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 30, 31, 36, 37, 38, 39, 41, 43, 44, 45, 46, 47, 48, 49, 51, 53, 54, 55, 56, 57, 59, 60, 62, 63, 65, 67, 68, 69, 70, 72, 74, 75, 76, 81, 83, 84, 88, 89, 90, 91, 94, 96, 97, 99, 101, 103, 104, 107, 110, 111, 112, 113, 114, 115, 116, 119, 120, 121, 129, 130, 131, 134], "miller": [2, 8, 27, 28, 29, 30, 68], "kai": [2, 8, 68], "j": [2, 4, 5, 8, 26, 27, 28, 29, 30, 31, 36, 39, 41, 43, 51, 54, 56, 59, 60, 65, 68, 84, 87, 92, 93, 95, 96, 98, 100, 101, 134], "A": [2, 3, 4, 5, 8, 9, 10, 16, 27, 28, 29, 30, 31, 35, 37, 38, 41, 53, 55, 57, 59, 67, 68, 70, 73, 75, 76, 85, 88, 89, 90, 92, 93, 97, 98, 101, 107, 111, 112, 113, 118, 119, 122, 130, 134, 140], "human": [2, 8, 26, 31, 34, 39, 56, 68, 84, 95, 96, 107, 134], "electrocorticograph": [2, 8, 68], "analys": [2, 8, 29, 30, 68], "natur": [2, 8, 14, 68], "behaviour": [2, 8, 68], "11": [2, 3, 4, 5, 8, 10, 11, 12, 13, 16, 17, 18, 19, 20, 21, 27, 28, 29, 31, 32, 33, 68, 85], "2019": [2, 8, 31, 68], "1225": [2, 8, 68], "1235": [2, 8, 68], "doi": [2, 8, 10, 26, 27, 28, 29, 30, 34, 68, 83, 84, 87, 88, 89, 95, 96, 97, 99, 101, 134], "org": [2, 4, 5, 8, 26, 27, 28, 29, 30, 34, 45, 62, 67, 68, 74, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 99, 100, 101, 103, 119, 129, 132, 134], "10": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 33, 34, 39, 46, 47, 48, 49, 63, 67, 68, 83, 84, 86, 87, 88, 89, 95, 96, 97, 99, 101, 107, 111, 119, 120, 134], "1038": [2, 8, 68], "s41562": [2, 8, 68], "019": [2, 8, 68, 97], "0678": [2, 8, 68], "import": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 41, 59, 135, 139], "copi": [2, 11, 16, 41, 59, 68, 105, 135], "numpi": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 17, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 63, 67, 107, 110, 119, 132, 134], "np": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 26, 29, 31, 32, 67, 115, 116, 119, 120, 121, 122, 123, 130], "sklearn": [2, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 30, 31, 67, 119, 127, 134, 140], "from": [2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 37, 38, 41, 45, 46, 47, 48, 49, 55, 57, 59, 63, 67, 69, 71, 72, 74, 75, 76, 77, 78, 79, 80, 81, 83, 84, 85, 87, 88, 89, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 111, 112, 113, 119, 120, 121, 122, 123, 125, 126, 127, 129, 130, 137, 140], "mne": [2, 3, 4, 8, 9, 10, 11, 12, 14, 15, 17, 18, 20, 22, 23, 24, 25, 28, 30, 33, 46, 63, 68, 70, 71, 74, 77, 79, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 105, 106, 107, 108, 109, 110, 111, 112, 113, 117, 119, 135, 140], "set_log_level": [2, 8, 12, 14, 22], "bcicompetitionivdataset4": [2, 8, 140], "subject_id": [2, 3, 4, 5, 8, 9, 10, 11, 16, 17, 18, 19, 20, 21, 27, 28, 29, 30, 32, 68, 69, 72, 73, 74, 140], "can": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 20, 21, 22, 26, 27, 28, 29, 30, 32, 34, 42, 46, 63, 67, 70, 74, 75, 76, 77, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 106, 107, 108, 110, 111, 119, 130, 137, 138, 140], "easili": [2, 8, 20, 26, 28, 29, 30, 32, 121], "addit": [2, 8, 12, 17, 20, 21, 26, 28, 29, 30, 32, 43, 60, 67, 69, 70, 71, 77, 80, 113, 119, 134], "info": [2, 3, 4, 8, 12, 14, 16, 17, 19, 20, 21, 26, 27, 28, 29, 30, 32, 70, 77, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 108, 111, 121, 123, 135, 140], "store": [2, 4, 8, 9, 10, 11, 12, 14, 18, 22, 28, 29, 30, 32, 68, 70, 81, 140], "descript": [2, 5, 8, 12, 17, 18, 19, 20, 22, 27, 28, 29, 30, 32, 68, 69, 70, 71, 75, 76, 77, 80, 81, 83, 86, 88, 90, 92, 93, 94, 95, 97, 103, 112, 113], "attribut": [2, 8, 26, 28, 29, 30, 32, 67, 71, 77, 109, 119, 140], "case": [2, 8, 16, 21, 26, 27, 28, 29, 30, 32, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 111, 119, 132, 138, 140], "session": [2, 4, 8, 12, 18, 20, 21, 27, 28, 29, 30, 31, 32, 69, 72, 121], "column": [2, 8, 19, 21, 22, 27, 28, 29, 30, 32, 70, 77, 81, 91, 120, 121, 134], "select": [2, 4, 8, 9, 16, 20, 27, 28, 29, 30, 32, 36, 72, 111, 120], "valid": [2, 21, 26, 27, 31, 32, 67, 99, 111, 112, 113, 119, 127, 128, 140], "final": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 26, 27, 28, 29, 30, 32, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 116], "evalu": [2, 3, 4, 5, 8, 9, 10, 11, 14, 21, 27, 28, 30, 100], "train_set": [2, 3, 4, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32], "test_set": [2, 8, 29, 31, 32], "now": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 22, 26, 27, 28, 30, 111, 139, 140], "appli": [2, 3, 4, 5, 8, 9, 10, 12, 16, 18, 19, 20, 26, 27, 28, 29, 30, 32, 35, 36, 37, 38, 39, 41, 42, 43, 46, 47, 48, 49, 50, 51, 52, 53, 54, 67, 71, 77, 97, 98, 102, 107, 109, 111, 117, 118, 119, 129, 140], "like": [2, 8, 16, 26, 28, 29, 30, 32, 36, 41, 46, 54, 59, 63, 67, 78, 79, 80, 99, 107, 108, 119, 121, 139, 140], "bandpass": [2, 3, 4, 8, 20, 27, 28, 29, 30, 32, 69, 107, 117], "filter": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 20, 26, 27, 28, 29, 30, 32, 36, 54, 69, 83, 84, 86, 88, 89, 90, 93, 96, 98, 100, 101, 103, 109, 110, 117, 140], "our": [2, 5, 8, 9, 10, 11, 12, 16, 20, 26, 27, 28, 30, 32, 72, 137], "either": [2, 8, 26, 28, 29, 30, 67, 69, 70, 72, 91, 107, 111, 119, 130], "provid": [2, 8, 9, 10, 11, 26, 28, 30, 32, 34, 67, 69, 70, 71, 75, 76, 102, 107, 108, 109, 118, 119, 135], "raw": [2, 3, 4, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 27, 28, 29, 30, 31, 70, 71, 74, 75, 76, 80, 85, 105, 106, 107, 108, 109, 111, 112, 113, 117, 136, 140], "epoch": [2, 3, 4, 5, 8, 9, 10, 11, 14, 19, 24, 25, 27, 28, 29, 30, 31, 32, 33, 67, 70, 77, 79, 80, 91, 96, 105, 106, 107, 108, 109, 111, 112, 113, 119, 122, 125, 126, 127, 140], "your": [2, 3, 4, 8, 14, 16, 21, 24, 25, 27, 28, 30, 33, 34, 67, 70, 73, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 109, 113, 116, 118, 119, 132, 135, 137], "own": [2, 8, 27, 28, 29, 30, 32, 72, 135], "object": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 18, 19, 21, 27, 28, 29, 30, 31, 32, 40, 71, 74, 75, 76, 77, 80, 105, 109, 112, 113, 118, 134, 140], "underli": [2, 5, 8, 28, 30, 109], "arrai": [2, 4, 8, 11, 17, 22, 26, 28, 29, 30, 36, 46, 53, 54, 63, 67, 78, 79, 80, 107, 108, 109, 110, 119, 123, 130, 134], "step": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 18, 22, 28, 29, 30, 32, 80, 113, 135], "taken": [2, 5, 8, 14], "process": [2, 4, 5, 7, 8, 13, 14, 15, 16, 22, 24, 29, 30, 70, 75, 109, 112, 118, 140], "pipelin": [2, 5, 8, 29, 32], "onli": [2, 4, 5, 8, 9, 10, 11, 12, 14, 18, 19, 21, 26, 27, 29, 30, 32, 40, 53, 67, 72, 74, 80, 87, 88, 89, 90, 92, 93, 105, 107, 108, 110, 111, 113, 119, 128, 135, 139, 140], "cutoff": [2, 8, 16, 107], "proper": [2, 8], "other": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 18, 26, 29, 30, 32, 53, 67, 72, 74, 83, 84, 85, 91, 94, 95, 96, 97, 98, 99, 100, 103, 119], "mai": [2, 3, 4, 5, 8, 9, 10, 11, 16, 18, 19, 27, 28, 29, 32, 34, 67, 119, 127, 132, 135], "need": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 26, 27, 28, 29, 32, 67, 83, 86, 90, 119, 132, 137, 140], "These": [2, 5, 8, 26, 27, 28, 30], "prepocess": [2, 8, 28, 30], "directli": [2, 3, 5, 8, 12, 22, 26, 27, 28, 30, 31, 67, 77, 109, 111, 119, 139], "fly": [2, 8, 28, 30, 71, 77, 140], "transform": [2, 5, 8, 9, 10, 11, 20, 27, 28, 29, 30, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 64, 65, 66, 67, 71, 77, 78, 79, 80, 86, 91, 119, 140], "pytorch": [2, 8, 14, 22, 24, 25, 26, 27, 28, 30, 33, 67, 70, 73, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 109, 113, 116, 118, 119, 130, 132, 138, 140], "torchvis": [2, 8, 28, 30], "preprocessor": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 18, 20, 27, 28, 29, 30, 32, 118, 140], "exponential_moving_standard": [2, 3, 4, 8, 27, 28, 29, 30, 32], "low_cut_hz": [2, 3, 4, 8, 27, 28, 29, 30, 32], "low": [2, 3, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 30, 32, 36, 54, 88, 89, 107], "high_cut_hz": [2, 3, 4, 5, 8, 9, 10, 27, 28, 29, 30, 32], "200": [2, 8, 10, 11, 14, 84], "high": [2, 3, 4, 8, 11, 27, 28, 29, 30, 32, 36, 54, 72, 88, 89, 103, 107, 120], "higher": [2, 5, 8, 32, 99], "paramet": [2, 3, 4, 5, 8, 10, 14, 16, 17, 18, 19, 26, 28, 29, 30, 31, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 105, 106, 107, 108, 109, 110, 111, 112, 113, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 127, 128, 129, 130, 131, 132, 134, 140], "exponenti": [2, 3, 4, 8, 27, 28, 29, 30, 32, 103, 115, 116], "move": [2, 3, 4, 8, 14, 16, 27, 28, 29, 30, 32, 68, 91, 115, 116, 140], "factor_new": [2, 3, 4, 8, 27, 28, 29, 30, 32, 115, 116], "1e": [2, 3, 4, 8, 9, 10, 11, 27, 28, 29, 30, 32], "init_block_s": [2, 3, 4, 8, 27, 28, 29, 30, 32, 115, 116], "1000": [2, 3, 4, 8, 12, 22, 26, 27, 28, 29, 30, 32, 72, 88, 89, 121], "30": [2, 5, 8, 9, 10, 11, 16, 27, 31, 32, 74, 96, 97, 98, 99, 103], "second": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 30, 31, 32, 39, 69, 72, 75, 76, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 105], "limit": [2, 5, 8, 11, 12, 16, 26, 105], "memori": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 67, 113, 119], "run": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 67, 69, 72, 80, 83, 86, 90, 97, 107, 109, 110, 113, 119, 121, 132, 135, 139, 140], "6": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 16, 17, 18, 19, 20, 21, 26, 27, 28, 29, 30, 31, 32, 69, 72, 86, 107], "To": [2, 3, 4, 5, 8, 9, 10, 11, 14, 16, 17, 22, 26, 27, 28, 29, 30, 31, 32, 107, 138, 139], "obtain": [2, 3, 4, 5, 8, 9, 11, 27, 28, 46, 63, 67, 71, 72, 77, 119, 121], "whole": [2, 8, 9, 10], "should": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 20, 26, 27, 28, 30, 36, 39, 46, 51, 54, 63, 65, 67, 68, 70, 71, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 105, 107, 108, 110, 111, 119, 127, 135, 139], "valid_set": [2, 3, 8, 9, 10, 11, 27, 28, 31], "deepcopi": 2, "tmin": [2, 8, 12, 16, 19, 105], "24": [2, 5, 9, 10, 11, 12, 16, 27, 32, 97, 101, 108], "tmax": [2, 8, 12, 105], "n_job": [2, 3, 4, 5, 12, 14, 16, 27, 28, 29, 30, 32, 75, 76, 81, 107, 110, 112, 113, 114, 118, 140], "0": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 33, 36, 37, 38, 41, 43, 44, 45, 53, 55, 57, 59, 62, 67, 69, 70, 74, 75, 76, 80, 83, 84, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 101, 103, 105, 106, 107, 108, 110, 111, 112, 113, 115, 116, 119, 121, 130, 134], "baseconcatdataset": [2, 5, 9, 10, 12, 14, 16, 21, 31, 67, 78, 79, 80, 81, 112, 113, 118, 119, 121, 130, 140], "0x7f3131378130": 2, "variabl": [2, 4, 8, 29, 30, 68, 132], "channel": [2, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 19, 26, 31, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 51, 55, 56, 57, 58, 59, 60, 62, 63, 65, 74, 77, 78, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 106, 107, 108, 111, 112, 113, 117, 140], "type": [2, 3, 4, 8, 11, 26, 27, 28, 29, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 51, 62, 67, 70, 72, 78, 79, 80, 81, 90, 91, 102, 104, 107, 108, 110, 111, 112, 113, 115, 116, 118, 119, 121, 123, 129, 131, 134, 140], "misc": [2, 4, 8, 77], "thu": [2, 4, 8, 105], "those": [2, 4, 5, 8, 12, 67, 107, 108, 119], "have": [2, 4, 5, 8, 11, 12, 14, 16, 17, 19, 21, 26, 27, 28, 29, 30, 32, 46, 51, 63, 65, 67, 78, 79, 80, 90, 109, 111, 112, 119, 127, 135, 138, 139, 140], "further": [2, 4, 5, 8, 9, 10, 11, 27, 29, 32, 67, 119], "howev": [2, 3, 4, 5, 8, 11, 14, 16, 21, 26, 27, 28, 29, 113], "mani": [2, 4, 5, 8, 16, 26, 27, 29, 32, 70], "ignor": [2, 4, 8, 51, 67, 83, 86, 90, 106, 109, 112, 113, 119, 122], "perform": [2, 4, 8, 9, 10, 11, 26, 27, 28, 29, 30, 32, 69, 70, 72, 83, 86, 90, 99, 115, 116, 140], "oper": [2, 3, 4, 8, 16, 36, 37, 38, 39, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 61, 105, 110], "see": [2, 3, 4, 5, 8, 9, 10, 11, 16, 18, 20, 21, 24, 26, 27, 28, 29, 30, 32, 45, 62, 67, 68, 69, 72, 74, 76, 77, 87, 91, 92, 93, 95, 100, 101, 105, 106, 107, 108, 110, 111, 112, 113, 118, 119, 120, 122, 123, 129, 132, 135, 138, 139], "tool": [2, 4, 8, 74, 136, 139], "stabl": [2, 4, 5, 8, 16, 26, 67, 74, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 119, 132, 134], "glossari": [2, 4, 8], "html": [2, 4, 5, 8, 12, 26, 27, 67, 74, 75, 76, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 119, 132, 134], "term": [2, 4, 8, 85, 91], "todo": 2, "ensur": [2, 103, 132, 138], "remov": [2, 3, 4, 5, 8, 9, 11, 18, 19, 20, 21, 26, 27, 28, 29, 30, 31, 32, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 106, 111, 131, 140], "pick_typ": [2, 3, 4, 8, 20, 27, 28, 29, 30, 32, 106], "true": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 26, 27, 28, 29, 30, 31, 32, 45, 46, 47, 48, 49, 67, 70, 71, 74, 75, 76, 77, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 109, 111, 112, 113, 114, 117, 119, 122, 123, 125, 126, 127, 130, 132, 140], "lambda": [2, 3, 4, 5, 8, 9, 10, 12, 27, 28, 29, 30, 32, 67, 94, 119], "x": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 20, 22, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 78, 79, 80, 83, 85, 86, 90, 95, 97, 98, 99, 100, 101, 102, 103, 110, 115, 116, 119, 124, 127, 128, 130], "1e6": [2, 3, 4, 5, 8, 9, 10, 12, 27, 28, 29, 30, 32], "pick": [2, 8, 10, 12, 19, 20, 107, 112, 113, 114, 140], "convert": [2, 3, 4, 5, 8, 9, 10, 12, 17, 19, 27, 28, 29, 30, 31, 32, 107], "v": [2, 3, 4, 5, 8, 9, 10, 12, 16, 27, 28, 29, 30, 32, 88, 89, 92, 93, 100], "uv": [2, 3, 4, 5, 8, 9, 10, 12, 27, 28, 29, 30, 32], "l_freq": [2, 3, 4, 5, 8, 9, 10, 16, 27, 28, 29, 30, 32, 107], "h_freq": [2, 3, 4, 5, 8, 9, 10, 16, 27, 28, 29, 30, 32, 107], "extract": [2, 8, 12, 14, 16, 17, 19, 22, 27, 32, 77, 88, 89, 90, 97, 99, 112, 113, 120, 122], "check": [2, 3, 4, 8, 9, 10, 11, 26, 27, 28, 29, 30, 32, 34, 83, 84, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 100, 101, 103, 135, 138, 140], "thei": [2, 3, 4, 8, 14, 16, 26, 27, 28, 29, 30, 32, 111, 140], "same": [2, 3, 4, 5, 8, 9, 10, 11, 14, 18, 21, 27, 28, 29, 30, 32, 42, 51, 58, 65, 67, 72, 74, 99, 119, 122], "all": [2, 3, 4, 8, 12, 14, 16, 24, 26, 27, 28, 29, 30, 32, 42, 43, 51, 58, 60, 65, 67, 68, 69, 72, 73, 74, 83, 86, 88, 89, 90, 91, 105, 107, 108, 110, 111, 112, 113, 119, 127, 140], "sfreq": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 20, 26, 27, 28, 29, 30, 31, 32, 36, 42, 54, 58, 78, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 119, 140], "assert": [2, 3, 4, 8, 12, 14, 27, 28, 29, 30, 32], "d": [2, 3, 4, 5, 8, 12, 14, 22, 26, 27, 28, 29, 30, 31, 32, 37, 38, 41, 55, 57, 59, 83, 84, 93, 95, 96, 97, 101, 122, 134, 140], "target_sfreq": [2, 8], "temp": [2, 8], "home": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 19, 26, 27, 28, 29, 30, 31, 32], "runner": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 17, 18, 19, 26, 27, 28, 29, 30, 31, 32], "work": [2, 3, 4, 5, 8, 9, 10, 12, 16, 18, 19, 20, 22, 24, 26, 27, 28, 29, 30, 31, 32, 67, 91, 103, 105, 119, 127, 136, 138, 140], "py": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 33], "55": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 32], "userwarn": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 18, 19, 26, 27, 28, 29, 30, 31, 32], "choic": [2, 3, 4, 5, 8, 9, 10, 12, 27, 28, 29, 30, 32, 86, 140], "cannot": [2, 3, 4, 5, 8, 9, 10, 11, 12, 27, 28, 29, 30, 32, 67, 105, 119], "save": [2, 3, 4, 5, 8, 9, 10, 12, 14, 15, 16, 23, 24, 27, 28, 29, 30, 32, 67, 70, 73, 81, 109, 113, 118, 119, 140], "warn": [2, 3, 4, 5, 8, 9, 10, 12, 14, 16, 18, 19, 26, 27, 28, 29, 30, 31, 32, 69, 99, 106, 112, 113, 132, 140], "contrast": [2, 4, 5, 27, 36, 43, 51, 54, 60, 65], "trialwis": [2, 4, 8, 20, 27, 28, 30, 67, 119, 130, 140], "befor": [2, 11, 16, 27, 28, 29, 30, 32, 67, 70, 71, 74, 77, 83, 84, 85, 86, 97, 98, 99, 115, 116, 119, 127, 132, 138, 140], "becaus": [2, 16, 26, 27, 29, 30, 135], "know": [2, 3, 4, 26, 27], "recept": [2, 27, 67, 119, 130], "field": [2, 27, 67, 111, 119, 130], "network": [2, 4, 5, 7, 8, 10, 13, 14, 25, 26, 27, 28, 29, 32, 33, 34, 43, 60, 67, 70, 71, 74, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 109, 112, 113, 118, 119, 121, 123, 124, 130, 132, 134, 140], "larg": [2, 5, 14, 16, 26, 27, 70, 113], "stride": [2, 9, 10, 11, 26, 27, 78, 79, 80, 84, 86, 91, 96, 101, 112, 113], "choos": [2, 3, 4, 8, 18, 27, 28, 29, 30, 32], "input": [2, 3, 4, 8, 10, 11, 14, 21, 26, 27, 28, 29, 32, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 64, 65, 66, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 119, 140], "size": [2, 3, 4, 5, 11, 14, 16, 26, 27, 28, 29, 30, 31, 32, 36, 51, 54, 65, 67, 78, 79, 80, 83, 86, 88, 89, 90, 91, 97, 98, 100, 101, 103, 104, 107, 110, 112, 113, 119, 122, 124, 128, 130, 134], "fed": [2, 27, 47, 48, 49], "dure": [2, 4, 5, 8, 9, 10, 11, 12, 14, 27, 28, 29, 30, 32, 67, 68, 107, 111, 119, 140], "ha": [2, 3, 4, 5, 8, 10, 12, 18, 19, 20, 21, 22, 27, 28, 29, 30, 31, 32, 47, 48, 49, 67, 70, 71, 74, 77, 80, 87, 88, 89, 90, 92, 93, 103, 107, 113, 119, 129, 135, 140], "larger": [2, 5, 27, 88, 89], "otherwis": [2, 14, 27, 29, 31, 80, 113], "chosen": [2, 16, 18, 27, 32, 51, 67, 107, 119, 130], "effici": [2, 3, 16, 27], "explan": [2, 27, 117, 118], "begin": [2, 27, 29, 30, 69, 97, 107, 112], "which": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 19, 20, 21, 24, 26, 27, 29, 30, 32, 34, 35, 38, 41, 46, 57, 59, 63, 67, 70, 71, 72, 77, 91, 99, 102, 107, 110, 111, 119, 121, 122, 123, 135], "rate": [2, 5, 14, 27, 28, 29, 30, 31, 32, 67, 72, 86, 88, 89, 97, 98, 99, 103, 119, 140], "input_window_sampl": [2, 3, 4, 8, 14, 26, 27, 28, 29, 30, 31, 32, 84, 86, 87, 88, 89, 92, 93, 94, 95, 96, 101, 104], "come": [2, 8, 14, 28, 30, 32, 123, 132], "some": [2, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 22, 26, 27, 28, 30, 34, 67, 70, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 111, 119, 132], "predefin": [2, 8, 28, 30], "convolut": [2, 5, 8, 9, 11, 24, 25, 26, 27, 28, 29, 30, 33, 34, 41, 43, 59, 60, 70, 71, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 112, 124, 132, 134, 140], "neural": [2, 4, 5, 8, 9, 10, 11, 14, 25, 26, 27, 28, 29, 33, 34, 43, 60, 70, 71, 84, 85, 86, 88, 89, 90, 91, 95, 96, 97, 98, 99, 101, 104, 112, 124, 132, 134, 140], "architectur": [2, 5, 8, 9, 10, 11, 26, 27, 28, 30, 67, 85, 86, 97, 98, 99, 103, 119, 136], "domain": [2, 4, 8, 16, 28, 30, 42, 58, 103, 107, 110], "shallow": [2, 8, 14, 26, 27, 28, 31, 96], "convnet": [2, 8, 26, 27, 28, 84, 95, 96], "visual": [2, 8, 9, 10, 11, 12, 26, 27, 28, 30, 31, 34, 72, 84, 86, 95, 96, 136, 140], "pure": [2, 5, 8, 28, 30, 140], "therefor": [2, 8, 12, 16, 27, 28, 29, 30, 32, 127], "just": [2, 4, 8, 22, 26, 28, 29, 30, 67, 84, 96, 119], "normal": [2, 5, 8, 9, 10, 28, 30, 97, 98, 121, 134, 140], "nn": [2, 3, 4, 5, 8, 9, 10, 11, 14, 26, 27, 28, 29, 30, 31, 32, 67, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 102, 103, 119, 130], "modul": [2, 4, 5, 8, 9, 10, 11, 14, 26, 28, 30, 32, 67, 83, 86, 88, 89, 90, 99, 102, 119, 130, 132, 134, 138, 140], "torch": [2, 3, 4, 5, 8, 9, 10, 11, 14, 22, 26, 27, 28, 29, 30, 31, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 119, 124, 128, 129, 130, 132, 140], "shallowfbcspnet": [2, 3, 4, 8, 14, 26, 27, 28, 29, 30, 31, 32], "util": [2, 3, 4, 5, 8, 9, 10, 11, 14, 18, 22, 26, 27, 28, 30, 31, 32, 67, 119, 140], "set_random_se": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32, 140], "cuda": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32, 67, 107, 110, 119, 132, 138], "is_avail": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32], "gpu": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 32, 67, 119, 138, 140], "devic": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32, 35, 67, 119, 140], "els": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 27, 28, 29, 30, 31, 32, 67, 119], "cpu": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 32, 67, 119], "backend": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32, 132, 140], "cudnn": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32, 132, 140], "benchmark": [2, 3, 4, 5, 8, 9, 10, 11, 15, 23, 24, 27, 28, 29, 30, 31, 32, 70, 74, 76, 84, 96, 109, 112, 118, 132, 140], "set": [2, 4, 8, 9, 10, 11, 12, 14, 16, 17, 19, 22, 26, 27, 29, 30, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 62, 67, 69, 70, 72, 84, 88, 89, 90, 96, 97, 98, 101, 103, 105, 108, 111, 112, 113, 119, 132, 138, 140], "random": [2, 3, 4, 5, 8, 9, 10, 11, 26, 27, 28, 30, 31, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 72, 120, 121, 122, 123, 127, 132, 140], "seed": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 60, 132], "abl": [2, 3, 4, 5, 8, 9, 10, 11, 12, 27, 28, 30, 67, 119, 135], "roughli": [2, 3, 4, 5, 8, 9, 11, 27, 28, 72], "reproduc": [2, 3, 4, 5, 8, 9, 10, 11, 24, 27, 28, 30, 132, 140], "note": [2, 3, 4, 5, 8, 9, 11, 17, 20, 26, 27, 28, 42, 58, 67, 68, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 108, 111, 119, 127, 132], "indetermin": [2, 3, 4, 5, 8, 9, 11, 27, 28], "still": [2, 3, 4, 5, 8, 9, 11, 27, 28, 29, 72], "make": [2, 3, 4, 5, 8, 9, 11, 12, 27, 28, 29, 30, 32, 99, 107, 135, 140], "substanti": [2, 3, 4, 5, 8, 9, 10, 11, 14, 19, 27, 28], "between": [2, 3, 4, 5, 8, 9, 11, 26, 27, 28, 29, 36, 37, 38, 41, 42, 45, 46, 47, 48, 49, 53, 54, 55, 57, 59, 62, 69, 78, 79, 80, 84, 86, 96, 97, 105, 112, 113, 123, 128], "consist": [2, 3, 4, 5, 8, 9, 11, 27, 28, 47, 48, 49, 69, 72], "cost": [2, 3, 4, 5, 8, 9, 11, 27, 28], "increas": [2, 3, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 32, 90, 99], "cudnn_benchmark": [2, 3, 4, 5, 8, 9, 11, 27, 28, 132], "fals": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 22, 26, 27, 28, 29, 30, 31, 32, 41, 45, 46, 47, 48, 49, 59, 63, 67, 68, 70, 71, 74, 75, 76, 77, 80, 82, 83, 84, 85, 86, 91, 96, 97, 98, 99, 100, 103, 105, 109, 111, 112, 113, 114, 117, 118, 119, 122, 123, 125, 126, 132, 134, 140], "20200220": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "n_class": [2, 3, 4, 9, 10, 11, 14, 26, 27, 28, 29, 30, 31, 32, 67, 83, 84, 85, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 101, 103, 119, 124, 128, 130], "number": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 22, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 60, 63, 65, 67, 70, 74, 75, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 110, 112, 113, 117, 118, 119, 120, 121, 122, 123, 130, 131], "chan": [2, 3, 4, 8, 27, 28, 29, 30, 32, 72], "n_chan": [2, 8, 11, 26, 27, 28, 30, 31, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 119], "shape": [2, 3, 4, 5, 8, 9, 10, 11, 17, 20, 22, 26, 27, 28, 29, 30, 32, 46, 63, 67, 85, 86, 91, 95, 97, 98, 99, 100, 101, 102, 103, 104, 123, 124, 128], "final_conv_length": [2, 3, 4, 8, 14, 26, 27, 28, 29, 30, 31, 32, 84, 92, 93, 96, 140], "2": [2, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 30, 31, 36, 37, 38, 41, 42, 43, 45, 51, 54, 59, 60, 62, 65, 67, 69, 72, 74, 83, 84, 88, 89, 91, 92, 93, 94, 97, 99, 101, 103, 107, 111, 116, 119, 120, 121, 129, 130], "add_log_softmax": [2, 8, 26, 31, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103], "send": [2, 3, 4, 8, 9, 10, 11, 16, 27, 28, 29, 30, 32], "get_output_shap": [2, 27, 31, 91, 140], "to_dense_prediction_model": [2, 27, 31, 91, 140], "local": [2, 5, 10, 11, 14, 27, 31, 32, 68, 111, 135, 139], "lib": [2, 5, 10, 11, 27, 31, 32], "python3": [2, 5, 10, 11, 27, 31, 32], "site": [2, 5, 10, 11, 27, 31, 32], "packag": [2, 5, 10, 11, 27, 31, 32, 34, 137, 138], "deprec": [2, 5, 10, 19, 31, 88, 140], "86": [2, 5, 11, 16, 31], "futurewarn": [2, 26, 30, 31, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103], "version": [2, 3, 4, 5, 9, 10, 18, 20, 21, 22, 29, 30, 31, 67, 86, 91, 105, 106, 107, 108, 110, 111, 119, 135, 137, 138, 139], "eegmodulemixin": [2, 31, 140], "method": [2, 4, 5, 8, 12, 16, 21, 26, 29, 31, 32, 34, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 67, 68, 70, 71, 77, 83, 85, 86, 90, 91, 95, 96, 97, 98, 99, 100, 101, 102, 103, 107, 109, 111, 119, 120, 121, 122, 124, 125, 126, 127, 128, 140], "msg": [2, 31], "categori": [2, 4, 31], "calcul": [2, 3, 4, 27, 28, 29, 30, 32, 67, 101, 119], "output": [2, 3, 4, 5, 11, 12, 14, 21, 26, 27, 28, 29, 30, 31, 32, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 107, 108, 110, 111, 112, 113, 119], "dummi": [2, 27], "n_preds_per_input": [2, 27, 31], "create_fixed_length_window": [2, 5, 12, 14, 16, 22, 31, 140], "It": [2, 3, 4, 8, 9, 10, 11, 18, 27, 28, 29, 30, 32, 41, 59, 67, 70, 77, 80, 99, 113, 119, 136], "defin": [2, 5, 9, 10, 11, 12, 14, 20, 21, 27, 28, 30, 39, 53, 56, 67, 77, 83, 86, 90, 101, 113, 119, 122], "start_offset_sampl": [2, 14, 22, 31, 112], "stop_offset_sampl": [2, 14, 22, 31, 112, 140], "none": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 18, 19, 20, 22, 26, 27, 28, 29, 31, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 57, 59, 60, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 108, 110, 111, 112, 113, 114, 115, 116, 118, 119, 120, 121, 122, 123, 125, 126, 127, 132, 134, 140], "window_size_sampl": [2, 5, 8, 9, 10, 11, 12, 14, 17, 19, 22, 27, 31, 78, 79, 80, 112, 113, 114], "window_stride_sampl": [2, 5, 9, 10, 11, 12, 14, 17, 19, 22, 27, 31, 78, 79, 80, 112, 113], "drop_last_window": [2, 12, 14, 17, 19, 22, 27, 31, 78, 79, 80, 112, 113], "targets_from": [2, 77, 112, 119], "last_target_onli": [2, 8, 77, 112, 114], "preload": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 22, 27, 28, 29, 30, 31, 32, 74, 75, 76, 80, 81, 111, 112, 113, 114, 118, 140], "thumb": [2, 8, 27], "": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 21, 22, 26, 27, 28, 30, 31, 32, 39, 41, 43, 46, 47, 48, 49, 56, 59, 60, 63, 67, 68, 69, 71, 72, 73, 74, 75, 76, 83, 89, 90, 92, 93, 98, 100, 103, 106, 107, 109, 111, 119, 120, 124, 127, 128], "consid": [2, 4, 29, 32, 47, 48, 49, 67, 119, 127], "well": [2, 5, 8, 12, 26, 27, 28, 29, 32, 80, 113, 136, 140], "encourag": [2, 8, 24, 27, 28], "find": [2, 4, 8, 30], "wai": [2, 5, 8, 16, 21, 24, 26, 29, 99, 137, 139], "target_transform": [2, 8, 9, 10, 70, 140], "suppli": [2, 3, 5, 8, 9, 10, 11, 27, 28, 29], "eegclassifi": [2, 5, 9, 10, 11, 26, 27, 28, 29, 30, 140], "croppedloss": [2, 27, 31], "criterion": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 67, 119], "criterion__loss_funct": [2, 27, 31], "loss": [2, 3, 4, 5, 8, 9, 10, 11, 14, 26, 27, 28, 29, 30, 31, 32, 67, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 119, 124, 128, 129], "mean": [2, 3, 4, 8, 10, 12, 14, 16, 19, 26, 27, 29, 30, 31, 32, 72, 84, 93, 96, 111, 115, 116, 119, 135], "default": [2, 8, 11, 12, 27, 28, 30, 31, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 67, 68, 74, 75, 76, 77, 80, 83, 84, 86, 88, 89, 90, 91, 105, 106, 107, 108, 110, 111, 113, 119, 127, 132, 140], "found": [2, 8, 10, 12, 16, 18, 19, 20, 26, 27, 28, 29, 32, 68, 111, 112, 113], "motor": [2, 4, 8, 27, 28, 69, 72, 83, 87, 90, 140], "strongli": [2, 8, 27, 28, 88, 89, 90], "hyperparamet": [2, 5, 8, 9, 10, 11, 14, 24, 25, 27, 28, 32, 33, 45, 67, 70, 73, 91, 96, 109, 113, 116, 118, 119, 132, 140], "optim": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32, 67, 72, 119], "cross": [2, 8, 16, 27, 28, 69], "skorch": [2, 3, 4, 5, 8, 9, 10, 11, 17, 26, 27, 28, 29, 30, 31, 67, 78, 79, 80, 119, 140], "callback": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32, 67, 119, 127], "lrschedul": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "helper": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31], "predefined_split": [2, 3, 5, 8, 9, 10, 11, 27, 28, 29, 31], "eegregressor": [2, 8, 26, 31, 140], "croppedtimeseriesepochscor": 2, "timeseriesloss": 2, "valu": [2, 4, 5, 8, 9, 10, 11, 12, 26, 27, 28, 30, 31, 32, 42, 45, 62, 67, 70, 71, 77, 80, 90, 101, 107, 108, 110, 111, 112, 113, 119, 128, 129, 130, 140], "good": [2, 8, 26, 27, 28], "mi": [2, 8], "lr": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32, 67, 119], "0625": [2, 3, 4, 8, 27, 28, 29, 32], "01": [2, 3, 4, 6, 8, 12, 16, 23, 26, 27, 28, 29, 32, 33, 67, 88, 89, 119], "weight_decai": [2, 3, 4, 8, 27, 28, 29, 32], "batch_siz": [2, 3, 4, 5, 8, 9, 10, 11, 14, 22, 27, 28, 29, 30, 31, 32, 36, 45, 46, 54, 62, 63, 67, 85, 86, 91, 95, 97, 98, 99, 100, 101, 102, 104, 119, 124, 128, 130, 133], "27": [2, 4, 9, 11, 16, 23, 27, 29, 72], "64": [2, 3, 4, 8, 10, 11, 14, 16, 17, 19, 27, 28, 29, 30, 32, 83, 93, 98], "n_epoch": [2, 3, 4, 5, 8, 9, 10, 11, 14, 27, 28, 29, 30, 31, 32], "8": [2, 3, 4, 5, 6, 8, 9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 23, 26, 27, 28, 29, 30, 31, 32, 33, 83, 86, 88, 89, 92, 93, 98, 117, 137], "regressor": [2, 8, 26, 31, 140], "aggregate_predict": [2, 67, 119], "mse_loss": [2, 31], "adamw": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "train_split": [2, 3, 4, 5, 8, 9, 10, 11, 26, 27, 28, 29, 30, 31, 67, 119], "optimizer__lr": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 67, 119], "optimizer__weight_decai": [2, 3, 4, 8, 27, 28, 29, 31], "iterator_train__shuffl": [2, 5, 9, 10, 11, 27, 31, 67, 119], "lr_schedul": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "cosineannealinglr": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "t_max": [2, 3, 4, 8, 27, 28, 29, 30, 31, 32], "r2_train": 2, "metric": [2, 5, 9, 10, 11, 27, 28, 32, 134], "r2_score": 2, "lower_is_bett": [2, 5, 8, 9, 10, 11, 125, 126, 127], "on_train": [2, 5, 8, 9, 10, 11, 125, 126], "r2_valid": 2, "verbos": [2, 3, 4, 8, 29, 30, 67, 68, 105, 107, 108, 110, 111, 112, 113, 114, 119, 140], "specifi": [2, 3, 5, 8, 9, 10, 11, 12, 18, 21, 22, 26, 27, 28, 29, 67, 68, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107, 111, 118, 119], "y": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 20, 22, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 48, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 78, 79, 80, 85, 86, 90, 110, 119, 127], "alreadi": [2, 3, 5, 8, 9, 10, 11, 14, 19, 27, 28, 29, 70, 71, 77, 118, 119, 135, 137], "fit": [2, 3, 5, 8, 9, 10, 11, 14, 24, 26, 27, 28, 29, 30, 31, 32, 67, 113, 119], "train_loss": [2, 3, 5, 8, 9, 10, 11, 27, 28, 29, 30, 31, 32, 67, 119], "valid_loss": [2, 3, 5, 8, 9, 10, 11, 26, 27, 28, 29, 30, 31], "dur": [2, 3, 5, 8, 9, 10, 11, 26, 27, 28, 29, 30, 31], "16": [2, 3, 5, 6, 9, 11, 16, 27, 30, 32, 83, 93, 98, 107], "9037": 2, "3086": 2, "5378": 2, "20": [2, 5, 6, 9, 10, 11, 12, 16, 26, 27, 29, 31, 32, 39, 46, 47, 48, 49, 63, 97, 111], "7324": 2, "0006": [2, 3, 8, 27, 28, 29], "5038": [2, 9], "13": [2, 5, 9, 11, 16, 17, 19, 26, 32, 72, 74, 107, 117], "7539": 2, "7": [2, 3, 4, 5, 9, 10, 11, 13, 16, 17, 18, 19, 20, 21, 26, 27, 28, 29, 30, 31, 32, 34, 72, 83, 90, 91, 97], "1244": 2, "9596": 2, "18": [2, 4, 5, 11, 12, 16, 27, 90], "0720": 2, "4052": 2, "12": [2, 4, 5, 10, 11, 13, 16, 17, 18, 19, 27, 28, 29, 30, 32, 33, 69, 103, 134], "7768": 2, "7402": 2, "6787": 2, "17": [2, 5, 11, 16, 27, 101], "1870": 2, "0005": [2, 3, 22, 28, 31], "4036": 2, "7970": 2, "3910": 2, "5638": 2, "4409": 2, "0004": 2, "4095": 2, "2712": [2, 10], "1840": 2, "4237": 2, "0095": 2, "0002": [2, 3, 28], "4032": 2, "5735": 2, "9203": 2, "3549": 2, "15": [2, 5, 9, 10, 11, 12, 14, 16, 26, 27, 28, 29, 30, 32, 46, 47, 48, 49, 86, 96, 101, 107, 110], "4436": 2, "0001": [2, 30, 94, 116], "9": [2, 3, 4, 5, 8, 9, 10, 11, 13, 16, 17, 18, 19, 20, 21, 23, 26, 27, 28, 29, 30, 32, 33, 69, 72, 88, 90, 103, 111], "8228": 2, "6181": 2, "3132": 2, "14": [2, 5, 8, 9, 11, 16, 17, 19, 27, 28, 32, 72, 107, 132], "7799": 2, "0000": [2, 3, 8, 27, 28, 29, 30, 31], "4031": 2, "0643": 2, "3047": 2, "3316": 2, "0884": 2, "4024": 2, "def": [2, 3, 5, 8, 9, 10, 11, 12, 14, 16, 29, 31, 32], "pad_and_select_predict": 2, "pred": [2, 8, 32, 124, 128, 129, 131], "pad": [2, 9, 10, 11, 27, 98, 107, 110, 140], "constant": 2, "constant_valu": 2, "mask": [2, 5, 51, 65, 128], "isnan": 2, "squeez": [2, 3, 4, 26, 27, 28, 29, 30, 32], "return": [2, 5, 8, 9, 10, 11, 12, 14, 17, 19, 21, 29, 30, 31, 32, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 64, 65, 66, 67, 70, 71, 75, 76, 77, 78, 79, 80, 81, 85, 86, 91, 97, 98, 99, 102, 103, 104, 105, 106, 107, 108, 110, 111, 112, 113, 115, 116, 117, 118, 119, 120, 121, 127, 129, 130, 131, 134, 140], "t": [2, 4, 5, 11, 17, 19, 26, 27, 28, 29, 30, 31, 32, 41, 59, 67, 68, 69, 84, 95, 96, 103, 105, 115, 116, 119, 132, 134], "preds_train": [2, 8], "y_train": [2, 8, 9, 10, 11, 29], "predict_tri": [2, 67, 119, 140], "return_target": [2, 67, 119, 130], "preds_valid": [2, 8], "y_valid": [2, 8], "preds_test": [2, 8], "y_test": [2, 8, 29], "decreas": [2, 8, 11], "doe": [2, 8, 14, 16, 18, 27, 29, 32, 44, 67, 83, 91, 113, 119, 135], "divers": [2, 4, 8], "caus": [2, 8], "overfit": [2, 8, 9, 10, 11, 29], "better": [2, 5, 8, 10, 14, 16, 27, 28, 29, 32, 86, 127, 140], "improv": [2, 3, 5, 8, 9, 10, 11, 32, 107, 135, 140], "matplotlib": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 31, 134], "pyplot": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 31], "plt": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 31], "panda": [2, 4, 5, 8, 9, 10, 11, 14, 16, 20, 21, 27, 28, 29, 30, 31, 67, 70, 71, 77, 80, 119], "pd": [2, 4, 5, 8, 9, 10, 11, 14, 16, 27, 28, 29, 30, 31, 70, 71, 77, 120, 121, 122, 123], "line": [2, 8, 14, 27, 28, 31, 69, 135], "line2d": [2, 8, 27, 28], "fig": [2, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 30, 31, 134], "ax": [2, 3, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 30, 31, 91], "subplot": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 31], "figsiz": [2, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 31, 134], "set_titl": [2, 8, 16, 31], "arang": [2, 8], "label": [2, 3, 5, 8, 9, 10, 11, 12, 16, 22, 26, 27, 28, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 102, 119, 122, 124, 128, 130, 134], "set_ylabel": [2, 5, 8, 9, 10, 11, 16, 27, 28, 31], "legend": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 31], "set_xlabel": [2, 4, 5, 8, 9, 10, 11, 16, 27, 28, 31], "tight_layout": [2, 4, 5, 8, 9, 10, 11, 27, 28, 30], "correl": [2, 8, 27, 29], "coeffici": [2, 8, 45, 62, 129], "corr_coeff": [2, 8], "dim": [2, 8], "rang": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 26, 27, 28, 29, 31, 32, 41, 59, 68, 117, 134], "append": [2, 8, 12, 14, 16, 27, 28, 31, 67, 107, 119], "corrcoef": [2, 8], "print": [2, 4, 5, 8, 9, 10, 11, 14, 17, 20, 21, 22, 26, 27, 28, 29, 30, 32, 67, 119, 135], "dimens": [2, 5, 8, 51, 65, 83, 86, 99, 103, 110, 140], "round": [2, 8], "histori": [2, 5, 8, 9, 10, 11, 27, 28, 31, 67, 119], "throughout": [2, 8, 9, 10, 11, 28, 29, 32], "accuraci": [2, 3, 4, 5, 8, 9, 10, 11, 27, 28, 29, 30, 32, 127, 140], "curv": [2, 8, 28], "results_column": [2, 8, 27, 28], "df": [2, 5, 8, 9, 10, 11, 12, 16, 27, 28], "datafram": [2, 4, 5, 8, 9, 10, 11, 14, 16, 20, 21, 22, 27, 28, 29, 30, 67, 70, 119, 120, 121, 122, 123], "index": [2, 5, 8, 9, 10, 11, 17, 27, 28, 30, 31, 71, 105, 115, 116, 120, 121, 131, 137], "ax1": [2, 5, 8, 9, 10, 11, 27, 28], "loc": [2, 8, 12, 26, 27, 28, 29], "style": [2, 5, 8, 27, 28, 47, 48, 49, 101], "marker": [2, 5, 8, 16, 27, 28], "o": [2, 4, 5, 8, 16, 27, 28, 36, 37, 38, 39, 43, 51, 54, 55, 56, 57, 60, 65, 122], "color": [2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 134], "tab": [2, 5, 8, 16, 27, 28], "blue": [2, 5, 8, 16, 27, 28], "fontsiz": [2, 8, 12, 27, 28], "tick_param": [2, 5, 8, 12, 27, 28], "axi": [2, 3, 5, 8, 27, 28, 31, 46, 47, 48, 49, 50, 52, 63, 64, 66, 91, 110, 131], "labelcolor": [2, 5, 8, 27, 28], "labels": [2, 8, 12, 27, 28], "ax2": [2, 5, 8, 9, 10, 11, 27, 28], "twinx": [2, 5, 8, 27, 28], "instanti": [2, 3, 4, 8, 14, 26, 27, 28, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 60, 67, 73, 119, 140], "share": [2, 8, 14, 27, 28], "red": [2, 8, 27, 28], "r2": [2, 8], "score": [2, 4, 5, 9, 10, 11, 29, 30, 67, 85, 97, 119, 125, 126, 127, 140], "where": [2, 4, 8, 9, 10, 22, 27, 28, 29, 36, 45, 46, 51, 54, 62, 63, 65, 67, 68, 70, 78, 119, 130, 132, 140], "been": [2, 3, 4, 8, 10, 14, 16, 18, 20, 21, 27, 28, 29, 30, 32, 87, 88, 89, 90, 91, 92, 93, 129, 135, 139, 140], "handl": [2, 3, 4, 8, 27, 28, 30, 111], "black": [2, 8, 12, 27, 28, 69, 72, 134], "linewidth": [2, 8, 27, 28], "linestyl": [2, 8, 12, 27, 28], "h": [2, 4, 5, 8, 27, 28, 36, 39, 43, 51, 54, 56, 60, 65, 83, 85, 87, 122], "get_label": [2, 8, 27, 28], "center": [2, 8, 9, 10, 29, 36, 54], "right": [2, 4, 8, 12, 27, 28, 29, 32, 39, 69, 72, 139], "total": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 33, 69], "script": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 132], "minut": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 74], "41": [2, 5, 6, 11, 16, 27], "420": [2, 6], "estim": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32], "usag": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 135, 140], "777": [2, 6], "mb": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32, 33], "python": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 34, 105, 132, 136, 137, 139, 140], "sourc": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 136, 137], "plot_bcic_iv_4_ecog_crop": [2, 6], "jupyt": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32], "notebook": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32], "ipynb": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32], "galleri": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32], "gener": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 32, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 67, 91, 97, 100, 107, 119, 127, 134, 140], "sphinx": [2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30, 31, 32], "follow": [3, 4, 5, 9, 10, 11, 14, 26, 29, 32, 88, 89, 107, 110, 113, 119, 137, 138, 139, 140], "wise": [3, 4, 5, 9, 10, 11], "also": [3, 4, 5, 9, 10, 11, 12, 14, 18, 21, 26, 28, 34, 67, 77, 86, 88, 89, 99, 107, 108, 110, 119, 130, 135, 138, 139], "illustr": [3, 29], "effect": [3, 19], "simon": [3, 20, 140], "brandt": [3, 20, 140], "simonbrandt": [3, 20], "protonmail": [3, 20], "c\u00e9dric": [3, 4], "rommel": [3, 4, 140], "cedric": [3, 4, 140], "inria": [3, 4, 11], "fr": [3, 4, 11], "moabbdataset": [3, 4, 18, 20, 21, 27, 28, 29, 30, 32, 140], "dataset_nam": [3, 4, 18, 20, 21, 27, 28, 29, 30, 32, 73], "bnci2014001": [3, 4, 18, 20, 21, 29, 30], "renam": [3, 4, 12, 18, 20, 21, 29, 30, 140], "bnci2014_001": [3, 4, 18, 20, 21, 27, 28, 29, 30, 32], "must": [3, 4, 12, 14, 16, 18, 20, 21, 26, 29, 30, 77, 84, 96, 97, 102, 105, 109, 111, 112, 120, 138, 140], "abbrevi": [3, 4, 18, 20, 21, 29, 30], "its": [3, 4, 9, 10, 16, 18, 20, 21, 26, 29, 30, 31, 67, 70, 109, 119], "bnci2014": [3, 4, 18, 20, 21, 29, 30], "001": [3, 4, 18, 20, 21, 27, 28, 29, 30, 31, 69, 115, 116], "moabb": [3, 4, 15, 18, 21, 23, 24, 27, 28, 29, 30, 32, 69, 70, 72, 73, 109, 118, 138, 139, 140], "is_abbrev": [3, 4, 18, 20, 21, 29, 30], "inform": [3, 4, 12, 14, 17, 18, 20, 26, 29, 30, 41, 59, 67, 70, 77, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 119, 121, 139], "multipli": [3, 4, 5, 9, 10, 12, 27, 28, 29, 30, 32, 83, 88, 89], "cut": [3, 4, 19, 28, 29, 30, 36, 54, 78, 107], "38": [3, 4, 11, 16, 27, 28, 29, 30, 31, 32], "factor": [3, 4, 5, 9, 10, 12, 27, 28, 29, 30, 32, 99, 101, 103, 110], "meg": [3, 4, 20, 27, 28, 29, 30, 32, 34, 107, 108, 136], "stim": [3, 4, 20, 27, 28, 29, 30, 32], "keep": [3, 4, 10, 11, 16, 27, 28, 29, 30, 32, 72, 74, 140], "sensor": [3, 4, 27, 28, 29, 30, 32, 39, 46, 47, 48, 49, 63, 72], "0x7f3131301330": 3, "create_windows_from_ev": [3, 4, 5, 9, 10, 11, 18, 21, 27, 28, 29, 30, 32, 140], "trial_start_offset_second": [3, 4, 27, 28, 29, 30, 32], "start": [3, 4, 12, 14, 16, 22, 27, 28, 29, 30, 32, 51, 65, 67, 80, 105, 110, 112, 113, 119, 137], "offset": [3, 4, 16, 18, 27, 28, 29, 30, 32, 70, 80, 112, 113], "trial_start_offset_sampl": [3, 4, 5, 9, 10, 11, 18, 19, 21, 27, 28, 29, 30, 32, 80, 113], "int": [3, 4, 5, 9, 10, 14, 16, 26, 27, 28, 29, 30, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 65, 67, 68, 69, 70, 72, 73, 74, 75, 76, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 108, 110, 111, 112, 113, 115, 116, 118, 119, 120, 121, 122, 123, 130, 132, 134], "windows_dataset": [3, 4, 5, 8, 9, 10, 11, 17, 18, 19, 27, 28, 29, 30, 31, 32, 78, 79, 80, 112, 113], "trial_stop_offset_sampl": [3, 4, 5, 9, 10, 11, 18, 19, 21, 27, 28, 29, 30, 31, 32, 80, 113, 140], "0train": [3, 4, 18, 20, 21, 27, 28, 29, 30, 32], "1test": [3, 4, 20, 21, 27, 28, 29, 30, 32], "callabl": [3, 26, 40, 53, 67, 70, 71, 77, 84, 96, 109, 119, 127], "custom": [3, 4, 15, 23, 24, 35, 70, 78], "loader": [3, 4, 5, 14, 32], "call": [3, 16, 26, 27, 29, 32, 67, 70, 77, 80, 83, 86, 90, 105, 109, 112, 113, 119, 125, 126, 127], "demonstr": [3, 4, 7, 22, 24, 26, 32], "below": [3, 5, 34, 36, 135, 138, 140], "illutr": 3, "purpos": [3, 14, 16, 32], "chose": 3, "frequencyshift": 3, "randomli": [3, 5, 27, 36, 37, 38, 43, 51, 55, 57, 60, 123], "translat": 3, "within": [3, 4, 72, 83, 86, 90, 101, 122, 140], "given": [3, 4, 5, 21, 32, 37, 38, 39, 41, 50, 52, 53, 67, 68, 81, 107, 108, 111, 119, 130, 140], "probabl": [3, 4, 26, 30, 32, 36, 37, 38, 39, 41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 67, 83, 84, 87, 96, 100, 101, 119], "actual": [3, 5, 12, 14, 22], "modifi": [3, 5, 10, 12, 41, 59, 67, 91, 105, 106, 108, 109, 117, 119, 132], "max_delta_freq": [3, 42], "shift": [3, 29, 42, 58], "next": [3, 4, 5, 9, 10, 11, 12, 14, 16, 18, 22], "let": [3, 4, 22, 26], "u": [3, 5, 7, 13, 24, 30, 70, 74, 91, 103, 109, 113, 118, 120, 121, 123, 132, 134, 139, 140], "result": [3, 12, 14, 16, 29, 32, 67, 80, 110, 113, 119, 127, 132, 135], "stack": [3, 8], "allow": [3, 5, 14, 26, 29, 30, 32, 40, 67, 80, 88, 89, 113, 119, 140], "fix": [3, 39, 56, 135, 140], "instead": [3, 4, 5, 8, 22, 27, 28, 29, 30, 31, 32, 67, 83, 86, 88, 90, 91, 111, 119, 140], "x_tr": 3, "_": [3, 5, 14, 16, 17, 26, 27, 28, 31, 32, 140], "as_tensor": 3, "float": [3, 5, 26, 31, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 57, 58, 59, 60, 63, 67, 74, 78, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 101, 103, 105, 107, 110, 113, 115, 116, 119, 129, 134], "psd": 3, "plot": [3, 5, 12, 14, 16, 29, 31, 140], "plot_psd": 3, "freq": 3, "time_frequ": 3, "psd_array_multitap": 3, "fmin": 3, "fmax": 3, "100": [3, 4, 5, 8, 9, 10, 11, 12, 14, 16, 20, 26, 27, 28, 29, 30, 31, 32, 36, 51, 69, 84, 103, 110], "log10": 3, "psds_mean": 3, "origin": [3, 11, 17, 19, 26, 29, 45, 46, 47, 48, 49, 51, 62, 63, 65, 70, 80, 86, 87, 88, 89, 90, 92, 93, 113, 117], "k": [3, 5, 9, 10, 11, 26, 27, 28, 30, 31, 32, 36, 43, 46, 47, 48, 49, 51, 54, 60, 63, 65, 84, 90, 95, 96, 134], "r": [3, 5, 9, 10, 11, 26, 27, 28, 29, 30, 31, 36, 43, 51, 54, 60, 65, 84, 88, 89, 92, 93, 95, 96, 134], "titl": [3, 12, 29, 30, 34], "multitap": 3, "gradiomet": 3, "xlabel": [3, 12, 29, 30], "ylabel": [3, 12, 30], "power": [3, 5, 30, 107, 110], "spectral": 3, "densiti": 3, "db": [3, 16, 111], "them": [3, 4, 5, 12, 14, 16, 17, 19, 26, 27, 29, 32, 67, 70, 83, 84, 85, 86, 90, 91, 94, 95, 96, 97, 98, 99, 100, 103, 119, 139], "try": [3, 4, 12, 18, 22, 24, 30, 135, 139], "comput": [3, 4, 5, 9, 10, 11, 18, 22, 34, 47, 48, 49, 67, 69, 80, 83, 86, 88, 89, 90, 92, 93, 97, 111, 113, 115, 116, 119, 124, 125, 126, 128, 132, 135, 139, 140], "list": [3, 5, 11, 14, 16, 21, 22, 26, 27, 28, 29, 31, 32, 34, 35, 39, 40, 47, 48, 49, 56, 67, 68, 69, 70, 72, 73, 74, 75, 76, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 106, 107, 108, 111, 112, 113, 117, 118, 119, 129, 131, 134, 140], "n_channel": [3, 4, 5, 9, 10, 14, 17, 19, 22, 29, 31, 32, 45, 46, 62, 63, 78, 83, 85, 86, 95, 97, 98, 99, 100, 101, 102, 115, 116], "auto": [3, 4, 8, 14, 17, 19, 26, 28, 29, 30, 32, 67, 84, 92, 93, 96, 107, 110, 111, 119, 140], "23": [3, 4, 5, 8, 9, 10, 11, 16, 27, 28, 29, 30, 31, 32, 106], "depreci": [3, 4, 8, 27, 28, 29, 30, 31, 32], "n_time": [3, 4, 5, 8, 9, 10, 11, 12, 14, 17, 19, 26, 27, 28, 29, 30, 31, 32, 45, 62, 78, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 115, 116, 119, 124, 128], "180": [3, 4, 11, 26, 27, 28, 29, 30, 32], "logsoftmax": [3, 4, 26, 27, 28, 29, 30, 32, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 140], "layer": [3, 4, 5, 9, 10, 11, 26, 27, 28, 29, 30, 31, 32, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 140], "adjust": [3, 4, 26, 27, 28, 29, 30, 32, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103], "accordingli": [3, 4, 9, 26, 27, 28, 29, 30, 32, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 105], "e": [3, 4, 5, 9, 10, 11, 14, 16, 26, 27, 28, 29, 30, 32, 36, 39, 43, 51, 53, 54, 56, 60, 65, 67, 71, 74, 75, 76, 77, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 105, 106, 107, 108, 109, 113, 117, 119, 123, 127, 134, 139, 140], "g": [3, 4, 5, 9, 10, 11, 14, 16, 26, 27, 28, 29, 30, 32, 36, 39, 41, 43, 51, 53, 54, 56, 59, 60, 67, 71, 74, 75, 76, 77, 80, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 100, 101, 102, 103, 105, 106, 107, 108, 109, 113, 117, 119, 123, 127, 134, 140], "crossentropyloss": [3, 4, 9, 10, 11, 26, 27, 28, 29, 30, 32, 67, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 119], "order": [3, 4, 12, 21, 26, 39, 47, 48, 49, 56, 67, 72, 75, 76, 107, 111, 117, 119, 123, 140], "pass": [3, 4, 9, 10, 11, 16, 22, 26, 27, 28, 29, 30, 32, 35, 40, 53, 67, 73, 83, 85, 86, 90, 95, 97, 98, 99, 100, 101, 105, 107, 108, 110, 111, 119, 124, 127, 128, 140], "sequenti": [3, 4, 5, 9, 10, 11, 16, 26, 27, 28, 29, 30, 32, 72, 91], "batch": [3, 4, 5, 26, 30, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 64, 65, 66, 67, 84, 85, 91, 95, 96, 97, 98, 99, 100, 101, 104, 119, 126, 130, 140], "augmenteddataload": [3, 4, 140], "signflip": 3, "freq_shift": 3, "sign_flip": 3, "iter": [3, 4, 5, 20, 22, 45, 67, 91, 106, 119, 130], "argument": [3, 4, 16, 19, 26, 29, 32, 35, 37, 38, 39, 41, 50, 52, 53, 67, 73, 105, 107, 108, 109, 110, 111, 117, 119, 127, 140], "clf": [3, 4, 5, 9, 10, 11, 27, 28, 29, 30], "iterator_train": [3, 4, 67, 119], "tell": [3, 4, 135], "dataload": [3, 4, 5, 14, 32, 35, 67, 119, 130], "iterator_train__transform": [3, 4], "nllloss": [3, 4, 14, 28, 29, 30, 32, 67], "train_accuraci": [3, 27, 28, 29, 30, 32], "valid_acc": [3, 5, 9, 10, 11, 26, 28, 29, 30], "valid_accuraci": [3, 27, 28, 29, 30], "2500": [3, 22, 28, 29, 121], "6077": 3, "0179": 3, "7346": 3, "2569": 3, "3809": 3, "1898": 3, "5458": 3, "3021": 3, "2767": 3, "2604": [3, 27], "7960": 3, "5160": 3, "3229": 3, "1763": 3, "2674": [3, 28], "6417": 3, "5309": 3, "classifi": [3, 4, 5, 9, 10, 11, 26, 29, 31, 140], "initi": [3, 5, 9, 10, 11, 26, 29, 30, 32, 67, 86, 88, 89, 103, 119], "module_": [3, 9, 10, 11, 26, 67, 119], "var_nam": [3, 4, 11, 26, 27, 28, 29, 32, 91], "depth": [3, 4, 11, 26, 27, 28, 29, 30, 32, 83, 88, 89, 91, 103], "idx": [3, 4, 9, 10, 11, 26, 27, 28, 29, 30, 32], "param": [3, 4, 5, 11, 26, 27, 28, 29, 30, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 51], "kernel": [3, 4, 11, 26, 27, 28, 29, 30, 32, 46, 47, 48, 49, 63, 83, 89, 90, 97, 98, 100, 103], "22": [3, 4, 5, 9, 11, 16, 17, 19, 27, 28, 29, 32], "1125": [3, 4, 28, 29, 32], "ensure4d": [3, 4, 26, 27, 28, 29, 32], "ensuredim": [3, 4, 26, 27, 28, 29, 32], "rearrang": [3, 4, 26, 27, 28, 29, 32, 140], "dimshuffl": [3, 4, 26, 27, 28, 29, 32], "combinedconv": [3, 4, 26, 27, 28, 29, 32], "conv_time_spat": [3, 4, 26, 27, 28, 29, 32], "40": [3, 4, 11, 14, 16, 26, 27, 28, 29, 31, 32, 86, 96], "1101": [3, 4, 28, 29, 32], "36": [3, 4, 9, 11, 16, 27, 28, 29, 32], "240": [3, 4, 16, 17, 26, 27, 28, 29, 32], "batchnorm2d": [3, 4, 26, 27, 28, 29, 32, 84, 88, 89, 96], "bnorm": [3, 4, 26, 27, 28, 29, 32], "80": [3, 4, 5, 10, 11, 16, 19, 26, 27, 28, 29, 32, 72, 99], "express": [3, 4, 26, 27, 28, 29, 32], "conv_nonlin_exp": [3, 4, 26, 27, 28, 29, 32], "avgpool2d": [3, 4, 26, 27, 28, 29, 32], "pool": [3, 4, 26, 27, 28, 29, 32, 83, 84, 86, 88, 89, 91, 96, 98, 101, 103], "69": [3, 4, 5, 16, 28, 29, 30, 32], "75": [3, 4, 5, 9, 14, 16, 26, 27, 28, 29, 32, 86, 96, 101], "pool_nonlin_exp": [3, 4, 26, 27, 28, 29, 32], "dropout": [3, 4, 5, 9, 10, 26, 27, 28, 29, 30, 32, 83, 84, 86, 87, 88, 89, 96, 97, 98, 99, 100, 101], "drop": [3, 4, 10, 14, 19, 26, 27, 28, 29, 32, 37, 55, 80, 106, 113, 117], "final_lay": [3, 4, 11, 26, 27, 28, 29, 32], "conv2d": [3, 4, 9, 26, 27, 28, 29, 32], "conv_classifi": [3, 4, 26, 27, 28, 29, 32], "044": [3, 4, 28, 29, 32], "47": [3, 4, 5, 9, 10, 11, 16, 27, 28, 29, 32], "364": [3, 4, 28, 29, 32], "trainabl": [3, 4, 11, 26, 27, 28, 29, 32], "non": [3, 4, 11, 16, 22, 26, 27, 28, 29, 30, 32, 67, 72, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 107, 119], "mult": [3, 4, 11, 26, 27, 28, 29, 32], "add": [3, 4, 5, 11, 26, 27, 28, 29, 32, 42, 43, 58, 60, 67, 70, 71, 77, 107, 119, 127, 140], "m": [3, 4, 5, 9, 10, 11, 12, 16, 22, 26, 27, 28, 29, 30, 31, 32, 36, 39, 43, 46, 47, 48, 49, 51, 54, 56, 60, 63, 65, 83, 84, 92, 93, 95, 96, 98, 103, 107, 120, 134, 139], "forward": [3, 4, 5, 11, 26, 27, 28, 29, 32, 40, 53, 67, 83, 85, 86, 90, 95, 97, 98, 99, 100, 101, 102, 103, 107, 109, 111, 119, 124, 128, 130], "backward": [3, 4, 11, 14, 26, 27, 28, 29, 32, 91, 107, 140], "35": [3, 4, 11, 16, 27, 28, 29, 31, 32], "04": [3, 4, 6, 11, 16, 23, 26, 27, 28, 29, 32], "50": [3, 4, 5, 9, 10, 11, 14, 16, 19, 27, 28, 29, 30, 32, 69, 84], "would": [3, 26, 27, 29, 32, 67, 84, 96, 119], "equival": 3, "although": [3, 67, 83, 86, 90, 119], "composit": [3, 40], "composed_transform": 3, "possibl": [3, 4, 11, 12, 16, 18, 26, 67, 69, 112, 119, 132, 135, 140], "most": [3, 9, 10, 11, 14, 122, 135, 138], "windowsdataset": [3, 18, 26, 70, 78, 79, 80, 81, 112, 113, 118, 119, 140], "through": [3, 4, 11, 12, 14, 16, 20, 22, 27, 46, 63, 71, 77, 85, 97, 98, 99, 140], "commonli": 3, "done": [3, 11, 16, 18, 26, 27, 83, 112, 113], "advis": [3, 27, 30, 41, 59, 119], "abov": [3, 14, 16, 22, 27, 29, 135, 137], "compat": [3, 14, 17, 19, 30, 67, 78, 79, 80, 119, 140], "183": [3, 6], "518": 3, "plot_data_augment": [3, 6], "inde": 4, "known": [4, 67], "often": [4, 9, 10, 11, 28, 30], "depend": [4, 5, 9, 10, 11, 12, 14, 16, 26, 29, 30, 32, 34, 67, 72, 99, 119, 130, 137, 139, 140], "task": [4, 9, 10, 11, 26, 30, 41, 59, 69, 71, 122], "phenomenon": 4, "studi": [4, 5, 7, 24], "methodologi": 4, "propos": [4, 37, 38, 41, 51, 55, 57, 59, 65, 90, 140], "openli": [4, 5, 9, 10, 11], "could": [4, 5, 14, 29, 32, 91, 139], "brain": [4, 24, 25, 26, 27, 29, 30, 31, 33, 34, 70, 73, 84, 88, 89, 91, 92, 93, 95, 96, 109, 113, 116, 118, 132, 134, 136], "recent": [4, 26, 135], "shown": [4, 5, 9, 11, 16, 29, 32, 69, 72], "artifici": 4, "cast": [4, 40], "paradigm": [4, 5, 67, 69, 119, 130], "present": [4, 12, 29, 32, 69, 72, 106], "both": [4, 5, 16, 22, 30, 69, 72, 97, 98, 103], "pretext": 4, "approach": [4, 5, 9, 10, 11, 16, 24, 30, 99, 120], "demand": 4, "intens": 4, "comparison": [4, 14, 27, 28], "strength": 4, "context": [4, 5, 29, 34, 99, 122], "bruno": [4, 140], "aristimunha": [4, 140], "ufabc": 4, "br": 4, "bnci": [4, 69], "websit": 4, "There": [4, 24, 26, 84, 96, 137, 139], "subject": [4, 5, 9, 10, 11, 12, 14, 18, 19, 20, 21, 22, 29, 36, 43, 51, 54, 60, 65, 68, 69, 71, 72, 73, 74, 121], "electrod": [4, 20, 69, 72, 111], "while": [4, 5, 14, 29, 32, 72, 83, 86, 90, 97, 131], "do": [4, 12, 14, 26, 27, 29, 32, 67, 78, 79, 80, 103, 112, 113, 119, 123, 132, 139, 140], "imageri": [4, 69, 83, 87, 90, 140], "144": 4, "focu": 4, "relat": [4, 5, 26, 27, 34, 72, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 119, 140], "activ": [4, 19, 26, 67, 72, 83, 84, 88, 89, 90], "0x7f3131677cd0": 4, "out": [4, 8, 9, 10, 26, 36, 51, 54, 65, 67, 69, 119, 120, 128, 135], "provind": 4, "slicedataset": [4, 29, 30], "eval_set": [4, 30], "three": [4, 16, 29, 32, 67, 68, 86, 88, 89, 119, 135], "categor": [4, 120], "aggreg": [4, 86], "sever": [4, 12, 18, 24, 112, 113, 136], "being": [4, 10, 14, 27, 67, 72, 119], "spatial": [4, 26, 41, 59, 84, 96, 103, 140], "paper": [4, 11, 34, 46, 47, 48, 49, 63, 83, 86, 87, 88, 89, 90, 92, 93, 99, 140], "ftsurrog": 4, "smoothtimemask": 4, "channelsdropout": 4, "respect": [4, 5, 30], "two": [4, 5, 9, 10, 11, 12, 14, 16, 18, 27, 29, 32, 45, 51, 62, 69, 72, 74, 90, 97, 107, 110, 111, 122, 123, 129], "insid": [4, 29, 30, 88, 89, 139], "rememb": [4, 29, 32], "\u03c6max": 4, "2\u03c0": 4, "p_drop": [4, 37, 55], "linspac": [4, 12], "transforms_freq": 4, "phase_noise_magnitud": [4, 41, 59], "phase_freq": 4, "random_st": [4, 5, 8, 30, 36, 37, 38, 39, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 120, 121, 122, 123], "transforms_tim": 4, "mask_len_sampl": [4, 51, 65], "transforms_spati": 4, "prob": 4, "gridsearchcv": [4, 29, 30, 127, 140], "control": [4, 5, 10, 29, 67, 97, 105, 107, 108, 110, 111, 112, 113, 118, 119, 140], "over": [4, 10, 16, 29, 31, 32, 41, 46, 47, 48, 49, 59, 63, 67, 119, 140], "framework": 4, "necessari": [4, 67, 111, 119], "slicedata": 4, "mandatori": 4, "eval": [4, 30, 32, 140], "train_x": [4, 30], "train_i": [4, 30], "kfold": [4, 29, 30], "model_select": [4, 5, 8, 29, 30], "cv": [4, 29, 30], "n_split": [4, 29, 30], "shuffl": [4, 8, 14, 29, 30, 32, 38, 45, 57, 67, 119, 140], "fit_param": [4, 30, 119], "param_grid": [4, 29, 30], "return_train_scor": [4, 29, 30], "refit": [4, 29, 30], "error_scor": [4, 29, 30], "rais": [4, 14, 26, 29, 30, 31, 67, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 106, 113, 118, 140], "fold": [4, 30, 32], "candid": [4, 29, 30], "x27": 4, "lt": 4, "gt": 4, "uniniti": [4, 67, 119], "ou": 4, "environ": [4, 68, 132], "rerun": 4, "cell": 4, "represent": [4, 36, 43, 45, 51, 54, 60, 62, 65, 140], "trust": 4, "On": [4, 27, 30, 31, 71, 77], "github": [4, 30, 135, 137, 140], "unabl": 4, "render": 4, "page": [4, 29, 32, 34, 135, 140], "nbviewer": 4, "gridsearchcvgridsearchcv": 4, "analysi": [4, 5, 9, 10, 11, 26, 34, 136], "wa": [4, 5, 9, 10, 11, 27, 28, 29, 32, 67, 69, 72, 86, 99, 119, 120, 140], "search_result": [4, 29, 30], "cv_results_": [4, 29, 30], "best_run": [4, 29, 30], "rank_test_scor": [4, 29, 30], "best_aug": 4, "validation_scor": 4, "around": [4, 10, 32, 46, 47, 48, 49, 63, 113, 120], "mean_test_scor": [4, 30], "training_scor": 4, "mean_train_scor": [4, 30], "report_messag": 4, "gave": [4, 30], "format": [4, 14, 17, 19, 26, 78, 79, 80], "eval_x": [4, 30], "eval_i": [4, 30], "f": [4, 5, 10, 11, 12, 14, 16, 17, 18, 22, 26, 27, 28, 29, 30, 31, 32, 43, 60, 84, 88, 89, 95, 96, 101, 134], "2f": [4, 29, 30, 32], "accuracyof": 4, "78": [4, 11, 16, 74], "28": [4, 9, 11, 16, 27, 30, 33, 88, 89], "00": [4, 6, 10, 13, 16, 23, 26, 27, 32, 33], "bar": 4, "param_iterator_train__transform": 4, "yerr": 4, "std_train_scor": 4, "rot": 4, "45": [4, 5, 11, 16, 29], "c0": 4, "c1": 4, "c2": 4, "strategi": [4, 25, 29, 30], "set_ylim": [4, 27, 28], "32": [4, 5, 9, 10, 11, 16, 26, 27, 29, 30, 33, 83, 92, 101], "c": [4, 5, 9, 10, 11, 20, 27, 28, 29, 30, 41, 59, 85, 90, 92, 93, 103, 120, 135], "paillard": 4, "moreau": [4, 140], "gramfort": [4, 5, 9, 10, 34, 98, 122, 140], "2022": [4, 30, 83, 86, 87, 88, 89], "systemat": 4, "arxiv": [4, 5, 31, 36, 37, 38, 39, 41, 43, 45, 51, 54, 55, 56, 57, 59, 60, 62, 65, 92, 93, 100, 122, 129], "ab": [4, 5, 45, 62, 129], "2206": 4, "14483": 4, "banvil": [4, 5, 9, 14, 16, 20, 122, 140], "chehab": [4, 5, 11, 122, 140], "hyv\u00e4rinen": [4, 5, 122], "engemann": [4, 5, 34, 122, 140], "2021": [4, 10, 11, 88, 89, 90, 99, 103, 120], "uncov": [4, 5, 122], "structur": [4, 5, 16, 17, 19, 121, 122, 140], "clinic": [4, 5, 7, 24, 122], "journal": [4, 28, 29, 30, 34, 90], "engin": [4, 5, 9, 10, 28, 29, 30, 46, 47, 48, 49, 63, 85, 86, 88, 89, 90, 98, 99], "046020": 4, "31": [4, 5, 6, 9, 10, 11, 16, 26, 27, 29, 86], "663": [4, 6], "503": [4, 140], "plot_data_augmentation_search": [4, 6], "access": [5, 9, 10, 11, 12, 14, 26, 87, 121, 137], "physionet": [5, 7, 13, 16, 24, 70, 74, 91, 98, 99, 102, 103, 109, 113, 118, 121, 123, 132, 134, 140], "ssl": [5, 27], "leverag": [5, 99], "unlabel": 5, "design": [5, 16, 99, 107], "prior": [5, 91], "understand": [5, 24, 29], "under": [5, 14, 68, 118, 139, 140], "autocorrel": 5, "requir": [5, 11, 12, 14, 16, 17, 22, 53, 67, 72, 77, 119, 140], "anoth": [5, 21, 29, 32, 122], "interest": [5, 12, 22, 26], "onc": [5, 16, 29, 107, 112, 122, 139], "reus": [5, 9, 11], "featur": [5, 9, 10, 26, 29, 85, 86, 88, 89, 90, 91, 97, 98, 99, 103, 135, 139, 140], "extractor": [5, 9, 10, 85, 97, 98, 99, 103], "weight": [5, 9, 10, 11, 29, 30, 32, 83, 134], "downstream": 5, "help": [5, 9, 10, 21, 111], "reduc": [5, 10, 14, 16, 74, 113], "quantiti": 5, "compar": [5, 14, 16, 22, 27, 29, 32], "strictli": 5, "rp": 5, "simpl": [5, 12, 16, 24, 25, 32, 33, 91, 96], "whether": [5, 14, 26, 37, 38, 39, 41, 46, 47, 48, 49, 50, 52, 53, 59, 63, 67, 70, 77, 78, 79, 80, 81, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 112, 117, 118, 119, 122, 127, 132, 135], "close": [5, 16, 18, 122, 135], "far": [5, 122], "apart": 5, "yield": [5, 14, 20, 69, 101, 135], "physiolog": [5, 9, 10, 11], "relev": [5, 29, 34, 67, 119], "boost": 5, "classif": [5, 9, 10, 11, 26, 27, 30, 36, 41, 43, 51, 54, 59, 60, 65, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101], "regim": 5, "hubert": [5, 9, 14, 16, 20, 140], "jbanvil": [5, 9, 14, 16, 20], "87": [5, 16, 27], "few": [5, 9, 10, 11, 14, 16, 26, 140], "sleep_physionet": [5, 9, 10, 11], "sleepphysionet": [5, 9, 10, 11, 16, 140], "recording_id": [5, 9, 10, 11, 12, 14, 16, 22, 74, 75, 76], "crop_wake_min": [5, 9, 10, 11, 16, 74], "microvolt": [5, 9, 10], "lowpass": [5, 9, 10, 16], "sinc": [5, 9, 10, 11, 12, 22, 26, 30, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 119, 135], "don": [5, 11, 17, 19, 67, 119], "resampl": [5, 12, 14, 18, 20, 74, 107, 140], "0x7f313047dd80": 5, "As": [5, 16, 26, 27, 29, 67, 119], "conveni": [5, 111], "later": [5, 12, 22, 71, 72, 75, 76, 84], "window_size_": [5, 9, 10, 11], "map": [5, 9, 10, 11, 12, 22, 26, 27, 28, 29, 30, 31, 34, 67, 80, 83, 84, 95, 96, 102, 112, 113, 119, 134], "merg": [5, 9, 10, 11, 140], "aasm": [5, 9, 10, 11], "w": [5, 9, 10, 11, 12, 27, 28, 29, 30], "z": [5, 9, 10, 31, 46, 49, 63, 100], "scale": [5, 9, 10, 11, 12, 16, 86, 88, 89, 90, 140], "standard_scal": [5, 9, 10], "channel_wis": [5, 9, 10, 11, 16], "0x7f31313c03d0": 5, "new": [5, 9, 10, 11, 20, 39, 56, 67, 86, 105, 106, 107, 108, 110, 111, 119, 135, 139], "receiv": [5, 86], "pair": [5, 122], "indic": [5, 9, 10, 21, 31, 45, 62, 70, 107, 108, 111, 121, 122, 123, 140], "when": [5, 9, 10, 11, 14, 16, 22, 27, 29, 30, 32, 34, 40, 41, 46, 47, 48, 49, 53, 59, 63, 67, 68, 73, 78, 79, 80, 83, 86, 103, 106, 107, 108, 111, 112, 113, 118, 119, 132, 135, 140], "train_test_split": [5, 8, 29], "uniqu": [5, 9, 10, 11, 21, 67, 71, 119], "subj_train": 5, "subj_test": 5, "test_siz": [5, 8, 29], "subj_valid": 5, "relativepositioningdataset": 5, "__getitem__": [5, 67, 119], "expect": [5, 14, 26, 32, 67, 119], "__init__": [5, 32], "list_of_d": [5, 70], "super": [5, 32, 125, 126], "return_pair": 5, "ind1": 5, "ind2": 5, "properti": [5, 70, 140], "_return_pair": 5, "setter": 5, "split_id": [5, 9, 10, 11, 12, 70, 140], "dict": [5, 9, 10, 11, 21, 26, 35, 36, 37, 38, 39, 41, 42, 43, 45, 46, 51, 70, 71, 73, 77, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 107, 112, 113, 117, 119, 140], "item": [5, 14, 19, 20, 26, 27, 28, 32], "main": [5, 88, 89, 90], "tau_po": [5, 122], "tau_neg": [5, 122], "neg": [5, 27, 31, 67, 122], "separ": [5, 29, 32, 69, 107, 113, 122], "less": [5, 27, 29, 32], "min": [5, 12, 29, 74, 107], "n_exampl": [5, 122], "regular": [5, 115, 116], "instanc": [5, 32, 36, 37, 38, 39, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 60, 67, 83, 86, 90, 105, 106, 107, 108, 111, 119, 121, 140], "000": [5, 14, 16, 17, 18, 19, 22, 23, 31], "lower": [5, 9, 12, 29, 32, 36, 54, 107, 127], "250": [5, 20, 27, 69, 83, 86, 90], "relativepositioningsampl": 5, "60": [5, 10, 12, 16, 19, 27, 32], "n_examples_train": 5, "len": [5, 8, 9, 10, 11, 12, 14, 17, 20, 22, 29, 32, 72, 117], "n_examples_valid": 5, "n_examples_test": 5, "train_sampl": [5, 9, 10, 11], "get_metadata": [5, 9, 10, 11, 27, 28, 29, 31, 70, 121], "same_rec_neg": [5, 122], "valid_sampl": [5, 9, 10, 11], "presampl": [5, 122], "test_sampl": 5, "introduc": [5, 9, 10, 11, 14, 15, 24, 25, 27, 31], "four": [5, 9, 46, 69, 72], "embedd": 5, "dimension": [5, 67, 86, 119, 130], "last": [5, 22, 27, 31, 32, 51, 65, 72, 74, 78, 79, 80, 83, 86, 107, 110, 112, 113, 140], "embed": [5, 9, 10, 83, 86], "after": [5, 12, 16, 21, 26, 28, 29, 32, 69, 74, 84, 96, 97, 98, 124, 127, 140], "tempor": [5, 9, 10, 14, 26, 83, 84, 86, 87, 89, 96, 97, 98, 99, 100, 101, 103, 140], "wrap": [5, 26, 32, 70], "siames": 5, "contrastivenet": 5, "sleepstagerchambon2018": [5, 9, 26], "input_size_sampl": [5, 9, 10, 11], "emb_siz": 5, "emb": 5, "n_output": [5, 9, 10, 11, 26, 31, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 119], "n_conv_ch": [5, 98], "apply_batch_norm": [5, 97, 98], "linear": [5, 9, 10, 26, 30, 45, 62, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 103, 107], "top": [5, 9, 10, 11, 34], "x1": [5, 122], "x2": [5, 122], "z1": 5, "z2": 5, "flatten": [5, 9, 10, 11], "similar": [5, 27, 105], "account": [5, 70, 112], "smaller": [5, 27, 32, 80, 88, 89, 113], "checkpoint": [5, 32], "earlystop": [5, 29, 32], "epochscor": [5, 8, 9, 10, 11, 67, 119], "5e": 5, "128": [5, 10, 11, 67, 72, 88, 89, 98, 103, 119], "512": [5, 11], "enough": [5, 72], "num_work": [5, 14, 32, 130], "cp": 5, "dirnam": 5, "f_criterion": 5, "f_optim": 5, "f_histori": 5, "early_stop": 5, "patienc": 5, "train_acc": 5, "bcewithlogitsloss": [5, 67, 119], "adam": [5, 9, 10, 11, 14, 31], "max_epoch": [5, 29, 32, 67, 119], "iterator_train__sampl": [5, 9, 10, 11], "iterator_valid__sampl": [5, 9, 10, 11], "iterator_train__num_work": 5, "iterator_valid__num_work": 5, "load_param": 5, "lowest": 5, "pt": [5, 83], "delet": [5, 22, 70, 118], "file": [5, 6, 12, 13, 14, 16, 17, 18, 19, 23, 26, 33, 70, 74, 75, 81, 105, 123, 135, 140], "5234": 5, "7013": 5, "6680": 5, "6320": 5, "1660": 5, "5938": 5, "7149": 5, "4880": 5, "8358": 5, "8803": 5, "4922": 5, "0040": 5, "6440": 5, "6172": 5, "8777": 5, "7031": 5, "6120": 5, "5990": 5, "8684": 5, "5391": [5, 27, 28, 29, 30, 31], "6751": 5, "5920": 5, "6213": 5, "8710": 5, "6719": 5, "6227": 5, "6263": 5, "8768": 5, "6562": 5, "6309": 5, "6240": 5, "6117": 5, "8771": 5, "6641": 5, "6272": 5, "6480": 5, "5950": [5, 28, 29], "8705": 5, "6328": 5, "6238": 5, "5797": 5, "8819": 5, "6406": 5, "6177": 5, "6800": 5, "5746": 5, "9290": 5, "6250": 5, "6323": 5, "7040": 5, "5787": 5, "8672": 5, "6094": 5, "6281": 5, "6760": 5, "5772": 5, "8615": 5, "6422": 5, "6880": 5, "5790": 5, "8652": 5, "6840": 5, "5765": 5, "8659": 5, "6170": 5, "6920": 5, "5730": 5, "8657": 5, "7578": 5, "5608": 5, "6960": 5, "5676": 5, "8648": 5, "6875": 5, "5936": [5, 30], "7120": 5, "5612": 5, "8691": 5, "7734": 5, "5472": 5, "7080": 5, "5500": 5, "8600": 5, "19": [5, 9, 10, 11, 16, 27, 105, 111], "7656": 5, "5245": 5, "5400": [5, 30], "8745": 5, "5641": 5, "7160": 5, "5333": 5, "8807": 5, "21": [5, 9, 11, 16, 27, 31, 111], "7422": 5, "5307": 5, "7200": [5, 10], "5272": 5, "7109": 5, "5499": 5, "7360": 5, "5211": [5, 22], "8677": 5, "6259": 5, "7400": 5, "5164": 5, "8719": 5, "5712": 5, "5120": 5, "5030": 5, "7280": 5, "8638": 5, "balanc": [5, 9, 10, 11, 120, 140], "to_list": [5, 9, 10, 11], "ys1": 5, "ys2": 5, "y1": 5, "y2": 5, "zip": [5, 12, 16, 24], "l": [5, 9, 10, 11, 12, 17, 18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 83, 84, 95, 96, 103, 120, 134], "orang": [5, 12, 16], "lines1": 5, "labels1": 5, "get_legend_handles_label": 5, "lines2": 5, "labels2": 5, "displai": [5, 9, 10, 11, 27, 28, 29, 32, 72, 132], "confus": [5, 9, 10, 11, 134, 140], "matrix": [5, 9, 10, 11, 38, 39, 46, 56, 57, 63, 86, 134, 140], "report": [5, 9, 10, 11, 14, 29, 32, 75, 76, 83, 135], "confusion_matrix": [5, 9, 10, 11, 27, 28, 134], "classification_report": [5, 9, 10, 11], "switch": [5, 32, 140], "y_pred": [5, 9, 10, 11, 27, 28, 67, 103, 126], "y_true": [5, 9, 10, 11, 27, 28, 67], "90": [5, 16, 29, 32, 134], "88": [5, 16], "precis": [5, 9, 10, 11, 134], "recal": [5, 9, 10, 11], "f1": [5, 9, 10, 11, 83, 93, 127], "support": [5, 9, 10, 11, 18, 27, 32, 67, 107, 110, 111, 117, 119, 140], "74": [5, 16], "71": [5, 16], "121": [5, 12], "68": [5, 16, 27], "129": [5, 11], "macro": [5, 9, 10, 11], "avg": [5, 9, 10, 11], "logist": 5, "balanced_accuracy_scor": [5, 11], "linear_model": 5, "logisticregress": 5, "standardscal": 5, "make_pipelin": 5, "singl": [5, 9, 10, 27, 30, 40, 41, 42, 58, 59, 67, 85, 99, 111, 119, 130, 140], "no_grad": [5, 32], "feat": 5, "batch_x": [5, 22], "concaten": [5, 9, 10, 70, 83, 102, 107, 112, 113], "log_reg": 5, "penalti": 5, "l2": [5, 83], "class_weight": [5, 9, 10, 11], "solver": 5, "lbfg": 5, "multi_class": 5, "multinomi": 5, "clf_pipe": 5, "train_y_pr": 5, "valid_y_pr": 5, "test_y_pr": 5, "train_bal_acc": [5, 9, 10, 11], "valid_bal_acc": [5, 9, 10, 11], "test_bal_acc": 5, "bal": 5, "acc": [5, 29, 32], "4f": 5, "_logist": 5, "460": [5, 140], "convergencewarn": 5, "fail": [5, 12], "converg": [5, 29, 31], "statu": 5, "stop": [5, 32, 36, 54, 80, 107, 112, 113, 131, 140], "NO": 5, "reach": [5, 9, 10, 32], "max_it": 5, "scikit": [5, 24, 25, 33, 67, 70, 73, 91, 96, 109, 113, 116, 118, 119, 132, 134, 140], "document": [5, 10, 12, 34, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 105, 107, 108, 110, 111, 135, 139, 140], "altern": [5, 26, 32, 67, 119], "option": [5, 10, 18, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 67, 70, 73, 80, 83, 89, 90, 91, 107, 110, 113, 119, 130, 134, 139, 140], "n_iter_i": 5, "_check_optimize_result": 5, "8924": [5, 29], "5215": 5, "6011": 5, "107": [5, 26], "26": [5, 9, 10, 11, 16, 20, 27, 98], "70": [5, 16], "350": 5, "77": [5, 11, 13, 16], "79": [5, 16], "58": [5, 11, 16], "66": [5, 16], "142": [5, 140], "43": [5, 10, 11, 16, 27, 29], "109": 5, "81": [5, 16, 19, 27], "62": [5, 14, 16, 26, 27], "562": 5, "48": [5, 10, 11, 16, 18, 20, 23, 27, 69, 90], "61": [5, 9, 16, 26, 27], "105": [5, 33], "46": [5, 11, 16, 26], "170": [5, 140], "1088": [5, 101], "57": [5, 14, 16, 26], "much": [5, 27, 67, 110, 119], "chanc": [5, 9, 10], "level": [5, 9, 10, 22, 68, 105, 107, 108, 110, 111, 140], "problem": [5, 26, 41, 59, 135, 138], "quick": [5, 121], "2d": [5, 134], "space": [5, 16], "pca": 5, "decomposit": 5, "cm": [5, 69, 134], "n_compon": 5, "tsne": 5, "compon": [5, 9, 10, 11, 72, 88, 89], "fit_transform": 5, "get_cmap": 5, "viridi": 5, "enumer": [5, 12, 29, 32], "n1": [5, 9, 10, 11], "n2": [5, 9, 10, 11], "n3": [5, 9, 10, 11], "scatter": [5, 16, 31], "alpha": [5, 9, 10, 11, 12, 45, 83, 88, 89], "advanced_train": 5, "plot_relative_posit": [5, 6], "472": [5, 140], "matplotlibdeprecationwarn": 5, "minor": 5, "releas": [5, 88, 135, 139], "colormap": [5, 134], "obj": 5, "0x7f312debfd60": 5, "nonlinear": [5, 29, 67, 83, 94, 119], "project": [5, 12, 14, 19, 26, 75, 76, 111], "umap": 5, "might": [5, 14, 16, 26, 29, 30, 32, 113, 121], "insight": 5, "explor": [5, 29], "ag": [5, 12, 18, 22, 69, 72, 75, 76], "sex": 5, "specif": [5, 9, 10, 11, 16, 18, 30, 67, 81, 97, 105, 119, 121, 137], "subset": [5, 8, 20, 29, 31, 70, 107, 108, 140], "achiev": [5, 9, 10, 11], "reason": [5, 10, 29, 32, 67, 119, 127], "avenu": 5, "entir": [5, 14, 20, 29, 32, 140], "describ": [5, 11, 26, 27, 28, 29, 32, 72, 84, 85, 88, 89, 90, 91, 96, 97, 98, 99, 103], "discov": 5, "2020": [5, 36, 37, 38, 43, 51, 54, 55, 57, 60, 65, 88, 89, 97, 101, 122], "preprint": [5, 31, 36, 37, 38, 39, 41, 43, 51, 54, 55, 56, 57, 59, 60, 65, 92, 93, 100, 122], "2007": [5, 36, 43, 51, 54, 60, 65, 122], "16104": [5, 122], "kemp": [5, 9, 10, 11], "b": [5, 9, 10, 11, 16, 27, 39, 56, 86, 92, 93, 103], "zwinderman": [5, 9, 10, 11], "tuk": [5, 9, 10, 11], "kamphuisen": [5, 9, 10, 11], "obery": 5, "2000": [5, 9, 10, 11, 22, 30, 121], "neuron": [5, 9, 10, 11], "feedback": [5, 9, 10, 11, 69], "loop": [5, 9, 10, 11, 14, 67, 119], "slow": [5, 9, 10, 11, 16, 132, 140], "wave": [5, 9, 10, 11], "microcontinu": [5, 9, 10, 11], "ieee": [5, 9, 10, 11, 46, 47, 48, 49, 63, 83, 85, 86, 87, 88, 89, 98, 99], "transact": [5, 10, 83, 85, 86, 88, 89, 98, 99], "biomed": 5, "1185": [5, 9, 10, 11, 22], "1194": [5, 9, 10, 11], "goldberg": [5, 9, 10, 11], "amar": [5, 9, 10, 11], "glass": [5, 9, 10, 11], "hausdorff": [5, 9, 10, 11], "ivanov": [5, 9, 10, 11], "p": [5, 9, 10, 27, 28, 29, 30, 31, 36, 43, 51, 54, 60, 65, 92, 93, 98], "mark": [5, 9, 10, 11], "stanlei": [5, 9, 10, 11], "physiobank": [5, 9, 10, 11], "physiotoolkit": [5, 9, 10, 11], "research": [5, 9, 10, 11, 30, 34, 136], "resourc": [5, 7, 9, 10, 11, 13, 16, 24, 70, 75, 109, 112, 118, 140], "complex": [5, 9, 10, 11, 29, 32, 72, 97], "circul": [5, 9, 10, 11], "101": [5, 9, 10, 11, 12], "e215": [5, 9, 10, 11], "e220": [5, 9, 10, 11], "chambon": [5, 9, 10, 98], "galtier": [5, 9, 10, 98], "arnal": [5, 9, 10, 98], "wainrib": [5, 9, 10, 98], "2018": [5, 9, 10, 28, 29, 30, 39, 41, 43, 45, 56, 59, 60, 62, 93, 98, 100], "multivari": [5, 9, 10, 98], "multimod": [5, 9, 10, 98], "tran": [5, 9, 10], "system": [5, 9, 10, 46, 63, 85, 86, 88, 89, 98, 99, 138], "rehabilit": [5, 9, 10, 85, 86, 88, 89, 98, 99], "758": [5, 9, 10, 98], "769": [5, 9, 10, 98], "215": [5, 6], "165": 5, "49": [6, 11, 16], "481": 6, "execut": [6, 11, 12, 13, 14, 16, 17, 19, 23, 33, 72, 118], "auto_examples_advanced_train": 6, "02": [6, 10, 11, 13, 16, 23, 26, 27, 33], "164": [6, 140], "502": [6, 28, 33], "517": [6, 140], "analaysi": [7, 24], "sleep": [7, 13, 16, 24, 30, 41, 59, 70, 74, 85, 91, 97, 98, 99, 102, 103, 109, 113, 118, 120, 121, 123, 132, 134, 140], "cognit": [7, 24], "experi": [7, 14, 24, 29, 32, 68, 72], "stage": [7, 13, 24, 29, 30, 32, 70, 74, 85, 91, 97, 98, 99, 102, 103, 109, 113, 118, 120, 121, 123, 132, 134, 140], "chambon2018": [7, 13, 24, 70, 74, 91, 98, 102, 109, 113, 118, 121, 123, 132, 134], "eldele2021": [7, 13, 24, 70, 74, 91, 99, 102, 109, 113, 118, 121, 123, 132, 134], "big": [7, 13, 24, 70, 75, 109, 112, 118, 140], "tuh": [7, 13, 14, 15, 23, 24, 70, 76, 109, 112, 118, 140], "corpu": [7, 13, 14, 15, 23, 24, 70, 75, 76, 109, 112, 118, 140], "bcicomp": 8, "0x7f3130e1ceb0": 8, "decid": [8, 28, 37, 38, 39, 41, 50, 52, 53], "about": [8, 9, 10, 12, 26, 30, 71, 77, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 132, 135], "length": [8, 9, 11, 12, 14, 16, 26, 27, 30, 45, 62, 70, 80, 83, 84, 85, 86, 87, 88, 89, 91, 92, 93, 94, 96, 97, 98, 99, 100, 101, 107, 112, 113, 140], "preced": 8, "create_windows_from_target_channel": [8, 140], "cnosid": 8, "finer": [8, 140], "fexion": 8, "idx_train": 8, "idx_valid": 8, "n_out_chan": 8, "long": [8, 14, 29, 30, 72, 85], "respons": [8, 9, 10, 11, 28, 30], "manag": [8, 9, 10, 11, 28, 30, 31], "inherit": [8, 9, 10, 11, 26, 28, 30, 67, 119], "neuralnetregressor": 8, "logic": [8, 9, 10, 11, 28, 30, 32], "pearson": 8, "pearson_r_scor": 8, "net": [8, 26, 67, 99, 103, 119, 125, 126, 127], "mseloss": [8, 119], "valid_pearson_r": 8, "train_pearson_r": 8, "train_r2": 8, "valid_r2": 8, "5083": 8, "1251": [8, 22], "5570": 8, "7337": 8, "1507": 8, "6139": 8, "3240": 8, "7986": 8, "3712": 8, "3153": 8, "2582": 8, "1510": 8, "3971": 8, "1032": 8, "154": [8, 11, 13], "112": 8, "plot_bcic_iv_4_ecog_tri": [8, 13], "test": [9, 10, 11, 16, 21, 24, 25, 27, 28, 30, 33, 67, 70, 72, 73, 91, 96, 109, 113, 116, 118, 119, 132, 140], "adapt": [9, 11, 16, 87, 88, 89, 99, 100, 101], "distribut": [9, 10, 29, 45, 137], "individu": [9, 10, 11, 12, 26, 27, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 119, 140], "integr": [9, 10, 32], "omit": [9, 36], "downsampl": [9, 10, 110], "apply_on_arrai": [9, 10, 12, 109], "0x7f3130f17040": 9, "0x7f3130e808b0": 9, "take": [9, 10, 11, 16, 17, 29, 31, 53, 81, 83, 86, 90, 99], "everi": [9, 10, 11, 12, 14, 18, 22, 29, 32, 72, 83, 86, 90], "consecut": [9, 10, 11, 51, 65, 102, 113, 120, 123], "simplifi": [9, 10, 121, 140], "rather": [9, 10], "freez": [9, 10, 140], "sequencesampl": [9, 10, 11, 140], "n_window": [9, 10, 11, 22, 83, 120, 123], "n_windows_strid": [9, 10, 11, 123], "maxim": [9, 10, 30, 36], "overlap": [9, 10, 11, 78, 79, 80, 107, 112, 113], "372": 9, "383": 9, "implement": [9, 10, 14, 16, 26, 29, 45, 53, 62, 67, 83, 87, 88, 89, 90, 92, 93, 119, 129, 130, 136, 140], "get_center_label": [9, 10], "isinst": [9, 10], "ceil": [9, 10, 101], "astyp": [9, 10], "appear": [9, 10, 11, 69], "lot": [9, 10, 11, 67, 119], "night": [9, 10, 11], "spent": [9, 10, 11], "imbalanc": [9, 10, 11], "avoid": [9, 10, 11, 12, 14, 16, 22, 27, 29, 74, 140], "frequent": [9, 10, 11], "compute_class_weight": [9, 10, 11], "vector": [9, 10, 107, 110], "timedistribut": [9, 10, 140], "feat_extractor": [9, 10], "return_feat": [9, 10, 85, 97, 98, 99], "start_dim": [9, 10], "len_last_lay": [9, 10], "neuralnetclassifi": [9, 10, 11, 28, 30], "mass": 9, "ss3": 9, "speak": [9, 11, 14], "recommend": [9, 11, 16, 29, 30, 34, 86, 138, 139], "balanced_accuraci": [9, 10], "criterion__weight": [9, 10, 11], "tensor": [9, 10, 11, 22, 26, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 85, 86, 90, 95, 97, 98, 99, 100, 101, 102, 119, 124, 128, 129], "2136": 9, "5768": 9, "0888": 9, "6372": 9, "6288": 9, "2036": 9, "4788": 9, "6676": [9, 27], "5263": 9, "2324": 9, "4033": 9, "0966": 9, "2102": 9, "6337": 9, "4958": 9, "2888": 9, "3407": 9, "1149": 9, "2465": 9, "6790": 9, "4974": 9, "3993": 9, "2126": 9, "4517": 9, "4013": 9, "6235": 9, "5035": 9, "5294": 9, "0967": 9, "2768": 9, "4076": 9, "6179": 9, "4931": 9, "5755": 9, "9662": 9, "5927": 9, "5671": [9, 22], "3689": 9, "6251": 9, "8904": 9, "7076": 9, "5786": 9, "2952": 9, "5046": 9, "6877": 9, "8148": 9, "7154": 9, "5876": 9, "3450": 9, "4988": 9, "6860": 9, "7449": 9, "5196": 9, "5269": 9, "6322": 9, "5106": 9, "spatial_conv": 9, "kernel_s": [9, 10, 91, 100, 140], "feature_extractor": [9, 10], "ident": [9, 11, 32, 44, 67, 84, 119], "relu": [9, 10, 90], "maxpool2d": 9, "dilat": [9, 10, 11, 27, 91], "ceil_mod": [9, 10], "end_dim": [9, 10], "inplac": [9, 10, 16], "in_featur": [9, 10], "816": 9, "out_featur": [9, 10], "bia": [9, 10, 11], "sharex": [9, 10, 11], "plot_confusion_matrix": [9, 10, 11, 27, 28, 140], "confusion_mat": [9, 10, 11, 27, 28, 134], "class_nam": [9, 10, 11, 27, 28, 134], "wake": [9, 10, 11, 74], "rem": [9, 10, 11], "33": [9, 11, 16, 27, 33], "56": [9, 11, 13, 16, 27], "34": [9, 11, 16, 30], "42": [9, 11, 16, 27, 30], "194": 9, "03": [9, 10, 11, 16, 23, 27], "37": [9, 11, 16, 22, 26, 27], "hypnogram": [9, 10, 11], "overlaid": [9, 10, 11], "correctli": [9, 10, 11, 91, 139, 140], "identifi": [9, 10, 11, 80, 113], "amount": [9, 10, 11, 16, 110], "expert": [9, 10, 11], "annot": [9, 10, 11, 18, 19, 21, 27, 28, 29, 30, 32, 107], "text": [9, 10, 11, 29, 134], "150": [9, 10, 11, 72], "22222222222223": [9, 10, 11], "despit": [9, 10, 11], "held": [9, 10], "includ": [9, 11, 12, 14, 28, 29, 30, 32, 38, 57, 73, 105, 107, 108, 112, 113, 135, 136], "especi": [9, 30, 32], "ah": [9, 10, 11], "hac": [9, 10, 11], "jjl": [9, 10, 11], "obery\u00e9": [9, 10, 11], "bme": [9, 10, 11], "al": [9, 10, 11, 26, 72, 84, 85, 87, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 127], "lan": [9, 10, 11], "jm": [9, 10, 11], "pch": [9, 10, 11], "rg": [9, 10, 11], "mietu": [9, 10, 11], "je": [9, 10, 11], "moodi": [9, 10, 11], "gb": [9, 10, 11], "peng": [9, 10, 11, 43, 60], "he": [9, 10, 11], "622": [9, 13], "plot_sleep_staging_chambon2018": [9, 13], "attent": [10, 83, 86, 99], "divyesh": [10, 140], "narayanan": [10, 140], "400": [10, 11, 140], "speed": [10, 11, 16, 140], "0x7f311d82ad70": 10, "fpz": 10, "cz": [10, 12, 26, 111, 117], "give": [10, 12, 22, 26, 46, 63, 107, 135], "pz": [10, 12], "oz": 10, "130": [10, 19], "reject": [10, 19, 112, 113, 114], "flat": [10, 19, 37, 55, 112, 113, 114], "bad": [10, 14, 19, 107, 108, 111, 135], "slower": [10, 14, 19], "futur": [10, 19, 26, 30, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103], "0x7f311dd5d7b0": 10, "133": [10, 11], "sleepstagereldele2021": [10, 26, 140], "1471": 10, "1815": 10, "3459": 10, "1795": 10, "4748": 10, "2672": 10, "8805": 10, "1955": 10, "2186": 10, "1537": [10, 30], "9725": 10, "4550": 10, "4941": 10, "2256": 10, "2200": 10, "2159": 10, "9764": 10, "_mrcnn": 10, "gelu": 10, "approxim": [10, 47, 48, 49], "features1": 10, "conv1d": [10, 11, 103], "batchnorm1d": [10, 11], "ep": [10, 116], "05": [10, 11, 12, 16, 23, 101], "momentum": [10, 26, 84, 88, 89, 96], "affin": 10, "track_running_stat": 10, "maxpool1d": [10, 11], "features2": 10, "afr": [10, 99], "_sebasicblock": 10, "conv1": 10, "bn1": 10, "conv2": 10, "bn2": 10, "se": 10, "_selay": 10, "avg_pool": 10, "adaptiveavgpool1d": [10, 101], "output_s": [10, 91, 102], "fc": [10, 99], "sigmoid": [10, 67, 119], "_tce": 10, "modulelist": 10, "_encoderlay": 10, "self_attn": 10, "_multiheadedattent": 10, "conv": [10, 11, 103], "_causalconv1d": 10, "feed_forward": 10, "_positionwisefeedforward": 10, "w_1": 10, "120": [10, 72, 99], "w_2": 10, "sublayer_output": 10, "_sublayeroutput": 10, "norm": [10, 83], "layernorm": 10, "06": [10, 11, 13, 16, 27, 33], "elementwise_affin": 10, "n4": 10, "_classif": 10, "undefinedmetricwarn": 10, "ill": 10, "zero_divis": 10, "behavior": [10, 30, 32, 67, 119, 140], "_warn_prf": 10, "averag": [10, 12, 27, 29, 31, 32, 67, 83, 91, 111, 119, 124], "msg_start": 10, "faster": [10, 16, 27, 67, 110, 119], "89": [10, 16], "eldel": [10, 99], "et": [10, 26, 72, 84, 85, 87, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 127], "With": [10, 99], "vol": [10, 99], "29": [10, 11, 16, 27, 31, 99], "pp": [10, 36, 43, 46, 47, 48, 49, 51, 54, 60, 63, 65, 86, 99], "809": [10, 99], "818": [10, 99], "1109": [10, 83, 87, 88, 89, 99], "tnsre": [10, 88, 89, 99], "3076234": [10, 99], "868": [10, 13], "plot_sleep_staging_eldele2021": [10, 13], "look": [11, 12, 17, 22, 26, 29, 68, 121], "simpler": 11, "current": [11, 67, 111, 119, 135], "seq2seq": 11, "written": [11, 118, 137], "veri": [11, 29, 32, 70, 113], "short": [11, 12, 29, 32, 69, 85], "too": 11, "small": [11, 12, 27, 29, 135], "theo": [11, 140], "gnassoun": [11, 140], "omar": [11, 140], "emir": 11, "zero": [11, 16, 51, 65, 107, 110, 113, 116], "median": 11, "unit": [11, 26, 107, 139], "interquartil": 11, "upsampl": [11, 103, 110], "light": [11, 134], "No": [11, 19, 26, 29, 32, 69], "robust_scal": 11, "0x7f3130017cd0": 11, "shorter": [11, 140], "fulli": [11, 29, 30, 83, 86, 88, 89, 90], "usleep": [11, 26, 140], "in_chan": [11, 26, 31, 84, 92, 93, 94, 95, 96, 101, 103, 104], "with_skip_connect": [11, 103], "balanced_accuracy_multi": 11, "deactiv": 11, "set_param": [11, 67, 119], "callbacks__valid_acc": 11, "306": 11, "even": [11, 26, 29, 32, 67, 68, 103, 119], "odd": [11, 90, 103], "trigger": 11, "intern": [11, 14, 16, 20, 21, 43, 45, 46, 47, 48, 49, 60, 62, 63, 109], "aten": 11, "src": 11, "nativ": 11, "cpp": 11, "1008": [11, 29], "2040": 11, "6129": 11, "1707": 11, "5807": 11, "1839": 11, "2224": 11, "5430": 11, "1594": 11, "5866": 11, "7164": 11, "3464": 11, "4928": 11, "1853": 11, "6026": 11, "7267": 11, "3000": [11, 22, 26, 31], "encod": [11, 99, 103], "_encoderblock": 11, "1500": [11, 101, 121], "block_prepool": 11, "102": 11, "maxpool": [11, 103], "750": 11, "405": 11, "375": 11, "726": 11, "188": 11, "constantpad1d": 11, "377": 11, "94": [11, 16, 29], "160": [11, 72], "004": 11, "960": 11, "565": 11, "876": 11, "108": 11, "536": 11, "152": [11, 140], "115": 11, "368": 11, "214": 11, "228": 11, "338": 11, "bottom": 11, "302": 11, "452": 11, "698": 11, "elu": [11, 83, 84, 88, 89, 94], "604": 11, "_decoderblock": 11, "block_preskip": 11, "898": 11, "block_postskip": 11, "428": [11, 140], "641": 11, "786": 11, "65": [11, 16], "304": [11, 140], "323": 11, "912": 11, "156": 11, "216": 11, "163": 11, "620": 11, "863": 11, "83": [11, 16, 22], "237": 11, "635": 11, "110": 11, "515": [11, 140], "520": [11, 140], "39": [11, 16, 22, 27], "324": 11, "060": 11, "660": 11, "44": [11, 16, 26, 27, 32, 33, 72], "376": 11, "645": 11, "195": 11, "363": 11, "727": 11, "225": 11, "161": [11, 140], "126": 11, "51": [11, 16], "522": 11, "tanh": 11, "avgpool1d": 11, "482": 11, "011": 11, "91": [11, 16], "93": [11, 16, 27, 43, 60], "52": [11, 16, 26], "197": [11, 140], "84": [11, 16], "399": 11, "perslev": [11, 103, 120], "darkner": [11, 103, 120], "kempfner": [11, 103, 120], "nikol": [11, 103, 120], "jennum": [11, 103, 120], "pj": [11, 103, 120], "igel": [11, 103, 120], "resili": [11, 103, 120], "npj": [11, 103, 120], "digit": [11, 22, 103, 120], "med": [11, 103, 120], "72": [11, 16, 30, 103, 120], "166": [11, 13, 140], "plot_sleep_staging_usleep": [11, 13], "showcas": [12, 29, 32], "templ": [12, 75, 76, 140], "univers": [12, 72, 75, 76, 140], "hospit": [12, 75, 76, 140], "www": [12, 14, 34, 68, 75, 76], "isip": [12, 14, 75, 76], "piconepress": [12, 14, 75, 76], "tuh_eeg": [12, 14, 22, 75, 76], "shtml": [12, 75, 76], "c_tueg": [12, 75], "luka": [12, 17, 18, 19, 20, 21, 22, 31, 34, 140], "gemein": [12, 17, 18, 19, 20, 21, 22, 31, 140], "tempfil": [12, 16, 18], "error": [12, 22, 27, 30, 31, 80, 106, 112, 113, 114, 119, 135, 140], "messag": [12, 14, 22, 135], "creation": [12, 22], "mock": [12, 22], "want": [12, 14, 18, 21, 22, 24, 28, 29, 30, 32, 67, 119, 136, 139], "disconsid": 12, "section": [12, 22, 72, 138], "_tuhmock": [12, 22], "noqa": [12, 22], "f811": [12, 22], "firstli": [12, 21], "complet": [12, 14, 16, 27, 67, 119], "read": [12, 14, 16, 17, 18, 19, 75, 76, 81, 113], "tuh_path": [12, 14, 22], "pars": 12, "path": [12, 14, 16, 17, 18, 19, 22, 32, 68, 70, 75, 76, 81, 82], "patient": [12, 68], "id": [12, 18, 20, 29, 70, 75, 76, 81, 112, 113, 140], "sort": [12, 27, 28, 140], "chronolog": [12, 75, 76], "year": [12, 34], "month": [12, 34], "dai": [12, 69], "segment": [12, 16, 29, 32, 86, 107], "regard": 12, "gender": [12, 18, 22, 75, 76], "insert": [12, 22, 91], "job": [12, 67, 75, 81, 107, 110, 112, 113, 118, 119], "load": [12, 16, 17, 19, 22, 23, 68, 70, 73, 74, 76, 81, 84, 96, 109, 112, 113, 118, 140], "target_nam": [12, 14, 18, 22, 31, 70, 71, 75, 76, 81, 140], "add_physician_report": [12, 22, 75, 76], "__name__": 12, "statist": 12, "plt_histogram": 12, "df_of_ages_gend": 12, "ylim": 12, "show_titl": 12, "dafaram": 12, "male_df": 12, "female_df": 12, "figur": [12, 27, 28, 29, 69, 83, 134], "suptitl": 12, "95": [12, 16, 67, 119], "male": 12, "hist": 12, "bin": 12, "green": 12, "orient": 12, "horizont": 12, "axhlin": 12, "1f": [12, 32], "std": [12, 29, 43, 60, 72], "barh": [12, 29], "height": [12, 29], "width": [12, 30, 101, 107], "xlim": 12, "upper": [12, 16, 107], "left": [12, 27, 28, 29, 39, 67, 69, 72, 119], "ytick": 12, "gca": 12, "invert_xaxi": 12, "femal": [12, 72], "122": 12, "subplots_adjust": 12, "wspace": 12, "hspace": 12, "count": [12, 67, 119], "labelpad": 12, "durat": [12, 29, 30, 31, 105, 107, 113], "least": [12, 107, 121, 122, 131], "five": [12, 68], "select_by_dur": 12, "inf": 12, "determin": [12, 30, 67, 89, 119], "d_i": 12, "ones": [12, 26, 120, 140], "split": [12, 15, 20, 23, 24, 26, 31, 67, 70, 73, 84, 96, 113, 119, 140], "discard": [12, 74], "incomplet": 12, "configur": [12, 16, 27, 29, 32], "subdivis": 12, "le": 12, "repres": [12, 21, 47, 48, 49, 86], "re": [12, 21, 67, 111, 119, 135], "referenc": [12, 111], "short_ch_nam": 12, "a1": 12, "a2": 12, "fp1": 12, "fp2": 12, "f3": 12, "f4": 12, "c3": [12, 26], "c4": [12, 26], "p3": 12, "p4": 12, "o1": [12, 117], "o2": 12, "f7": 12, "f8": 12, "t3": 12, "t4": 12, "t5": 12, "t6": 12, "fz": 12, "subdivid": 12, "refer": [12, 34, 36, 37, 38, 39, 41, 43, 45, 46, 47, 48, 49, 51, 54, 55, 56, 57, 59, 60, 62, 63, 65, 68, 69, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 111, 117, 120, 122, 129, 134], "ar_ch_nam": 12, "ref": 12, "le_ch_nam": 12, "ar_ch_map": 12, "ch_name": [12, 14, 17, 26, 78, 106, 117], "le_ch_map": 12, "ch_map": 12, "select_by_channel": 12, "endswith": 12, "seta": 12, "kei": [12, 21, 26, 27, 28, 70, 71, 77, 112, 113], "recod": 12, "setb": 12, "issubset": 12, "region": [12, 107], "micro": 12, "volt": 12, "clip": 12, "outlier": 12, "800": [12, 18], "common": [12, 14, 111, 138, 140], "custom_rename_channel": 12, "unexpect": [12, 135], "rename_channel": 12, "custom_crop": 12, "include_tmax": [12, 105], "bigger": 12, "set_eeg_refer": [12, 111], "ref_channel": [12, 111], "ch_type": [12, 26, 111], "pick_channel": [12, 106, 109], "a_min": 12, "a_max": 12, "parallel": [12, 14, 15, 23, 24, 70, 74, 75, 81, 88, 89, 90, 107, 109, 110, 112, 113, 118, 140], "addition": [12, 18, 26, 34, 67, 119, 130], "serial": [12, 15, 18, 23, 24, 70, 74, 109, 112, 118, 140], "lazi": [12, 15, 16, 23, 24, 76, 84, 96, 112, 140], "capabl": [12, 16, 29, 32, 67, 119], "automat": [12, 14, 26, 68, 85, 101, 111, 140], "reload": [12, 16, 118], "machin": [12, 14, 16, 29, 32, 34, 36, 39, 43, 51, 54, 56, 60, 65, 67, 119], "build": [12, 27, 32, 137, 139], "core": [12, 16, 32], "out_path": 12, "mkdtemp": [12, 18], "directori": [12, 16, 18, 27, 68, 70, 75, 76, 81, 118, 139], "tuh_preproc": 12, "concat_d": [12, 16, 18, 112, 113, 114, 118], "save_dir": [12, 16, 118], "readi": [12, 16, 17, 18, 19, 31], "model": [12, 14, 21, 33, 34, 43, 60, 67, 70, 71, 73, 109, 112, 113, 116, 118, 119, 124, 125, 126, 127, 128, 129, 130, 132, 133, 136, 140], "train": [12, 14, 20, 21, 33, 67, 70, 72, 73, 77, 91, 96, 109, 113, 116, 118, 119, 132, 140], "disk": [12, 14, 16, 75, 76, 113], "tuh_window": [12, 22], "988": [12, 13], "plot_tuh_eeg_corpu": [12, 13], "799": 13, "auto_examples_applied_exampl": 13, "111": 13, "sake": 14, "etc": [14, 28, 30, 109], "preprocess": [14, 15, 18, 19, 20, 21, 22, 23, 24, 26, 31, 70, 74, 136, 140], "continu": [14, 16, 20, 71, 72, 78, 79, 80, 112, 113, 138, 140], "fast": [14, 16, 32, 132], "expens": [14, 67, 119], "ultim": 14, "becom": [14, 16, 29], "imposs": 14, "tb": 14, "potenti": [14, 16, 32, 138], "issu": [14, 16, 135, 140], "overhead": [14, 113], "accommod": 14, "window": [14, 16, 18, 19, 21, 26, 67, 70, 77, 78, 79, 80, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 107, 110, 112, 113, 119, 120, 121, 122, 123, 130, 131, 140], "overal": 14, "though": [14, 16, 29, 32], "impact": [14, 27, 30], "dispatch": 14, "enabl": [14, 16, 27, 32, 67, 69, 101, 119, 140], "fif": [14, 16, 18, 70, 81, 140], "edf": [14, 16, 17, 19, 22], "itertool": [14, 16], "product": [14, 16], "seaborn": [14, 29, 30], "sn": [14, 29, 30], "tuhabnorm": [14, 18, 140], "deep4net": [14, 26, 31, 140], "affect": [14, 27, 127], "algorithm": [14, 26, 28, 29, 30, 32], "set_num_thread": 14, "thread": 14, "autom": [14, 29], "abnorm": [14, 76], "slide": [14, 31, 83, 112], "bundl": 14, "prepar": [14, 16, 20, 32], "load_example_data": 14, "window_len_": 14, "n_record": [14, 121], "creat": [14, 16, 17, 18, 19, 20, 21, 31, 67, 70, 77, 78, 79, 80, 111, 112, 113, 119, 130, 140], "bool": [14, 26, 41, 45, 46, 47, 48, 49, 59, 63, 67, 68, 70, 71, 74, 75, 76, 77, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 108, 109, 110, 111, 112, 113, 117, 118, 119, 122, 123, 127, 130, 132, 134], "windows_d": [14, 16], "assum": [14, 26, 67, 105, 119, 124, 128, 140], "patholog": [14, 18, 76], "window_len_sampl": 14, "xxx": [14, 94], "itself": [14, 29, 30, 135], "drop_bad": [14, 80, 113], "create_example_model": 14, "kind": [14, 26], "str": [14, 22, 26, 27, 28, 29, 35, 67, 68, 70, 71, 73, 75, 76, 77, 80, 81, 84, 86, 91, 96, 105, 106, 107, 108, 109, 110, 111, 112, 113, 118, 119, 127, 134], "n_filters_tim": [14, 26, 31, 84, 86, 96], "filter_time_length": [14, 26, 84, 86, 96], "n_filters_spat": [14, 26, 31, 84, 96], "pool_time_length": [14, 26, 84, 86, 96], "pool_time_strid": [14, 26, 84, 86, 96], "split_first_lay": [14, 26, 84, 94, 96], "batch_norm": [14, 26, 84, 96], "batch_norm_alpha": [14, 26, 84, 88, 89, 94, 96], "drop_prob": [14, 26, 30, 84, 86, 87, 88, 89, 92, 93, 96, 100, 101], "elif": [14, 31], "n_filters_2": [14, 31, 84], "filter_length_2": [14, 84], "n_filters_3": [14, 31, 84], "filter_length_3": [14, 84], "n_filters_4": [14, 31, 84], "filter_length_4": [14, 84], "first_pool_mod": [14, 84], "max": [14, 16, 26, 29, 84, 92, 96, 98, 101, 103, 107, 116], "later_pool_mod": [14, 84], "double_time_conv": 14, "stride_before_pool": [14, 31, 84], "valueerror": [14, 26, 31, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103], "run_train": 14, "serv": [14, 69, 71, 77], "loss_val": 14, "zero_grad": [14, 32], "256": [14, 26, 140], "minibatch": 14, "pin_memori": 14, "pin": 14, "n_repetit": 14, "repeat": [14, 135], "get": [14, 16, 17, 22, 27, 28, 29, 32, 67, 119], "folder": [14, 32, 68], "storag": 14, "tuh_eeg_abnorm": 14, "v2": 14, "cycl": 14, "combin": [14, 16, 70], "all_result": 14, "win_len_": 14, "model_kind": 14, "repetit": [14, 16, 72], "nrepetit": 14, "n": [14, 16, 22, 26, 27, 28, 29, 30, 32, 36, 37, 38, 43, 45, 51, 54, 55, 57, 60, 62, 65, 83, 92, 93, 98, 129], "data_loading_start": 14, "data_loading_end": 14, "training_setup_start": 14, "worker_init_fn": 14, "training_setup_end": 14, "model_training_start": 14, "trained_model": 14, "model_training_end": 14, "del": 14, "data_prepar": 14, "training_setup": 14, "model_train": 14, "csv": 14, "results_df": 14, "fname": 14, "lazy_vs_eager_loading_result": 14, "to_csv": 14, "summar": 14, "catplot": 14, "row": [14, 22, 39, 70, 91, 134], "hue": 14, "col": 14, "strip": 14, "hardwar": [14, 16], "pretti": [14, 135], "worker": [14, 32, 130, 140], "speedup": 14, "benchmark_lazy_eager_load": [14, 23], "basic": [15, 27, 29, 32, 33, 53, 70, 73, 90, 91, 96, 109, 113, 116, 118, 132, 134, 140], "eager": [15, 23, 24, 76, 84, 96, 112], "discret": [15, 23, 24, 70, 75, 112, 140], "simplest": 16, "scenario": [16, 113], "act": [16, 111], "stai": [16, 27, 69], "aris": 16, "bottleneck": [16, 32, 88, 89, 101], "consider": 16, "solut": [16, 111], "clear": 16, "downsid": 16, "write": [16, 18], "cours": [16, 68], "whenev": 16, "up": [16, 17, 69, 103, 110, 140], "significantli": 16, "joblib": [16, 118], "made": [16, 27, 90, 140], "remain": [16, 29, 32], "tradeoff": 16, "memory_profil": 16, "memory_usag": 16, "goe": 16, "prepare_data": 16, "n_rec": 16, "tmp_dir": 16, "temporarydirectori": 16, "overwrit": [16, 18, 67, 70, 71, 75, 76, 77, 82, 118, 119], "measur": 16, "peak": [16, 112, 113], "character": 16, "n_repet": 16, "all_n_rec": 16, "all_n_job": 16, "mem": 16, "proc": 16, "time_taken": 16, "max_mem": 16, "1m": [16, 27], "115k": 16, "11mb": 16, "229k": 16, "10mb": 16, "344k": 16, "459k": 16, "573k": 16, "09mb": 16, "688k": 16, "803k": 16, "918k": 16, "03m": 16, "15m": 16, "26m": 16, "38m": 16, "49m": [16, 27], "61m": 16, "12mb": 16, "72m": 16, "84m": 16, "08mb": 16, "95m": 16, "06m": 16, "18m": 16, "29m": 16, "41m": [16, 27], "54m": 16, "14mb": 16, "65m": 16, "13mb": 16, "79m": 16, "90m": 16, "01m": 16, "13m": 16, "24m": 16, "36m": 16, "47m": 16, "59m": 16, "70m": 16, "82m": 16, "93m": 16, "07mb": 16, "05m": 16, "06mb": 16, "16m": [16, 27], "28m": [16, 27], "05mb": 16, "39m": 16, "51m": 16, "62m": [16, 27], "73m": 16, "04mb": 16, "85m": 16, "96m": [16, 27], "08m": 16, "19m": 16, "31m": 16, "42m": 16, "67m": 16, "80m": 16, "91m": 16, "14m": 16, "37m": 16, "50m": 16, "07": [16, 27, 29, 33], "77m": 16, "88m": 16, "00m": 16, "11m": [16, 27], "22m": 16, "34m": 16, "15mb": 16, "81m": 16, "08": 16, "04m": 16, "27m": 16, "40m": 16, "52m": 16, "63m": 16, "76m": 16, "09": [16, 27], "99m": 16, "2m": 16, "4m": [16, 27], "5m": [16, 27], "6m": [16, 27], "7m": [16, 27], "8m": [16, 27], "9m": [16, 27], "3m": [16, 27], "0m": [16, 27], "16mb": 16, "17mb": 16, "20mb": 16, "21mb": 16, "19mb": 16, "18mb": 16, "53": [16, 22], "54": [16, 27], "59": [16, 29], "63": 16, "67": [16, 27, 32, 103], "73": [16, 27], "76": 16, "03mb": 16, "82": [16, 43, 60], "85": [16, 27, 28], "92": 16, "96": 16, "97": 16, "98": 16, "99": [16, 27], "276gb": 16, "90k": 16, "4mb": [16, 27], "mne_data": [16, 17, 19, 27, 68], "sc4001e0": 16, "psg": 16, "detect": [16, 17, 19, 30, 72], "sc4011e0": 16, "2507000": 16, "25070": 16, "sec": [16, 17, 18, 19, 31], "contigu": [16, 51, 65], "fir": [16, 107], "phase": [16, 41, 59, 107], "causal": [16, 107], "firwin": [16, 107], "ham": [16, 107], "0194": 16, "passband": 16, "rippl": 16, "stopband": 16, "attenu": [16, 107], "edg": [16, 107], "transit": [16, 36, 54, 107], "bandwidth": [16, 36, 54], "450": 16, "tmp": [16, 18], "tmprqo1r57a": 16, "3260000": 16, "32600": 16, "708": [16, 18], "subdirectori": [16, 18, 70, 118], "open": [16, 18, 135, 136, 138], "isotrak": 16, "2884000": 16, "5391000": 16, "28840": 16, "53910": 16, "1975000": 16, "5235000": 16, "19750": 16, "52350": 16, "700": [16, 18], "match": [16, 18, 19, 26, 30, 70, 83], "exist": [16, 18, 22, 29, 31, 68, 70, 71, 77, 111, 118], "encount": [16, 18, 135], "mix": [16, 18, 45, 62, 129], "i_d": [16, 18], "tmp8bd4vm1l": 16, "tmpmhmgkrsv": 16, "tmp5_t3lhz9": 16, "sub_df": 16, "groupbi": 16, "mib": 16, "without": [16, 26, 27, 29, 30, 32, 67, 119, 129, 140], "circl": 16, "advantag": [16, 29, 88, 89], "togeth": [16, 27, 140], "521": [16, 23], "plot_benchmark_preprocess": [16, 23], "create_from_x_i": 17, "fetch": [17, 19, 20, 21, 69, 72, 73], "imagin": [17, 19], "hand": [17, 19, 24, 28, 30, 69, 72], "feet": [17, 18, 19, 21, 27, 28, 29, 30, 32, 69, 72], "event_cod": [17, 19], "yet": [17, 19, 91, 139], "physionet_path": [17, 19], "eegbci": [17, 19], "load_data": [17, 19], "update_path": [17, 19], "io": [17, 19, 27, 71, 105, 107, 117], "read_raw_edf": [17, 19], "stim_channel": [17, 19], "eegmmidb": [17, 19], "s022": [17, 19], "s022r05": [17, 19], "19999": [17, 19], "124": [17, 19, 27], "994": [17, 19], "s022r06": [17, 19], "s022r09": [17, 19], "s022r10": [17, 19], "s022r13": [17, 19], "s022r14": [17, 19], "ani": [17, 18, 26, 27, 29, 32, 67, 99, 107, 111, 119, 139], "get_data": 17, "500": [17, 19, 28, 121, 140], "rawarrai": [17, 19, 31, 80], "float64": [17, 19, 31], "20000": 17, "manipul": 17, "x_i": 17, "y_i": 17, "window_ind": 17, "start_ind": 17, "stop_ind": 17, "209": [17, 23], "plot_custom_dataset_exampl": [17, 23], "load_concat_dataset": [18, 140], "skip": [18, 22, 29, 32, 90, 103], "fn": [18, 109], "event": [18, 19, 20, 26, 29, 30, 74, 80, 112, 113], "0x7f313110b610": 18, "concat": [18, 70, 83, 112, 113, 118], "json": [18, 70, 81, 140], "hold": [18, 70, 71, 77, 112, 113], "due": [18, 32, 140], "tmpdir": 18, "temporari": [18, 140], "tmpvkqehedo": 18, "complianc": 18, "upon": [18, 26], "dataset_load": 18, "ids_to_load": [18, 81], "3868": 18, "386": 18, "left_hand": [18, 21, 27, 28, 29, 30, 32], "right_hand": [18, 21, 27, 28, 29, 30, 32], "tongu": [18, 21, 27, 28, 29, 30, 32, 69], "again": [18, 22, 29], "epo": [18, 70, 81], "windows_dataset_load": 18, "025": [18, 23], "plot_load_save_dataset": [18, 23], "create_from_mne_raw": 19, "create_from_mne_epoch": 19, "t0": 19, "t1": 19, "t2": 19, "point": [19, 20, 26, 69, 111, 115, 116], "beforehand": 19, "list_of_epoch": [19, 79], "baselin": [19, 26], "Not": [19, 26], "metadata": [19, 26, 70, 77, 112, 119, 120, 121, 122, 123], "correct": [19, 26, 32, 67, 87, 88, 89, 90, 92, 93, 119, 140], "ad": [19, 27, 70, 75, 76, 101, 103, 111, 140], "455": [19, 23], "plot_mne_dataset_exampl": [19, 23], "daniel": [20, 34, 140], "wilson": [20, 140], "dan": [20, 140], "wil": 20, "break": [20, 69], "place": [20, 31, 91, 105, 117], "legaci": 20, "inst": [20, 106, 107, 108, 111], "criteria": [20, 67, 119], "subset_nam": 20, "232164": 20, "790": [20, 23], "plot_moabb_dataset_exampl": [20, 23], "aim": [21, 22], "dictionari": [21, 26, 67, 70, 73, 107, 119], "string": [21, 22, 26, 34, 39, 47, 48, 49, 67, 70, 107, 108, 109, 118, 119, 127], "entri": [21, 106], "0x7f312dda4e20": 21, "0x7f312dda6fb0": 21, "0x7f312dda68f0": 21, "0x7f312dda6b60": 21, "0x7f312ddb0e50": 21, "0x7f312ddb0dc0": 21, "integ": [21, 22, 27, 28, 39, 51, 56, 65, 70, 107, 108], "0x7f3130eed3c0": 21, "0x7f3130eee6b0": 21, "0x7f3130eed4e0": 21, "0x7f312ddb22f0": 21, "0x7f312ddb0a90": 21, "0x7f312ddb3340": 21, "similarli": [21, 32], "0x7f312ddb19c0": 21, "0x7f312ddb1090": 21, "0x7f312ddb1e40": 21, "0x7f312ddb3a00": 21, "0x7f312ddb0af0": 21, "0x7f312ddb2680": 21, "0x7f3130eef9d0": 21, "817": [21, 23], "plot_split_dataset": [21, 23], "welcom": 22, "ll": 22, "guid": [22, 29, 138], "log": [22, 26, 27, 32, 67, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 105, 107, 108, 110, 111, 112, 113, 119, 140], "excess": 22, "v1": [22, 32], "02_tcp_le": 22, "00000058": 22, "s001": 22, "01_tcp_ar": 22, "099": 22, "00009932": 22, "s004": 22, "03_tcp_ar_a": 22, "123": 22, "00012331": 22, "s0": 22, "00000000": 22, "149": 22, "00014928": 22, "ndarrai": [22, 46, 63, 67, 110, 115, 116, 119, 123, 130, 131], "92922518": 22, "22477157": 22, "12493701": 22, "28417889": 22, "13578887": 22, "56835277": 22, "25153176": 22, "7638324": 22, "14345092": 22, "30167542": 22, "68056549": 22, "70380673": 22, "70052629": 22, "21543634": 22, "96330007": 22, "02736802": 22, "65902848": 22, "15756383": 22, "38658058": 22, "04194231": 22, "15447331": 22, "set_descript": [22, 32, 70, 71, 77], "ind": 22, "16017832": 22, "11754766": 22, "6515615": 22, "50407195": 22, "7429778": 22, "9292252": 22, "86039335": 22, "5169721": 22, "0308012": 22, "1209397": 22, "5210943": 22, "2247716": 22, "373041": 22, "14827406": 22, "25829056": 22, "1486133": 22, "15352039": 22, "30362263": 22, "939559": 22, "5686462": 22, "5503989": 22, "3299779": 22, "3865806": 22, "7443461": 22, "1792846": 22, "25878426": 22, "5670986": 22, "2997373": 22, "0537782": 22, "4429058": 22, "05458383": 22, "000525": 22, "66521484": 22, "15447332": 22, "dtype": [22, 30, 140], "float32": 22, "2600": 22, "3600": [22, 74], "dl": 22, "batch_i": 22, "batch_ind": 22, "simpli": [22, 26], "8024": 22, "4564": 22, "4433": 22, "7404": 22, "2522": 22, "0508": 22, "4418": 22, "5201": 22, "2037": 22, "0273": 22, "0506": 22, "1677": 22, "1145": 22, "7075": 22, "1768": 22, "0260": 22, "7216": 22, "2742": 22, "3986": 22, "3912": 22, "8000": 22, "0593": 22, "8097": 22, "1729": 22, "6267": 22, "8419": 22, "3996": 22, "6685": 22, "9266": 22, "1319": 22, "1409": 22, "6246": 22, "6229": 22, "5953": 22, "3169": 22, "4604": 22, "2885": 22, "0168": 22, "6279": 22, "6533": 22, "7673": 22, "6671": 22, "0448": 22, "1422": 22, "5395": 22, "4664": 22, "1882": 22, "2031": 22, "6282": 22, "4535": 22, "8585": 22, "2657": 22, "9942": 22, "3878": 22, "1360": 22, "9132": 22, "9481": 22, "5033": 22, "3406": 22, "6089": 22, "9883": 22, "2919": 22, "3796": 22, "8036": 22, "7666": 22, "8174": 22, "3829": 22, "1508": 22, "8516": 22, "0426": 22, "1322": 22, "4122": 22, "2526": 22, "9711": 22, "6890": 22, "4660": 22, "5510": 22, "3613": 22, "0280": 22, "1350": 22, "2249": 22, "9406": 22, "7754": 22, "7664": 22, "1807": 22, "8206": 22, "1281": 22, "1607": 22, "9353": 22, "0165": 22, "6509": 22, "7276": 22, "2137": 22, "5619": 22, "0408": 22, "9825": 22, "3648": 22, "6978": 22, "8943": 22, "2374": 22, "4398": 22, "8218": 22, "5172": 22, "2975": [22, 28], "0311": 22, "1602": 22, "1175": 22, "6516": 22, "5041": 22, "7430": 22, "9292": 22, "8604": 22, "5170": 22, "0308": 22, "1209": 22, "2248": 22, "3730": 22, "1483": 22, "2583": 22, "1486": 22, "1535": 22, "1249": 22, "3036": 22, "9396": 22, "5686": 22, "5504": 22, "3300": 22, "3866": 22, "7443": 22, "1793": [22, 30], "2588": 22, "2997": 22, "0419": 22, "0538": 22, "4429": 22, "0546": 22, "6652": 22, "1545": 22, "176": [22, 23], "plot_tuh_discrete_multitarget": [22, 23], "993": 23, "auto_examples_datasets_io": 23, "239": 23, "fundament": [24, 25], "tune": [24, 25, 32, 33, 70, 73, 86, 91, 96, 109, 113, 116, 118, 132, 140], "fake": [24, 25, 26, 33, 70, 71, 84, 91, 96, 104, 112, 124, 132, 140], "auto_examples_python": 24, "auto_examples_jupyt": 24, "develop": [26, 29, 32, 135, 139], "particular": 26, "pierr": [26, 140], "guetschel": [26, 140], "suppos": 26, "stumbl": 26, "schirrmeist": [26, 27, 28, 29, 30, 31, 34, 72, 84, 95, 96, 134, 140], "2017": [26, 27, 28, 29, 30, 31, 34, 46, 47, 48, 49, 63, 72, 84, 85, 95, 96, 134], "articl": [26, 34], "mention": [26, 29], "novel": [26, 88, 89], "shallowconvnet": [26, 31], "fortun": 26, "publish": 26, "what": [26, 29, 67, 83, 112, 113, 119], "exact": 26, "visit": [26, 29], "api": [26, 139], "models_dict": [26, 67, 119, 140], "atcnet": [26, 140], "deepsleepnet": [26, 140], "eegconform": [26, 140], "eegitnet": [26, 140], "eegincept": [26, 89, 140], "eeginceptionerp": [26, 88, 140], "eeginceptionmi": [26, 140], "eegnetv1": 26, "eegnetv4": 26, "eegresnet": [26, 140], "hybridnet": 26, "sleepstagerblanco2020": [26, 140], "tcn": [26, 83, 140], "tidnet": [26, 140], "investig": 26, "docstr": [26, 140], "__doc__": 26, "schirrmeister2017": [26, 72, 84, 95, 96], "conv_nonlin": [26, 96], "pool_mod": [26, 92, 93, 96], "pool_nonlin": [26, 96], "normalis": [26, 84, 96], "chs_info": [26, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 119], "fill": [26, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103], "ch": [26, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103], "detail": [26, 29, 32, 45, 62, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 107, 108, 110, 111, 117, 118, 132, 139], "input_window_second": [26, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 103, 119], "alia": [26, 83, 84, 85, 86, 87, 88, 89, 90, 92, 93, 94, 96, 97, 98, 99, 100, 101, 103], "softmax": [26, 27, 31, 67, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 119], "doc": [26, 83, 84, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 100, 101, 103, 132, 139, 140], "infer": [26, 29, 30, 67, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 113, 119, 127], "attempt": [26, 83, 84, 85, 91, 94, 95, 96, 97, 98, 99, 100, 103, 111], "springenberg": [26, 27, 28, 29, 30, 31, 34, 84, 95, 96, 134], "fieder": [26, 27, 28, 29, 30, 31, 34, 84, 95, 96, 134], "glasstett": [26, 27, 28, 29, 30, 31, 34, 84, 95, 96, 134], "eggensperg": [26, 27, 28, 29, 30, 31, 34, 84, 95, 96, 134], "tangermann": [26, 27, 28, 29, 30, 31, 34, 84, 95, 96, 134], "hutter": [26, 27, 28, 29, 30, 34, 84, 95, 96, 134], "ball": [26, 27, 28, 29, 30, 31, 34, 72, 84, 95, 96, 134], "aug": [26, 34, 84, 95, 96, 134], "dx": [26, 34, 84, 88, 89, 95, 96, 134], "1002": [26, 27, 28, 29, 30, 34, 84, 95, 96, 134], "hbm": [26, 27, 28, 29, 30, 34, 84, 95, 96, 134], "23730": [26, 27, 28, 29, 30, 34, 84, 95, 96, 134], "__str__": 26, "976": [26, 27], "882": 26, "202": [26, 33], "quit": [26, 29], "popular": 26, "collect": [26, 67, 72, 119], "1024": 26, "simul": 26, "create_info": 26, "randn": 26, "256hz": 26, "epochsarrai": 26, "randint": [26, 31], "99609": 26, "off": [26, 29, 30, 107], "wrapper": [26, 28, 29], "form": [26, 45, 62, 69, 70, 71, 77], "facilit": [26, 140], "easiest": [26, 29], "former": [26, 67, 83, 86, 90, 119], "prefix": [26, 67, 119], "module__": 26, "validsplit": [26, 30, 67, 119], "module__final_conv_length": 26, "along": [26, 71, 77, 110, 138, 140], "8816": 26, "0141": 26, "0085": 26, "0071": 26, "0070": 26, "0078": 26, "0082": 26, "0068": 26, "0067": 26, "840": 26, "924": 26, "844": 26, "pre": [26, 78, 111, 140], "via": [26, 28, 29, 30, 103, 107, 137, 138, 140], "And": [26, 27], "nan": [26, 128], "unit_mul": 26, "fiff_unitm_non": 26, "cal": 26, "fiffv_eeg_ch": 26, "coil_typ": 26, "fiffv_coil_eeg": 26, "fiff_unit_v": 26, "coord_fram": 26, "fiffv_coord_head": 26, "scanno": 26, "logno": 26, "target_from": 26, "miss": [26, 32, 83, 86, 88, 90, 92, 93, 94, 95, 97, 103, 140], "manual": [26, 27, 29, 138], "974": [26, 33], "plot_basic_training_epoch": [26, 33], "push": [27, 67, 119], "produc": [27, 29, 32, 99], "neighbour": 27, "simultan": [27, 88, 89], "sub": [27, 140], "afterward": [27, 29, 83, 86, 90, 111], "implicitli": [27, 29, 32], "timestep": 27, "user": [27, 67, 119, 135, 137, 138, 140], "mostli": 27, "runtim": 27, "rule": [27, 67, 119], "mathemat": 27, "neighbourhood": 27, "At": [27, 69], "redund": 27, "lead": [27, 29, 67, 111, 119], "gradient": [27, 140], "likelihood": [27, 67], "typic": [27, 67, 105, 119], "locat": [27, 68], "anyth": [27, 67], "runtimewarn": 27, "config": [27, 68], "mne_datasets_bnci_path": 27, "set_config": 27, "get_config": 27, "urllib3": 27, "connectionpool": 27, "1061": 27, "insecurerequestwarn": 27, "unverifi": 27, "request": [27, 111, 135], "host": 27, "lampx": 27, "tugraz": 27, "certif": 27, "verif": 27, "readthedoc": 27, "en": 27, "advanc": [27, 137], "8k": 27, "169kb": 27, "121k": 27, "470kb": 27, "289k": 27, "925kb": 27, "665k": 27, "92mb": 27, "93mb": 27, "17m": 27, "24mb": 27, "83m": 27, "83mb": 27, "3mb": 27, "5mb": 27, "2mb": 27, "1mb": 27, "8mb": 27, "0mb": 27, "7mb": 27, "9mb": 27, "267gb": 27, "172kb": 27, "113k": 27, "432kb": 27, "296k": 27, "957kb": 27, "681k": 27, "97mb": 27, "31mb": 27, "89mb": 27, "6mb": 27, "177gb": 27, "0x7f3130efbeb0": 27, "definit": [27, 67, 119], "torchinfo": [27, 28, 29, 32, 91, 140], "tabl": [27, 28, 29, 30, 32, 83, 91, 140], "804": 27, "dens": [27, 91, 97, 98], "explicit": [27, 127], "deep4": [27, 28, 140], "nll_loss": 27, "2778": [27, 28], "5658": 27, "2535": [27, 28], "5302": 27, "9096": 27, "3090": 27, "4417": 27, "4977": 27, "percent": [27, 28], "misclass": [27, 28], "assign": [27, 28, 131], "train_misclass": [27, 28], "valid_misclass": [27, 28], "misclassif": [27, 28], "get_ylim": [27, 28], "room": [27, 28], "matric": [27, 28, 47, 48, 49, 67, 119], "label_dict": [27, 28], "i_class": [27, 28], "window_kwarg": [27, 28, 70], "kv": [27, 28], "conf": [27, 28], "640x480": [27, 28], "m\u00fcller": [27, 28, 29, 30], "aertsen": [27, 28, 29, 30], "birbaum": [27, 28, 29, 30], "braun": [27, 28, 29, 30], "brunner": [27, 28, 29, 30], "leeb": [27, 28, 29, 30], "mehr": [27, 28, 29, 30], "mueller": [27, 28, 29, 30], "putz": [27, 28, 29, 30], "nolt": [27, 28, 29, 30], "2012": [27, 28, 29, 30], "review": [27, 28, 29, 30], "frontier": [27, 28, 29, 30, 34], "neurosci": [27, 28, 29, 30, 34], "burgard": [27, 28, 29, 30, 34], "hum": [27, 28, 29, 30], "5420": [27, 28, 29, 30, 31], "913": [27, 33], "747": 27, "plot_bcic_iv_2a_moabb_crop": [27, 33], "classic": 28, "0x7f3131388eb0": 28, "benefici": 28, "6093": 28, "5148": 28, "2708": 28, "4426": 28, "4172": 28, "3333": 28, "2141": 28, "7940": 28, "4043": 28, "3438": 28, "1842": 28, "4347": 28, "4155": 28, "jayaram": [28, 29, 30], "vinai": [28, 29, 30], "alexandr": [28, 29, 30, 34], "barach": [28, 29, 30], "trustworthi": [28, 29, 30], "066011": [28, 29, 30], "274": [28, 33, 140], "plot_bcic_iv_2a_moabb_tri": [28, 33], "properli": [29, 107, 110, 111], "exclus": [29, 32], "elabor": [29, 32], "feel": [29, 32], "free": [29, 32], "distinguish": 29, "scheme": [29, 32, 111, 140], "answer": [29, 32], "reliabl": [29, 32], "sound": [29, 32], "divis": [29, 32, 97, 99, 116], "But": [29, 32], "stori": [29, 32], "learnabl": 29, "connect": [29, 30, 83, 86, 90, 97, 103], "bias": 29, "capac": [29, 30], "ml": [29, 32], "degre": [29, 32, 46, 47, 48, 49, 63], "freedom": [29, 32], "kept": [29, 32], "leakag": [29, 32], "memor": [29, 32], "longer": [29, 32, 67, 119], "independ": [29, 32, 41, 59, 107, 140], "never": [29, 32], "explicitli": [29, 32, 107, 108, 111], "recogn": [29, 32], "behind": [29, 32], "alwai": [29, 32, 34, 53, 67, 119], "readabl": [29, 32, 107], "reiniti": [29, 32], "rescal": [29, 30], "varianc": [29, 30, 116], "0x7f31310d3a90": 29, "One": [29, 30, 69, 88, 89], "demarc": [29, 30], "stimulu": [29, 30], "trial_stop_offset_second": [29, 30], "0test": 29, "matter": [29, 32, 75, 76], "distinct": [29, 32], "previous": [29, 32], "credibl": [29, 32], "test_acc": [29, 32], "2071": 29, "3661": 29, "0997": 29, "patch": 29, "font_scal": 29, "plot_simple_train_test": 29, "all_dataset": 29, "bd_cmap": 29, "3a6190": 29, "683e00": 29, "ddf2ff": 29, "2196f3": 29, "ndataset": 29, "nsplit": 29, "invert_yaxi": 29, "ncol": 29, "bbox_to_anchor": 29, "set_xlim": 29, "risk": [29, 45, 62, 129], "tweak": 29, "until": [29, 69], "realli": 29, "unreli": 29, "ratio": 29, "leav": [29, 140], "empti": [29, 67, 107, 111], "x_train": 29, "train_indic": 29, "val_indic": 29, "indices_": 29, "train_subset": 29, "val_subset": 29, "meaning": 29, "3435": 29, "3505": 29, "2759": [29, 30], "2666": 29, "9983": 29, "3478": 29, "1789": 29, "0685": 29, "9464": 29, "compact": [29, 92, 93], "plot_train_valid_test": 29, "n_train": 29, "n_val": 29, "n_test": 29, "suffici": 29, "compens": [29, 107], "unseen": 29, "holdout": 29, "highli": 29, "cross_val_scor": 29, "splitter": 29, "train_val_split": 29, "By": [29, 30, 31, 45, 67, 119], "processor": [29, 30], "cv_result": 29, "3870": 29, "2082": 29, "9267": 29, "3957": 29, "1560": 29, "8368": 29, "2870": 29, "2641": 29, "2266": 29, "8351": 29, "4000": 29, "3003": 29, "8402": 29, "4087": [29, 30], "1477": 29, "8295": 29, "2727": 29, "2076": 29, "8570": 29, "2900": 29, "1233": 29, "8363": 29, "4242": 29, "1577": 29, "8342": 29, "4286": 29, "0504": 29, "8276": 29, "plot_k_fold": 29, "fraction": [29, 31], "ii": 29, "tr_idx": 29, "val_idx": 29, "n_train2": 29, "rotat": [29, 46, 47, 48, 49, 63, 134], "verticalalign": 29, "horizontalalign": 29, "transax": 29, "earli": 29, "rough": 29, "quickli": 29, "messi": 29, "jointli": 29, "analog": [29, 127], "grid": [29, 30], "tupl": [29, 30, 45, 53, 62, 67, 71, 74, 91, 104, 110, 117, 119, 122, 134], "00625": [29, 30], "000625": 29, "best_paramet": 29, "2826": 29, "5258": 29, "0063": [29, 30], "9264": 29, "4053": 29, "8297": 29, "4826": 29, "2205": 29, "8301": 29, "5130": [29, 30], "1218": 29, "8310": 29, "4375": 29, "2991": 29, "1621": 29, "4688": 29, "1161": 29, "replac": [29, 51, 65, 140], "571": [29, 33], "395": [29, 33], "plot_how_train_test_and_tun": [29, 33], "sensit": [30, 69, 134], "hyeperparamet": 30, "signific": 30, "discrimin": 30, "pathologi": 30, "playbook": 30, "googl": 30, "0x7f31312d2b30": 30, "functool": 30, "partial": 30, "analyz": 30, "initialis": [30, 119], "slice": [30, 107, 108, 112, 113], "fine": 30, "learning_r": 30, "0000625": 30, "module__drop_prob": 30, "got": 30, "5304": 30, "0774": 30, "1724": 30, "0998": 30, "5723": 30, "6174": 30, "2069": 30, "8704": 30, "5342": 30, "3565": 30, "3448": 30, "3154": 30, "5297": 30, "1784": 30, "8569": 30, "5363": 30, "2348": 30, "5185": 30, "0333": 30, "5407": 30, "4272": 30, "3804": 30, "5287": 30, "6046": 30, "3103": 30, "8912": 30, "5303": 30, "3911": 30, "7741": 30, "5316": 30, "7828": 30, "9789": 30, "5350": 30, "5826": 30, "1250": 30, "5773": 30, "2609": 30, "5664": 30, "3793": 30, "1215": [30, 31], "5364": 30, "4696": 30, "4854": 30, "4483": 30, "7465": 30, "5313": 30, "2261": 30, "7070": 30, "1473": 30, "2435": 30, "6492": 30, "8568": 30, "5394": 30, "2783": 30, "5837": 30, "4035": 30, "5385": 30, "2696": 30, "5464": 30, "1272": 30, "5362": 30, "1099": 30, "2171": 30, "5305": 30, "8860": 30, "9000": 30, "1420": 30, "4138": 30, "5093": 30, "5308": 30, "5210": 30, "3900": 30, "5370": 30, "8493": 30, "5397": 30, "9960": 30, "3377": 30, "5299": 30, "2516": 30, "5048": 30, "5306": 30, "1913": 30, "1263": 30, "0232": 30, "5401": 30, "2739": 30, "2403": 30, "2586": 30, "1557": 30, "0719": 30, "7535": 30, "9383": 30, "1192": 30, "pivot": 30, "heatmap": 30, "pivot_t": 30, "param_optimizer__lr": 30, "param_module__drop_prob": 30, "fmt": 30, "3f": 30, "cmap": 30, "ylgnbu": 30, "cbar": 30, "model_build": [30, 32], "plot_hyperparameter_tuning_with_scikit": [30, 33], "332": 30, "constructor": 30, "numer": [30, 113], "sequenc": [30, 35, 40, 67, 100, 102, 119, 120, 123, 130, 138, 140], "varun": 30, "godbol": 30, "georg": 30, "dahl": 30, "justin": 30, "gilmer": 30, "christoph": 30, "shallu": 30, "zachari": 30, "nado": 30, "tuning_playbook": 30, "271": [30, 33], "106": 30, "sara": [31, 140], "sedlar": [31, 140], "n_fake_rec": 31, "sinusoid": 31, "gaussian": [31, 43, 60], "nois": [31, 43, 60, 69], "n_fake_ch": 31, "fake_dur": 31, "fake_sfreq": 31, "basedataset": [31, 35, 70, 77, 81, 118, 140], "create_mne_dummy_raw": 31, "fake_regression_dataset": 31, "n_fake_target": 31, "fake_data_split": 31, "target_subset": 31, "sin": 31, "pi": [31, 41, 59], "_data": 31, "expand_dim": 31, "fake_descript": 31, "n_fake_chan": 31, "2999": 31, "990": 31, "model_nam": 31, "deepconvnet": 31, "unknown": [31, 127], "610": 31, "minim": [31, 45, 62, 129, 135], "mse": 31, "ground": [31, 69, 72], "truth": 31, "period": 31, "schedul": [31, 32], "optimizer_lr": 31, "optimizer_weight_decai": 31, "neg_root_mean_squared_error": 31, "train_neg_root_mean_squared_error": 31, "valid_neg_root_mean_squared_error": 31, "2505": 31, "9371": 31, "9685": 31, "0010": 31, "8932": 31, "9601": 31, "1443": 31, "2920": 31, "5329": 31, "8717": 31, "3129": 31, "0412": 31, "2603": 31, "4996": 31, "8760": 31, "root": [31, 139], "squar": [31, 96, 119], "rmse": 31, "0x7f3130f17cd0": 31, "versu": 31, "trend": 31, "y_estim": 31, "ravel": 31, "y_gt": 31, "to_numpi": [31, 125, 126, 127], "polyfit": 31, "poly1d": 31, "kingma": 31, "diederik": 31, "jimmi": 31, "ba": 31, "stochast": 31, "1412": 31, "6980": 31, "2014": [31, 69], "reddi": 31, "sashank": 31, "satyen": 31, "kale": 31, "sanjiv": 31, "kumar": 31, "beyond": [31, 45, 62, 129], "1904": 31, "09237": 31, "675": [31, 33], "plot_regress": [31, 33], "goal": [32, 88, 89, 90], "percept": 32, "adjustmenty": 32, "third": 32, "0x7f3130eee770": 32, "real": 32, "world": 32, "updat": [32, 67, 68, 70, 71, 77, 80, 113, 117, 119, 138, 140], "tqdm": 32, "train_one_epoch": 32, "loss_fn": 32, "print_batch_stat": 32, "progress_bar": 32, "disabl": [32, 67, 107, 119], "batch_idx": 32, "argmax": 32, "sum": [32, 140], "6f": 32, "accumul": 32, "doesn": [32, 67, 68, 119], "test_model": 32, "n_batch": [32, 124, 128], "test_loss": 32, "batch_loss": 32, "nnloss": 32, "seamlessli": 32, "train_load": 32, "test_load": 32, "test_accuraci": 32, "784639": 32, "85it": 32, "497504": 32, "16it": 32, "544960": 32, "33it": 32, "552846": 32, "28it": 32, "648800": 32, "05it": 32, "62it": 32, "067336": 32, "475679": 32, "69it": 32, "224905": 32, "333737": 32, "09it": 32, "520595": 32, "76it": 32, "324450": 32, "605750": 32, "460681": 32, "67it": 32, "178580": 32, "66it": 32, "232657": 32, "294503": 32, "61it": 32, "144602": 32, "41it": 32, "03it": 32, "412822": 32, "751318": 32, "71it": 32, "565414": 32, "667956": 32, "68it": 32, "836547": 32, "646811": 32, "262205": 32, "nice": 32, "interfac": [32, 34, 88, 89, 92, 93], "previou": [32, 140], "torchmetr": 32, "litmodul": 32, "lightningmodul": 32, "training_step": 32, "y_hat": 32, "test_step": 32, "multiclass": 32, "num_class": 32, "log_dict": 32, "configure_optim": 32, "trainer": 32, "lit_model": 32, "tpu": 32, "ipu": 32, "hpu": 32, "connector": 32, "logger_connector": 32, "tensorboardx": 32, "conflict": [32, 67, 119], "ecosystem": 32, "logger": 32, "csvlogger": 32, "unless": [32, 119], "tensorboard": 32, "pip": [32, 137, 138, 139, 140], "instal": [32, 67, 107, 110, 119, 140], "extra": [32, 140], "lightning_log": 32, "189": 32, "data_connector": 32, "441": 32, "train_dataload": 32, "fit_loop": 32, "293": 32, "interv": [32, 72, 113], "log_every_n_step": 32, "87it": 32, "v_num": 32, "21it": 32, "30it": 32, "38it": 32, "74it": 32, "64it": 32, "63it": 32, "58it": 32, "01it": 32, "00it": 32, "checkpoint_connector": 32, "145": 32, "ckpt_path": 32, "silenc": 32, "restor": [32, 67], "state": [32, 120, 121, 122, 123], "version_0": 32, "ckpt": 32, "test_dataload": 32, "81it": 32, "59it": 32, "02it": 32, "48it": 32, "22it": 32, "34375": 32, "5098872184753418": 32, "524": [32, 33, 140], "289": 32, "plot_train_in_pure_pytorch_and_pytorch_lightn": [32, 33], "auto_examples_model_build": 33, "746": 33, "288": [33, 69, 140], "scientif": 34, "softwar": [34, 135], "canon": 34, "hbm23730": 34, "robin": [34, 140], "tibor": [34, 140], "jost": 34, "tobia": 34, "dominiqu": 34, "josef": 34, "martin": [34, 140], "katharina": 34, "michael": 34, "frank": 34, "wolfram": 34, "tonio": 34, "issn": 34, "1097": 34, "0193": 34, "url": 34, "keyword": [34, 35, 73, 105, 107, 108, 109, 110, 111, 117], "electroencephalographi": 34, "interpret": [34, 39, 56, 107, 108, 119], "built": [34, 135], "zenodo": 34, "ask": [34, 69], "3389": 34, "fnin": 34, "2013": 34, "00267": 34, "luessi": 34, "larson": 34, "eric": 34, "deni": [34, 140], "strohmeier": 34, "brodbeck": 34, "christian": 34, "goj": 34, "roman": 34, "ja": 34, "mainak": 34, "brook": 34, "teon": 34, "parkkonen": 34, "lauri": 34, "h\u00e4m\u00e4l\u00e4inen": 34, "matti": 34, "volum": 34, "267": 34, "frontiersin": 34, "1662": 34, "453x": 34, "appropri": [34, 138], "kwarg": [35, 67, 91, 109, 119, 125, 126, 127], "max_freq": 36, "band": [36, 54, 107, 117, 140], "desir": [36, 46, 54, 63, 69, 105, 111], "suggest": [36, 39, 43, 46, 47, 48, 49, 51, 54, 56, 60, 63, 80, 113], "distanc": [36, 54, 69], "admiss": 36, "1hz": 36, "nyquist": 36, "cheng": [36, 43, 51, 54, 60, 65], "goh": [36, 43, 51, 54, 60, 65], "dogrusoz": [36, 43, 51, 54, 60, 65], "tuzel": [36, 43, 51, 54, 60, 65], "azemi": [36, 43, 51, 54, 60, 65], "awar": [36, 43, 51, 54, 60, 65], "biosign": [36, 43, 51, 54, 60, 65], "04871": [36, 43, 51, 54, 60, 65], "mohsenvand": [36, 43, 51, 54, 60, 65], "izadi": [36, 43, 51, 54, 60, 65], "mae": [36, 43, 51, 54, 60, 65], "electroencephalogram": [36, 43, 51, 54, 60, 65], "health": [36, 43, 51, 54, 60, 65], "238": [36, 43, 51, 54, 60, 65], "253": [36, 43, 51, 54, 60, 65], "pmlr": [36, 43, 51, 54, 60, 65], "get_augmentation_param": [36, 37, 38, 39, 41, 42, 43, 45, 46, 51, 53, 140], "freqs_to_notch": [36, 54], "greater": [36, 54], "static": [36, 37, 38, 39, 41, 42, 43, 44, 45, 46, 50, 51, 52, 68], "cmsaugment": [37, 38, 55, 57], "polici": [37, 38, 55, 57], "proba_drop": 37, "eras": 37, "saeed": [37, 38, 55, 57], "grangier": [37, 38, 55, 57], "pietquin": [37, 38, 55, 57], "zeghidour": [37, 38, 55, 57], "heterogen": [37, 38, 55, 57], "differenti": [37, 38, 55, 57], "reorder": [37, 38, 55, 57], "2010": [37, 38, 55, 57, 72], "13694": [37, 38, 55, 57], "p_shuffl": [38, 57], "permut": [38, 39, 45, 56, 57, 62], "carri": [38, 57, 69], "ordered_ch_nam": [39, 47, 48, 49], "invert": 39, "side": [39, 107], "nomenclatur": 39, "deiss": [39, 56], "biswal": [39, 56], "jin": [39, 56], "sun": [39, 56], "westov": [39, 56], "hamlet": [39, 56], "co": [39, 56], "techniqu": [39, 56, 107, 111], "1803": [39, 56, 100], "09702": [39, 56], "accord": [39, 56, 111], "channel_indep": [41, 59], "ft": [41, 59, 83], "surrog": [41, 59], "perturb": [41, 59], "uniformli": [41, 45, 46, 47, 48, 49, 59, 120], "schwabed": [41, 59], "snyder": [41, 59], "cakmak": [41, 59], "nemati": [41, 59], "clifford": [41, 59], "address": [41, 59], "imbal": [41, 59, 74], "noisi": [41, 59], "fourier": [41, 59], "1806": [41, 59], "08675": [41, 59], "magnitud": [41, 51], "cliffordlab": [41, 59], "tf": [41, 59], "draw": [41, 59], "maximum": [42, 46, 47, 48, 49, 83, 112], "absolut": 42, "delta_freq": [42, 58], "amplitud": [42, 58, 112, 113, 140], "white": [43, 60], "deviat": [43, 60], "wang": [43, 60], "zhong": [43, 60], "jiang": [43, 60], "liu": [43, 60, 86], "emot": [43, 60], "recognit": [43, 60], "confer": [43, 45, 46, 47, 48, 49, 60, 62, 63], "multimedia": [43, 60], "beta_per_sampl": 45, "drawn": 45, "beta": 45, "hongyi": [45, 62, 129], "zhang": [45, 62, 90, 129], "moustapha": [45, 62, 129], "ciss": [45, 62, 129], "yann": [45, 62, 129], "dauphin": [45, 62, 129], "david": [45, 62, 129], "lopez": [45, 62, 129], "paz": [45, 62, 129], "empir": [45, 62, 100, 129], "iclr": [45, 62], "onlin": [45, 62, 84, 88, 89, 95, 96, 129, 134], "1710": [45, 62, 129], "09412": [45, 62, 129], "facebookresearch": [45, 62, 129], "cifar10": [45, 62, 129], "interpol": [45, 46, 47, 48, 49, 62, 63], "lam": [45, 62], "idx_perm": [45, 62], "sensors_positions_matrix": [46, 63], "max_degre": [46, 47, 48, 49], "spherical_splin": [46, 47, 48, 49, 63], "angl": [46, 47, 48, 49, 63, 134], "3d": [46, 63, 140], "cartesian": [46, 63], "coordin": [46, 63], "ten_twenty_montag": [46, 63], "make_standard_montag": [46, 63], "standard_1020": [46, 63], "get_posit": [46, 63], "ch_po": [46, 63], "spheric": [46, 47, 48, 49, 63], "spline": [46, 47, 48, 49, 63], "scipi": [46, 47, 48, 49, 63, 67, 107, 110, 119], "rbf": [46, 47, 48, 49, 63], "quadrat": [46, 47, 48, 49, 63], "krell": [46, 47, 48, 49, 63], "kim": [46, 47, 48, 49, 63, 90], "electroencephalograph": [46, 47, 48, 49, 63], "39th": [46, 47, 48, 49, 63], "annual": [46, 47, 48, 49, 63], "medicin": [46, 47, 48, 49, 63], "biologi": [46, 47, 48, 49, 63], "societi": [46, 47, 48, 49, 63], "embc": [46, 47, 48, 49, 63], "471": [46, 47, 48, 49, 63], "474": [46, 47, 48, 49, 63], "element": [46, 51, 63], "montag": [47, 48, 49, 69], "flip": [50, 52, 64, 66], "sign": [50, 64], "smoothli": [51, 65], "Will": 51, "mask_start_per_sampl": [51, 65], "resp": 53, "uniform": 53, "arg": [67, 91, 119], "iterator_train__drop_last": [67, 119, 140], "uninstanti": [67, 119], "get_loss": 67, "classes_": 67, "attributeerror": 67, "sgd": [67, 119], "outcom": [67, 119], "keyboard": [67, 119], "interrupt": [67, 119], "mini": [67, 119], "iterator_train__batch_s": [67, 119], "iterator_test__batch_s": [67, 119], "iterator_valid": [67, 119], "incom": [67, 119], "__len__": [67, 119], "deal": [67, 119], "box": [67, 119], "dataset__": [67, 119], "initialz": [67, 119], "dataset_train": [67, 119, 125, 126, 127], "dataset_valid": [67, 119, 125, 126, 127], "get_default_callback": [67, 119], "resolv": [67, 119], "suffix": [67, 119], "epochscoring_1": [67, 119], "print_log": [67, 119], "callbacks__print_log__keys_ignor": [67, 119], "predict_nonlinear": [67, 119], "pickleabl": [67, 119], "accept": [67, 80, 102, 113, 119], "predict_proba": [67, 119, 140], "whatev": [67, 119], "anywher": [67, 119], "notabl": [67, 119], "unaffect": [67, 119], "warm_start": [67, 119], "cold": [67, 119], "warm": [67, 119], "summari": [67, 91, 101, 119], "regardless": [67, 119], "acceler": [67, 119], "sent": [67, 119], "unmodifi": [67, 119], "compil": [67, 119], "volta": [67, 119], "amper": [67, 119], "dunder": [67, 119], "notat": [67, 119], "compile__dynam": [67, 119], "dynam": [67, 119], "use_cach": [67, 119, 125, 126], "overrid": [67, 68, 119], "cach": [67, 119], "batchscor": [67, 119], "certain": [67, 119], "situat": [67, 119], "tight": [67, 119], "cumbersom": [67, 119], "global": [67, 119, 127], "honor": [67, 119], "prefer": [67, 119], "model_evalu": [67, 119], "prefixes_": [67, 119], "special": [67, 119], "neuralnet": [67, 119], "optimizer__momentum": [67, 119], "popul": [67, 119, 140], "cuda_dependent_attributes_": [67, 119], "whose": [67, 80, 113, 119], "unpickl": [67, 119], "expand": [67, 103, 119], "initialized_": [67, 119], "criterion_": [67, 119], "callbacks_": [67, 119], "_modul": [67, 119], "_criteria": [67, 119], "_optim": [67, 119], "get_iter": [67, 119], "drop_index": [67, 119], "iterator_test": [67, 119], "spars": [67, 119], "csr": [67, 119], "y_proba": [67, 119], "trial_predict": [67, 119, 130], "n_trial": [67, 78, 119, 130], "n_predict": [67, 119, 124, 128, 130], "trial_label": [67, 119, 130], "n_target": [67, 119, 130], "bbci": 68, "de": 68, "desc_4": 68, "pdf": 68, "force_upd": 68, "mne_datasets_": 68, "_path": 68, "forc": 68, "iia": 69, "r382d436f3223": 69, "cue": [69, 72], "imag": [69, 88, 89], "inat": 69, "movement": [69, 72], "compris": 69, "sit": 69, "comfort": 69, "armchair": 69, "front": 69, "screen": 69, "fixat": 69, "acoust": 69, "tone": 69, "arrow": [69, 72], "down": [69, 97, 103, 110, 132], "foot": 69, "prompt": [69, 135], "disappear": 69, "twenti": 69, "agcl": 69, "inter": [69, 72], "monopolarli": 69, "mastoid": [69, 111], "amplifi": 69, "\u03bcv": 69, "notch": 69, "suppress": [69, 107], "raw_preproc_kwarg": 70, "window_preproc_kwarg": 70, "old": [70, 118, 140], "datapoint": 70, "gamma": 72, "subj": 72, "500hz": 72, "r5e478952091a": 72, "cover": [72, 134], "cortex": 72, "healthi": [72, 74], "963": 72, "divid": [72, 78, 79, 80, 112], "rest": [72, 111], "approx": 72, "880": 72, "except": [72, 74], "acquir": 72, "lab": 72, "invas": 72, "2008": [72, 85], "darva": 72, "direct": [72, 135], "grai": 72, "back": 72, "had": [72, 88, 89, 91], "clench": 72, "toe": 72, "downward": 72, "tap": 72, "leftward": 72, "rightward": 72, "relax": 72, "upward": 72, "littl": 72, "proxim": 72, "muscular": 72, "volv": 72, "pace": 72, "maintain": 72, "pseudo": 72, "ideal": 72, "260": 72, "stimuli": 72, "bci2000": 72, "schalk": 72, "2004": 72, "approv": 72, "ethic": 72, "committe": 72, "freiburg": 72, "dataset_kwarg": 73, "load_eeg_onli": 74, "content": 74, "edfx": 74, "overnight": 74, "auto_tutori": 74, "plot_sleep": 74, "eog": [74, 103], "emg": 74, "temperatur": 74, "respir": 74, "3h": 74, "parent": [75, 76], "ascend": [75, 76], "preserv": [75, 76], "physician": [75, 76], "c_tuab": 76, "i_window_in_tri": [77, 121, 131], "i_start_in_tri": [77, 121], "i_stop_in_tri": [77, 121, 131], "applic": [77, 107], "drop_bad_window": [80, 113], "accepted_bads_ratio": [80, 113], "onset": [80, 113], "fall": [80, 113], "outsid": [80, 113], "proport": [80, 88, 89, 113], "withinconsist": 80, "exceed": [80, 113], "pathlib": 81, "concat_dataset": [81, 82], "conv_block_n_filt": 83, "conv_block_kernel_length_1": 83, "conv_block_kernel_length_2": 83, "conv_block_pool_size_1": 83, "conv_block_pool_size_2": 83, "conv_block_depth_mult": 83, "conv_block_dropout": 83, "att_head_dim": 83, "att_num_head": 83, "att_dropout": 83, "tcn_depth": 83, "tcn_kernel_s": 83, "tcn_n_filter": 83, "tcn_dropout": 83, "tcn_activ": 83, "max_norm_const": 83, "input_size_": [83, 97, 98, 99, 103], "offici": [83, 138], "tensorflow": 83, "block": [83, 88, 89, 90, 100, 103], "denot": 83, "kc": 83, "p2": 83, "depthwis": [83, 88, 89], "pc": 83, "head": [83, 86, 99, 121], "dh": 83, "1_": 83, "pa": 83, "residu": [83, 94], "kt": 83, "slid": 83, "feed": [83, 99], "logit": 83, "contrari": 83, "constraint": 83, "impos": 83, "altaheri": 83, "muhammad": 83, "alsulaiman": 83, "physic": 83, "industri": 83, "informat": 83, "tii": 83, "3197419": 83, "overridden": [83, 86, 90], "subclass": [83, 86, 90], "recip": [83, 86, 90], "care": [83, 86, 90], "regist": [83, 86, 90], "hook": [83, 86, 90, 140], "latter": [83, 86, 90], "silent": [83, 86, 90], "first_conv_nonlin": 84, "first_pool_nonlin": 84, "later_conv_nonlin": 84, "later_pool_nonlin": 84, "supratak": 85, "bidirect": 85, "supratak2017": 85, "dong": 85, "wu": 85, "guo": 85, "1998": 85, "att_depth": 86, "att_head": 86, "att_drop_prob": 86, "final_fc_length": 86, "2440": 86, "return_featur": 86, "conform": 86, "methodolog": 86, "song2022": 86, "conformercod": 86, "tradit": 86, "n_timestep": 86, "compos": 86, "patchembed": 86, "transformerencod": 86, "classificationhead": 86, "recombin": 86, "song": [86, 140], "zheng": 86, "q": 86, "gao": 86, "710": 86, "719": 86, "ieeexplor": 86, "9991178": 86, "eeyhsong": 86, "get_fc_siz": 86, "in_channel": [87, 88, 89, 90], "itnet": [87, 140], "incept": [87, 88, 89, 90, 140], "salami": 87, "salami2022": 87, "abbassalami": 87, "guarante": [87, 88, 89, 90, 92, 93], "reimplement": [87, 88, 89, 90, 92, 93], "andreu": 87, "perez": 87, "gillmeist": 87, "3161489": 87, "scales_samples_": [88, 89], "125": [88, 89, 98], "n_filter": [88, 89, 90, 100], "depth_multipli": [88, 89], "pooling_s": [88, 89], "erp": [88, 89], "AND": 88, "WILL": 88, "BE": 88, "IN": 88, "THE": 88, "OF": 88, "santamaria2020": [88, 89], "inceptionnet": [88, 89, 90], "largest": [88, 89], "associ": [88, 89], "winner": [88, 89], "beetl": [88, 89], "neurip": [88, 89], "r15fdf33b022f": 88, "santamaria": [88, 89], "vazquez": [88, 89], "martinez": [88, 89], "cagig": [88, 89], "vaquerizo": [88, 89], "villar": [88, 89], "hornero": [88, 89], "assist": [88, 89], "3048106": [88, 89], "grifcc": [88, 89], "r37c4761d4e92": 89, "n_conv": 90, "kernel_unit_": 90, "input_window_": 90, "vision": 90, "wide": 90, "branch": 90, "1d": 90, "bose": 90, "eskandarian": 90, "accur": 90, "robust": 90, "046014": 90, "mixin": 91, "output_shap": [91, 104], "get_torchinfo_statist": 91, "col_nam": 91, "input_s": 91, "num_param": 91, "row_set": 91, "modelstatist": 91, "load_state_dict": 91, "state_dict": 91, "intermedi": 91, "bug": 91, "second_kernel_s": 92, "third_kernel_s": [92, 93], "eegnet": [92, 93], "lawhern": [92, 93], "2016": 92, "solon": [92, 93], "waytowich": [92, 93], "gordon": [92, 93], "hung": [92, 93], "lanc": [92, 93], "1611": [92, 93], "08024": [92, 93], "f2": 93, "kernel_length": 93, "v4": 93, "eegnet4": 93, "final_pool_length": [94, 140], "n_first_filt": 94, "n_layers_per_block": 94, "first_filter_length": 94, "batch_norm_epsilon": 94, "conv_weight_init_fn": 94, "hybrid": 95, "safe_log": 96, "n_conv_chan": 97, "n_group": 97, "max_pool_s": 97, "blanco": 97, "blanco2020": 97, "seven": 97, "group": 97, "fernandez": 97, "rivero": 97, "pazo": 97, "soft": 97, "4067": 97, "4079": 97, "1007": 97, "s00500": 97, "04174": 97, "time_conv_size_": [98, 103], "max_pool_size_": 98, "pad_size_": 98, "half": [98, 107], "n_tce": 99, "d_model": 99, "d_ff": 99, "n_attn_head": 99, "after_reduced_cnn_s": 99, "multi": 99, "resolut": 99, "mrcnn": 99, "recalibr": 99, "tce": 99, "mechan": [99, 140], "captur": 99, "among": 99, "100hz": 99, "125hz": 99, "shh": 99, "unintend": 99, "clone": [99, 140], "positionwisefeedforward": 99, "emadeldeen24": 99, "attnsleep": 99, "sleepdata": 99, "n_block": 100, "n_in_chan": 100, "bai": 100, "bai2018": 100, "locuslab": 100, "kolter": 100, "koltun": 100, "recurr": 100, "01271": 100, "s_growth": 101, "t_filter": 101, "temp_lay": 101, "spat_lay": 101, "temp_span": 101, "thinker": [101, 140], "invari": [101, 140], "densenet": 101, "kosta": 101, "growth": 101, "densefilt": 101, "percentag": 101, "temp_len": 101, "spoclab": 101, "ca": 101, "thinkerinvari": 101, "rudzicz": 101, "across": [101, 111, 120, 124], "peopl": 101, "eng": 101, "056008": 101, "1741": 101, "2552": 101, "abb7a7": 101, "stager": 102, "middl": 102, "seq_len": 102, "n_time_filt": 103, "complexity_factor": 103, "0703125": 103, "ensure_odd_conv_s": 103, "autoencod": 103, "shrink": 103, "fewer": [103, 107], "2x2": 103, "halv": 103, "ne": 103, "subsequ": 105, "time_as_index": 105, "first_samp": 105, "last_samp": 105, "exce": 105, "exclud": [105, 107, 108, 111], "on_miss": [106, 112, 113], "emit": 106, "evok": [106, 107, 108, 111], "reorder_channel": 106, "drop_channel": 106, "filter_length": 107, "l_trans_bandwidth": 107, "h_trans_bandwidth": 107, "iir_param": 107, "fir_window": 107, "fir_design": 107, "skip_by_annot": 107, "bad_acq_skip": 107, "reflect_limit": [107, 110], "iir": 107, "meg0111": [107, 108], "meg2623": [107, 108], "reciproc": 107, "shortest": 107, "firwin2": 107, "5500m": 107, "doubl": 107, "cupi": [107, 110], "filtfilt": 107, "4th": 107, "butterworth": 107, "construct_iir_filt": 107, "symmetr": 107, "construct": [107, 111], "delai": [107, 140], "twice": 107, "minimum": 107, "weaker": 107, "lfilter": 107, "hann": 107, "blackman": 107, "concatenate_raw": 107, "acquisit": 107, "reflect": [107, 110], "mirror": [107, 110], "create_filt": 107, "savgol_filt": 107, "notch_filt": 107, "filter_data": 107, "apply_funct": 109, "raw_or_epoch": 109, "npad": 110, "boxcar": 110, "joint": 111, "virtual": 111, "infin": 111, "footcit": 111, "yao2001": 111, "apply_proj": 111, "seeg": 111, "projector": 111, "set_bipolar_refer": 111, "bipolar": 111, "m1": 111, "m2": 111, "concatdataset": 112, "ie": 112, "winddow_size_sampl": 112, "exactli": 113, "inconsist": 113, "demeanin": 115, "exponent": [115, 116], "m_t": [115, 116], "mathrm": [115, 116], "factornew": [115, 116], "cdot": [115, 116], "x_t": [115, 116], "m_": [115, 116], "deman": 115, "_t": [115, 116], "demean": 115, "Then": 116, "v_t": 116, "v_": 116, "sqrt": 116, "stabil": 116, "frequency_band": 117, "drop_original_sign": 117, "order_by_frequency_band": 117, "mne_filter_kwarg": 117, "unfilt": 117, "cz_4": 117, "o1_4": 117, "cz_8": 117, "o1_8": 117, "fileexistserror": 118, "n_sequenc": [120, 123], "inspir": 120, "perslev2021": 120, "recordingsampl": [120, 122, 123], "randomst": [120, 121, 122, 123], "sample_class": 120, "rec_ind": [120, 121], "session_t": 121, "run_0": 121, "multiindex": 121, "sample_record": 121, "sample_window": 121, "tau_max": 122, "banville2020": 122, "file_id": 123, "ensembl": [123, 140], "loss_funct": [124, 128], "target_extractor": [125, 126, 127], "on_epoch_end": [125, 126, 127], "on_batch_end": 126, "recomput": 127, "slightli": 127, "scorer": 127, "signatur": 127, "scalar": 127, "wors": 127, "tri": 127, "timeseri": 128, "window_len": 128, "mixup": [129, 140], "duplic": [131, 140], "2darrai": 131, "preds_per_tri": 131, "lack": 132, "pythonhashse": 132, "forum": 132, "ai": 132, "solv": [132, 140], "31628": 132, "use_deterministic_algorithm": 132, "linearsegmentedcolormap": 134, "textcolor": 134, "vmin": 134, "vmax": 134, "fontweight": 134, "rotate_row_label": 134, "rotate_col_label": 134, "with_f1_scor": 134, "norm_ax": 134, "rotate_precis": 134, "class_names_fonts": 134, "font": 134, "bold": 134, "heavi": 134, "ultrabold": 134, "ultralight": 134, "hard": 135, "happen": [135, 140], "mistak": 135, "corrupt": 135, "irregular": 135, "chat": 135, "bear": 135, "tracker": 135, "sure": 135, "ve": 135, "shell": 135, "__version__": [135, 139], "latest": [135, 138, 139], "replic": 135, "link": [135, 140], "anonym": 135, "portion": 135, "persist": 135, "smallest": 135, "past": 135, "backtick": 135, "contributor": [135, 139], "snippet": 135, "toolbox": 136, "electrophysiolog": 136, "fetcher": 136, "neuroscientist": 136, "who": 136, "neurophysiolog": 136, "pypi": 137, "repositori": 137, "beginn": 137, "familiar": 137, "instruct": 137, "contribut": [137, 139], "braincod": 138, "command": [138, 139], "nvidia": 138, "driver": 138, "cuda_path": 138, "troubleshoot": 138, "thing": 139, "enter": 139, "git": 139, "cd": 139, "repo": 139, "zipbal": 139, "master": 139, "egg": 139, "edit": 139, "verifi": 139, "guidelin": 139, "whats_new": 140, "incompat": 140, "429": 140, "431": 140, "mohammad": 140, "javad": 140, "oskar": 140, "st\u00f8rmer": 140, "417": 140, "454": 140, "yonghao": 140, "einop": 140, "466": 140, "467": 140, "marco": 140, "zamboni": 140, "468": 140, "refactor": 140, "470": 140, "conda": 140, "yml": 140, "ci": 140, "479": 140, "action": 140, "489": 140, "485": 140, "490": 140, "487": 140, "473": 140, "488": 140, "495": 140, "sylvain": 140, "chevalli": 140, "494": 140, "bruna": 140, "lope": 140, "491": 140, "enforc": 140, "497": 140, "env": 140, "505": 140, "friendli": 140, "\u015bliwowski": 140, "shallowfbcsp": 140, "sampler": 140, "504": 140, "th\u00e9o": 140, "dropchannel": 140, "seteegrefer": 140, "514": 140, "523": 140, "remi": 140, "delboui": 140, "535": 140, "529": 140, "528": 140, "539": 140, "541": 140, "hint": 140, "551": 140, "valentin": 140, "ioven": 140, "pyproject": 140, "toml": 140, "553": 140, "commit": 140, "556": 140, "461": 140, "e231": 140, "whitespac": 140, "untrac": 140, "flake8": 140, "transposit": 140, "_frequency_shift": 140, "446": 140, "matthieu": 140, "terri": 140, "451": 140, "465": 140, "wrong": 140, "538": 140, "546": 140, "397": 140, "flag": 140, "513": 140, "390": 140, "ghaith": 140, "bouallegu": 140, "371": 140, "389": 140, "exemplifi": 140, "349": 140, "unifi": 140, "378": 140, "wimpff": 140, "391": 140, "406": 140, "recoding_id": 140, "402": 140, "ft_surrog": 140, "409": 140, "get_param": 140, "388": 140, "alex": 140, "413": 140, "zscore": 140, "mnepreproc": 140, "numpypreproc": 140, "415": 140, "411": 140, "263": 140, "ann": 140, "kathrin": 140, "kiessner": 140, "henrik": 140, "bonsmann": 140, "vytauta": 140, "jankauska": 140, "254": 140, "thoma": 140, "287": 140, "aggregate_proba": 140, "294": 140, "312": 140, "balancedsequencesampl": 140, "295": 140, "277": 140, "318": 140, "261": 140, "cloneabl": 140, "347": 140, "353": 140, "333": 140, "365": 140, "367": 140, "mismatch": 140, "327": 140, "propag": 140, "269": 140, "favour": 140, "292": 140, "199": 140, "198": 140, "178": 140, "138": 140, "147": 140, "realiz": 140, "filterbank": 140, "158": 140, "159": 140, "timecrop": 140, "185": 140, "282": 140, "341": 140, "accident": 140, "167": 140, "compute_amplitude_gradi": 140, "4d": 140, "incorrect": 140, "146": 140, "169": 140, "window_s": 140, "148": 140, "171": 140, "155": 140, "223": 140, "favor": 140}, "objects": {"": [[0, 0, 0, "-", "braindecode"]], "braindecode.augmentation": [[35, 1, 1, "", "AugmentedDataLoader"], [36, 1, 1, "", "BandstopFilter"], [37, 1, 1, "", "ChannelsDropout"], [38, 1, 1, "", "ChannelsShuffle"], [39, 1, 1, "", "ChannelsSymmetry"], [40, 1, 1, "", "Compose"], [41, 1, 1, "", "FTSurrogate"], [42, 1, 1, "", "FrequencyShift"], [43, 1, 1, "", "GaussianNoise"], [44, 1, 1, "", "IdentityTransform"], [45, 1, 1, "", "Mixup"], [46, 1, 1, "", "SensorsRotation"], [47, 1, 1, "", "SensorsXRotation"], [48, 1, 1, "", "SensorsYRotation"], [49, 1, 1, "", "SensorsZRotation"], [50, 1, 1, "", "SignFlip"], [51, 1, 1, "", "SmoothTimeMask"], [52, 1, 1, "", "TimeReverse"], [53, 1, 1, "", "Transform"]], "braindecode.augmentation.BandstopFilter": [[36, 2, 1, "", "get_augmentation_params"], [36, 2, 1, "", "operation"]], "braindecode.augmentation.ChannelsDropout": [[37, 2, 1, "", "get_augmentation_params"], [37, 2, 1, "", "operation"]], "braindecode.augmentation.ChannelsShuffle": [[38, 2, 1, "", "get_augmentation_params"], [38, 2, 1, "", "operation"]], "braindecode.augmentation.ChannelsSymmetry": [[39, 2, 1, "", "get_augmentation_params"], [39, 2, 1, "", "operation"]], "braindecode.augmentation.Compose": [[40, 2, 1, "", "forward"]], "braindecode.augmentation.FTSurrogate": [[41, 2, 1, "", "get_augmentation_params"], [41, 2, 1, "", "operation"]], "braindecode.augmentation.FrequencyShift": [[42, 2, 1, "", "get_augmentation_params"], [42, 2, 1, "", "operation"]], "braindecode.augmentation.GaussianNoise": [[43, 2, 1, "", "get_augmentation_params"], [43, 2, 1, "", "operation"]], "braindecode.augmentation.IdentityTransform": [[44, 2, 1, "", "operation"]], "braindecode.augmentation.Mixup": [[45, 2, 1, "", "get_augmentation_params"], [45, 2, 1, "", "operation"]], "braindecode.augmentation.SensorsRotation": [[46, 2, 1, "", "get_augmentation_params"], [46, 2, 1, "", "operation"]], "braindecode.augmentation.SignFlip": [[50, 2, 1, "", "operation"]], "braindecode.augmentation.SmoothTimeMask": [[51, 2, 1, "", "get_augmentation_params"], [51, 2, 1, "", "operation"]], "braindecode.augmentation.TimeReverse": [[52, 2, 1, "", "operation"]], "braindecode.augmentation.Transform": [[53, 2, 1, "", "forward"], [53, 2, 1, "", "get_augmentation_params"]], "braindecode.augmentation.functional": [[54, 3, 1, "", "bandstop_filter"], [55, 3, 1, "", "channels_dropout"], [56, 3, 1, "", "channels_permute"], [57, 3, 1, "", "channels_shuffle"], [58, 3, 1, "", "frequency_shift"], [59, 3, 1, "", "ft_surrogate"], [60, 3, 1, "", "gaussian_noise"], [61, 3, 1, "", "identity"], [62, 3, 1, "", "mixup"], [63, 3, 1, "", "sensors_rotation"], [64, 3, 1, "", "sign_flip"], [65, 3, 1, "", "smooth_time_mask"], [66, 3, 1, "", "time_reverse"]], "braindecode.classifier": [[67, 1, 1, "", "EEGClassifier"]], "braindecode.classifier.EEGClassifier": [[67, 4, 1, "", "_criteria"], [67, 4, 1, "", "_modules"], [67, 4, 1, "", "_optimizers"], [67, 4, 1, "", "callbacks_"], [67, 4, 1, "", "classes_"], [67, 4, 1, "", "criterion_"], [67, 4, 1, "", "cuda_dependent_attributes_"], [67, 2, 1, "", "get_iterator"], [67, 2, 1, "", "get_loss"], [67, 4, 1, "", "initialized_"], [67, 4, 1, "", "module_"], [67, 2, 1, "", "predict"], [67, 2, 1, "", "predict_proba"], [67, 2, 1, "", "predict_trials"], [67, 4, 1, "", "prefixes_"]], "braindecode.datasets": [[68, 1, 1, "", "BCICompetitionIVDataset4"], [69, 1, 1, "", "BNCI2014001"], [70, 1, 1, "", "BaseConcatDataset"], [71, 1, 1, "", "BaseDataset"], [72, 1, 1, "", "HGD"], [73, 1, 1, "", "MOABBDataset"], [74, 1, 1, "", "SleepPhysionet"], [75, 1, 1, "", "TUH"], [76, 1, 1, "", "TUHAbnormal"], [77, 1, 1, "", "WindowsDataset"], [78, 3, 1, "", "create_from_X_y"], [79, 3, 1, "", "create_from_mne_epochs"], [80, 3, 1, "", "create_from_mne_raw"]], "braindecode.datasets.BCICompetitionIVDataset4": [[68, 2, 1, "", "download"]], "braindecode.datasets.BaseConcatDataset": [[70, 2, 1, "", "get_metadata"], [70, 2, 1, "", "save"], [70, 2, 1, "", "set_description"], [70, 2, 1, "", "split"]], "braindecode.datasets.BaseDataset": [[71, 2, 1, "", "set_description"]], "braindecode.datasets.WindowsDataset": [[77, 2, 1, "", "set_description"]], "braindecode.datautil": [[81, 3, 1, "", "load_concat_dataset"], [82, 3, 1, "", "save_concat_dataset"]], "braindecode.models": [[83, 1, 1, "", "ATCNet"], [84, 1, 1, "", "Deep4Net"], [85, 1, 1, "", "DeepSleepNet"], [86, 1, 1, "", "EEGConformer"], [87, 1, 1, "", "EEGITNet"], [88, 1, 1, "", "EEGInception"], [89, 1, 1, "", "EEGInceptionERP"], [90, 1, 1, "", "EEGInceptionMI"], [91, 1, 1, "", "EEGModuleMixin"], [92, 1, 1, "", "EEGNetv1"], [93, 1, 1, "", "EEGNetv4"], [94, 1, 1, "", "EEGResNet"], [95, 1, 1, "", "HybridNet"], [96, 1, 1, "", "ShallowFBCSPNet"], [97, 1, 1, "", "SleepStagerBlanco2020"], [98, 1, 1, "", "SleepStagerChambon2018"], [99, 1, 1, "", "SleepStagerEldele2021"], [100, 1, 1, "", "TCN"], [101, 1, 1, "", "TIDNet"], [102, 1, 1, "", "TimeDistributed"], [103, 1, 1, "", "USleep"], [104, 3, 1, "", "get_output_shape"]], "braindecode.models.ATCNet": [[83, 2, 1, "", "forward"]], "braindecode.models.DeepSleepNet": [[85, 2, 1, "", "forward"]], "braindecode.models.EEGConformer": [[86, 2, 1, "", "forward"], [86, 2, 1, "", "get_fc_size"]], "braindecode.models.EEGInceptionMI": [[90, 2, 1, "", "forward"]], "braindecode.models.EEGModuleMixin": [[91, 2, 1, "", "get_output_shape"], [91, 2, 1, "", "get_torchinfo_statistics"], [91, 2, 1, "", "load_state_dict"], [91, 2, 1, "", "to_dense_prediction_model"]], "braindecode.models.HybridNet": [[95, 2, 1, "", "forward"]], "braindecode.models.SleepStagerBlanco2020": [[97, 2, 1, "", "forward"]], "braindecode.models.SleepStagerChambon2018": [[98, 2, 1, "", "forward"]], "braindecode.models.SleepStagerEldele2021": [[99, 2, 1, "", "forward"]], "braindecode.models.TCN": [[100, 2, 1, "", "forward"]], "braindecode.models.TIDNet": [[101, 2, 1, "", "forward"]], "braindecode.models.TimeDistributed": [[102, 2, 1, "", "forward"]], "braindecode.models.USleep": [[103, 2, 1, "", "forward"]], "braindecode.preprocessing": [[105, 1, 1, "", "Crop"], [106, 1, 1, "", "DropChannels"], [107, 1, 1, "", "Filter"], [108, 1, 1, "", "Pick"], [109, 1, 1, "", "Preprocessor"], [110, 1, 1, "", "Resample"], [111, 1, 1, "", "SetEEGReference"], [112, 3, 1, "", "create_fixed_length_windows"], [113, 3, 1, "", "create_windows_from_events"], [114, 3, 1, "", "create_windows_from_target_channels"], [115, 3, 1, "", "exponential_moving_demean"], [116, 3, 1, "", "exponential_moving_standardize"], [117, 3, 1, "", "filterbank"], [118, 3, 1, "", "preprocess"]], "braindecode.preprocessing.Preprocessor": [[109, 2, 1, "", "apply"]], "braindecode.regressor": [[119, 1, 1, "", "EEGRegressor"]], "braindecode.regressor.EEGRegressor": [[119, 4, 1, "", "_criteria"], [119, 4, 1, "", "_modules"], [119, 4, 1, "", "_optimizers"], [119, 4, 1, "", "callbacks_"], [119, 4, 1, "", "criterion_"], [119, 4, 1, "", "cuda_dependent_attributes_"], [119, 2, 1, "", "fit"], [119, 2, 1, "", "get_iterator"], [119, 4, 1, "", "initialized_"], [119, 4, 1, "", "module_"], [119, 2, 1, "", "predict_proba"], [119, 2, 1, "", "predict_trials"], [119, 4, 1, "", "prefixes_"]], "braindecode.samplers": [[120, 1, 1, "", "BalancedSequenceSampler"], [121, 1, 1, "", "RecordingSampler"], [122, 1, 1, "", "RelativePositioningSampler"], [123, 1, 1, "", "SequenceSampler"]], "braindecode.samplers.BalancedSequenceSampler": [[120, 2, 1, "", "sample_class"]], "braindecode.samplers.RecordingSampler": [[121, 4, 1, "", "info"], [121, 4, 1, "", "n_recordings"], [121, 2, 1, "", "sample_recording"], [121, 2, 1, "", "sample_window"]], "braindecode.samplers.RelativePositioningSampler": [[122, 2, 1, "", "presample"]], "braindecode.samplers.SequenceSampler": [[123, 4, 1, "", "file_ids"], [123, 4, 1, "", "info"]], "braindecode.training": [[124, 1, 1, "", "CroppedLoss"], [125, 1, 1, "", "CroppedTimeSeriesEpochScoring"], [126, 1, 1, "", "CroppedTrialEpochScoring"], [127, 1, 1, "", "PostEpochTrainScoring"], [128, 1, 1, "", "TimeSeriesLoss"], [129, 3, 1, "", "mixup_criterion"], [130, 3, 1, "", "predict_trials"], [131, 3, 1, "", "trial_preds_from_window_preds"]], "braindecode.training.CroppedLoss": [[124, 2, 1, "", "forward"]], "braindecode.training.CroppedTimeSeriesEpochScoring": [[125, 2, 1, "", "on_epoch_end"]], "braindecode.training.CroppedTrialEpochScoring": [[126, 2, 1, "", "on_batch_end"], [126, 2, 1, "", "on_epoch_end"]], "braindecode.training.PostEpochTrainScoring": [[127, 2, 1, "", "on_epoch_end"]], "braindecode.training.TimeSeriesLoss": [[128, 2, 1, "", "forward"]], "braindecode.util": [[132, 3, 1, "", "set_random_seeds"]], "braindecode.visualization": [[133, 3, 1, "", "compute_amplitude_gradients"], [134, 3, 1, "", "plot_confusion_matrix"]]}, "objtypes": {"0": "py:module", "1": "py:class", "2": "py:method", "3": "py:function", "4": "py:attribute"}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "class", "Python class"], "2": ["py", "method", "Python method"], "3": ["py", "function", "Python function"], "4": ["py", "attribute", "Python attribute"]}, "titleterms": {"api": [0, 140], "refer": [0, 4, 5, 9, 10, 11, 26, 27, 28, 29, 30, 31, 135], "classifi": [0, 67], "regressor": [0, 119], "model": [0, 2, 3, 4, 5, 8, 9, 10, 11, 22, 24, 25, 26, 27, 28, 29, 30, 31, 32, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104], "train": [0, 1, 2, 3, 4, 5, 8, 9, 10, 11, 22, 24, 25, 26, 27, 28, 29, 30, 31, 32, 124, 125, 126, 127, 128, 129, 130, 131], "dataset": [0, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 17, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30, 31, 32, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80], "preprocess": [0, 2, 3, 4, 5, 8, 9, 10, 11, 12, 16, 27, 28, 29, 30, 32, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118], "data": [0, 3, 4, 12, 15, 22, 24, 26, 27, 28, 29, 31], "util": [0, 29, 132], "sampler": [0, 5, 9, 10, 11, 120, 121, 122, 123], "augment": [0, 3, 4, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66], "visual": [0, 3, 5, 29, 133, 134], "advanc": [1, 24], "neural": [1, 24, 30, 31], "network": [1, 9, 11, 24, 30, 31], "strategi": [1, 24], "finger": [2, 8], "flexion": [2, 8], "crop": [2, 27, 105], "decod": [2, 8, 27, 28], "bcic": [2, 3, 4, 8, 27], "iv": [2, 3, 4, 8, 27], "4": [2, 8], "ecog": [2, 8], "load": [2, 3, 4, 5, 8, 9, 10, 11, 14, 15, 18, 21, 24, 26, 27, 28, 29, 30, 32], "prepar": [2, 8, 28], "split": [2, 3, 4, 5, 8, 9, 10, 11, 21, 27, 28, 29, 30, 32], "test": [2, 5, 8, 29, 31, 32, 139], "creat": [2, 3, 4, 5, 8, 9, 10, 11, 12, 22, 27, 28, 29, 30, 32], "cut": [2, 8, 12, 27, 32], "comput": [2, 6, 8, 12, 13, 23, 27, 28, 30, 32, 33], "window": [2, 3, 4, 5, 8, 9, 10, 11, 12, 22, 27, 28, 29, 30, 31, 32], "plot": [2, 4, 8, 9, 10, 11, 27, 28, 30], "result": [2, 4, 5, 8, 9, 10, 11, 27, 28, 30], "2a": [3, 4, 27], "thi": [3, 4, 5, 12, 21, 26, 27, 28, 29, 30, 32], "exampl": [3, 4, 5, 7, 12, 17, 18, 19, 20, 21, 24, 26, 27, 28, 29, 30, 32, 35, 37, 40, 41, 42, 50, 51, 53, 68, 70, 71, 73, 74, 75, 76, 78, 79, 80, 81, 84, 91, 96, 98, 99, 102, 103, 104, 109, 112, 113, 114, 116, 118, 121, 122, 123, 124, 125, 126, 128, 132, 134], "cover": [3, 4, 5, 12, 21, 26, 27, 28, 29, 30, 32], "extract": [3, 4, 5, 9, 10, 11, 28, 29, 30], "valid": [3, 4, 5, 8, 9, 10, 11, 28, 29, 30], "defin": [3, 4, 29, 31, 32], "transform": [3, 4, 32, 53], "manipul": 3, "one": 3, "session": 3, "an": [3, 4], "eegclassifi": [3, 4, 67], "desir": [3, 4], "manual": 3, "compos": [3, 40], "set": [3, 5, 28], "level": 3, "search": 4, "best": [4, 30], "list": 4, "analys": 4, "fit": 4, "self": 5, "supervis": 5, "learn": [5, 26, 30], "eeg": [5, 12, 22, 28], "rel": 5, "posit": 5, "raw": [5, 32], "record": [5, 12], "inspect": 5, "pretext": 5, "task": 5, "perform": 5, "us": [5, 9, 10, 11, 12, 35, 37, 40, 41, 42, 50, 51, 53, 68, 70, 71, 73, 74, 75, 76, 78, 79, 80, 81, 84, 91, 96, 98, 99, 102, 103, 104, 109, 112, 113, 114, 116, 118, 121, 122, 123, 124, 125, 126, 128, 132, 134], "represent": 5, "sleep": [5, 9, 10, 11], "stage": [5, 9, 10, 11], "conclus": 5, "time": [6, 13, 23, 33], "appli": [7, 24], "real": [7, 24], "world": [7, 24], "physionet": [9, 10, 11], "chambon2018": 9, "sequenc": [9, 10, 11], "eldele2021": 10, "u": 11, "process": 12, "big": 12, "resourc": 12, "tuh": [12, 22, 75], "corpu": [12, 22], "tuhmock": 12, "select": 12, "combin": 12, "step": 12, "benchmark": [14, 16], "eager": 14, "lazi": 14, "organ": [15, 24], "parallel": 16, "serial": 16, "custom": 17, "save": 18, "mne": [19, 26, 34], "moabb": 20, "By": 21, "descript": 21, "inform": 21, "row": 21, "index": 21, "observ": 21, "multipl": 22, "discret": 22, "target": 22, "templ": 22, "univers": 22, "hospit": 22, "explor": [22, 26], "dataload": 22, "basic": [24, 25, 28], "build": [24, 25], "simpl": [26, 29], "epoch": 26, "find": 26, "you": [26, 30], "want": 26, "braindecod": [26, 32, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 139], "onlin": 26, "document": 26, "examin": 26, "your": [26, 29, 32, 139], "own": 26, "scikit": [26, 30], "compat": 26, "paramet": 27, "confus": [27, 28], "matrix": [27, 28], "brain": 28, "how": [29, 32, 34, 135], "tune": [29, 30], "why": [29, 30, 32], "should": [29, 32], "i": [29, 32, 135, 139], "care": [29, 32], "about": [29, 32], "evalu": [29, 31, 32], "etc": [29, 32], "option": [29, 32], "1": [29, 32, 140], "let": 29, "": [29, 140], "first": 29, "function": [29, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66], "2": [29, 32], "val": 29, "second": 29, "3": 29, "k": 29, "fold": 29, "cross": 29, "third": 29, "hyperparamet": [29, 30], "do": [30, 135], "need": 30, "get": [30, 135], "convolut": 31, "regress": 31, "fake": 31, "gener": 31, "cnn": 31, "choos": 31, "between": 31, "gpu": 31, "cpu": 31, "processor": 31, "pytorch": 32, "structur": 32, "offlin": 32, "pure": 32, "loop": 32, "lightn": 32, "cite": [34, 135], "other": 34, "algorithm": 34, "augmenteddataload": 35, "bandstopfilt": 36, "channelsdropout": 37, "channelsshuffl": 38, "channelssymmetri": 39, "ftsurrog": 41, "frequencyshift": 42, "gaussiannois": 43, "identitytransform": 44, "mixup": [45, 62], "sensorsrot": 46, "sensorsxrot": 47, "sensorsyrot": 48, "sensorszrot": 49, "signflip": 50, "smoothtimemask": 51, "timerevers": 52, "bandstop_filt": 54, "channels_dropout": 55, "channels_permut": 56, "channels_shuffl": 57, "frequency_shift": 58, "ft_surrog": 59, "gaussian_nois": 60, "ident": 61, "sensors_rot": 63, "sign_flip": 64, "smooth_time_mask": 65, "time_revers": 66, "bcicompetitionivdataset4": 68, "bnci2014001": 69, "summari": [69, 72], "baseconcatdataset": 70, "basedataset": 71, "hgd": 72, "moabbdataset": 73, "sleepphysionet": 74, "tuhabnorm": 76, "windowsdataset": 77, "create_from_x_i": 78, "create_from_mne_epoch": 79, "create_from_mne_raw": 80, "datautil": [81, 82], "load_concat_dataset": 81, "save_concat_dataset": 82, "atcnet": 83, "deep4net": 84, "deepsleepnet": 85, "eegconform": 86, "eegitnet": 87, "eegincept": 88, "eeginceptionerp": 89, "eeginceptionmi": 90, "eegmodulemixin": 91, "eegnetv1": 92, "eegnetv4": 93, "eegresnet": 94, "hybridnet": 95, "shallowfbcspnet": 96, "sleepstagerblanco2020": 97, "sleepstagerchambon2018": 98, "sleepstagereldele2021": 99, "tcn": 100, "tidnet": 101, "timedistribut": 102, "usleep": 103, "get_output_shap": 104, "dropchannel": 106, "filter": 107, "pick": 108, "preprocessor": 109, "resampl": 110, "seteegrefer": 111, "create_fixed_length_window": 112, "create_windows_from_ev": 113, "create_windows_from_target_channel": 114, "exponential_moving_demean": 115, "exponential_moving_standard": 116, "filterbank": 117, "eegregressor": 119, "balancedsequencesampl": 120, "recordingsampl": 121, "relativepositioningsampl": 122, "sequencesampl": 123, "croppedloss": 124, "croppedtimeseriesepochscor": 125, "croppedtrialepochscor": 126, "postepochtrainscor": 127, "timeseriesloss": 128, "mixup_criterion": 129, "predict_tri": 130, "trial_preds_from_window_pr": 131, "set_random_se": 132, "compute_amplitude_gradi": 133, "plot_confusion_matrix": 134, "frequent": 135, "ask": 135, "question": 135, "faq": 135, "help": 135, "can": 135, "t": 135, "python": 135, "work": [135, 139], "still": 135, "think": 135, "found": 135, "bug": [135, 140], "what": [135, 140], "homepag": 136, "instal": [137, 138, 139], "from": [138, 139], "pypi": 138, "sourc": 139, "clone": 139, "repositori": 139, "github": 139, "new": 140, "current": 140, "0": 140, "9": 140, "dev0": 140, "enhanc": 140, "chang": 140, "8": 140, "11": 140, "2022": 140, "7": 140, "10": 140, "version": 140, "6": 140, "2021": 140, "12": 140, "06": 140, "5": 140, "07": 140, "14": 140, "author": 140}, "envversion": {"sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.todo": 2, "sphinx.ext.intersphinx": 1, "sphinx": 60}, "alltitles": {"API Reference": [[0, "api-reference"]], "Classifier": [[0, "classifier"]], "Regressor": [[0, "regressor"]], "Models": [[0, "models"]], "Training": [[0, "training"], [2, "training"], [5, "training"], [8, "training"], [9, "training"], [10, "training"], [11, "training"], [27, "training"], [30, "training"]], "Datasets": [[0, "datasets"]], "Preprocessing": [[0, "preprocessing"], [2, "preprocessing"], [3, "preprocessing"], [4, "preprocessing"], [5, "preprocessing"], [8, "preprocessing"], [9, "preprocessing"], [10, "preprocessing"], [11, "preprocessing"], [12, "preprocessing"], [28, "preprocessing"], [30, "preprocessing"]], "Data Utils": [[0, "data-utils"]], "Samplers": [[0, "samplers"]], "Augmentation": [[0, "augmentation"]], "Utils": [[0, "utils"]], "Visualization": [[0, "visualization"]], "Advanced neural network training strategies": [[1, "advanced-neural-network-training-strategies"], [24, "advanced-neural-network-training-strategies"]], "Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset": [[2, "fingers-flexion-cropped-decoding-on-bcic-iv-4-ecog-dataset"]], "Loading and preparing the dataset": [[2, "loading-and-preparing-the-dataset"], [8, "loading-and-preparing-the-dataset"]], "Loading": [[2, "loading"], [3, "loading"], [4, "loading"], [8, "loading"], [9, "loading"], [10, "loading"], [11, "loading"], [30, "loading"]], "Split dataset into train and test": [[2, "split-dataset-into-train-and-test"], [29, "split-dataset-into-train-and-test"], [32, "split-dataset-into-train-and-test"]], "Create model": [[2, "create-model"], [3, "create-model"], [4, "create-model"], [8, "create-model"], [9, "create-model"], [10, "create-model"], [11, "create-model"], [29, "create-model"], [30, "create-model"]], "Cut Compute Windows": [[2, "cut-compute-windows"], [8, "cut-compute-windows"], [12, "cut-compute-windows"], [32, "cut-compute-windows"]], "Plot Results": [[2, "plot-results"], [8, "plot-results"], [27, "plot-results"]], "Data Augmentation on BCIC IV 2a Dataset": [[3, "data-augmentation-on-bcic-iv-2a-dataset"]], "This example covers:": [[3, "this-example-covers"], [4, "this-example-covers"], [5, "this-example-covers"], [12, "this-example-covers"], [21, "this-example-covers"], [26, "this-example-covers"], [27, "this-example-covers"], [28, "this-example-covers"], [29, "this-example-covers"], [30, "this-example-covers"], [32, "this-example-covers"]], "Loading and preprocessing the dataset": [[3, "loading-and-preprocessing-the-dataset"], [4, "loading-and-preprocessing-the-dataset"], [5, "loading-and-preprocessing-the-dataset"], [9, "loading-and-preprocessing-the-dataset"], [10, "loading-and-preprocessing-the-dataset"], [11, "loading-and-preprocessing-the-dataset"], [27, "loading-and-preprocessing-the-dataset"], [30, "loading-and-preprocessing-the-dataset"]], "Extracting windows": [[3, "extracting-windows"], [4, "extracting-windows"], [5, "extracting-windows"]], "Split dataset into train and valid": [[3, "split-dataset-into-train-and-valid"], [4, "split-dataset-into-train-and-valid"], [9, "split-dataset-into-train-and-valid"], [10, "split-dataset-into-train-and-valid"], [11, "split-dataset-into-train-and-valid"], [30, "split-dataset-into-train-and-valid"]], "Defining a Transform": [[3, "defining-a-transform"]], "Manipulating one session and visualizing the transformed data": [[3, "manipulating-one-session-and-visualizing-the-transformed-data"]], "Training a model with data augmentation": [[3, "training-a-model-with-data-augmentation"], [4, "training-a-model-with-data-augmentation"]], "Create an EEGClassifier with the desired augmentation": [[3, "create-an-eegclassifier-with-the-desired-augmentation"], [4, "create-an-eegclassifier-with-the-desired-augmentation"]], "Manually composing Transforms": [[3, "manually-composing-transforms"]], "Setting the data augmentation at the Dataset level": [[3, "setting-the-data-augmentation-at-the-dataset-level"]], "Searching the best data augmentation on BCIC IV 2a Dataset": [[4, "searching-the-best-data-augmentation-on-bcic-iv-2a-dataset"]], "Data Augmentation": [[4, null]], "Defining a list of transforms": [[4, "defining-a-list-of-transforms"]], "Analysing the best fit": [[4, "analysing-the-best-fit"]], "Plot results": [[4, "plot-results"], [9, "plot-results"], [10, "plot-results"], [11, "plot-results"]], "References": [[4, "references"], [5, "references"], [9, "references"], [10, "references"], [11, "references"], [26, "references"], [27, "references"], [28, "references"], [29, "references"], [30, "references"], [31, "references"], [135, "references"]], "Self-supervised learning on EEG with relative positioning": [[5, "self-supervised-learning-on-eeg-with-relative-positioning"]], "Self-supervised learning": [[5, null]], "Loading the raw recordings": [[5, "loading-the-raw-recordings"]], "Preprocessing windows": [[5, "preprocessing-windows"]], "Splitting dataset into train, valid and test sets": [[5, "splitting-dataset-into-train-valid-and-test-sets"]], "Creating samplers": [[5, "creating-samplers"]], "Creating the model": [[5, "creating-the-model"]], "Visualizing the results": [[5, "visualizing-the-results"]], "Inspecting pretext task performance": [[5, "inspecting-pretext-task-performance"]], "Using the learned representation for sleep staging": [[5, "using-the-learned-representation-for-sleep-staging"]], "Conclusion": [[5, "conclusion"]], "Computation times": [[6, "computation-times"], [13, "computation-times"], [23, "computation-times"], [33, "computation-times"]], "Applied examples on real-world datasets": [[7, "applied-examples-on-real-world-datasets"], [24, "applied-examples-on-real-world-datasets"]], "Fingers flexion decoding on BCIC IV 4 ECoG Dataset": [[8, "fingers-flexion-decoding-on-bcic-iv-4-ecog-dataset"]], "Split dataset into train, valid, and test": [[8, "split-dataset-into-train-valid-and-test"]], "Sleep staging on the Sleep Physionet dataset using Chambon2018 network": [[9, "sleep-staging-on-the-sleep-physionet-dataset-using-chambon2018-network"]], "Extract windows": [[9, "extract-windows"], [10, "extract-windows"], [11, "extract-windows"]], "Window preprocessing": [[9, "window-preprocessing"], [10, "window-preprocessing"]], "Create sequence samplers": [[9, "create-sequence-samplers"], [10, "create-sequence-samplers"], [11, "create-sequence-samplers"]], "Sleep staging on the Sleep Physionet dataset using Eldele2021": [[10, "sleep-staging-on-the-sleep-physionet-dataset-using-eldele2021"]], "Sleep staging on the Sleep Physionet dataset using U-Sleep network": [[11, "sleep-staging-on-the-sleep-physionet-dataset-using-u-sleep-network"]], "Process a big data EEG resource (TUH EEG Corpus)": [[12, "process-a-big-data-eeg-resource-tuh-eeg-corpus"]], "Creating the dataset using TUHMock": [[12, "creating-the-dataset-using-tuhmock"]], "Selecting recordings": [[12, "selecting-recordings"]], "Combining preprocessing steps": [[12, "combining-preprocessing-steps"]], "Benchmarking eager and lazy loading": [[14, "benchmarking-eager-and-lazy-loading"]], "Loading and organizing data": [[15, "loading-and-organizing-data"], [24, "loading-and-organizing-data"]], "Benchmarking preprocessing with parallelization and serialization": [[16, "benchmarking-preprocessing-with-parallelization-and-serialization"]], "Custom Dataset Example": [[17, "custom-dataset-example"]], "Load and save dataset example": [[18, "load-and-save-dataset-example"]], "MNE Dataset Example": [[19, "mne-dataset-example"]], "MOABB Dataset Example": [[20, "moabb-dataset-example"]], "Split Dataset Example": [[21, "split-dataset-example"]], "Loading the dataset": [[21, "loading-the-dataset"], [28, "loading-the-dataset"]], "Splitting": [[21, "splitting"]], "By description information": [[21, "by-description-information"]], "By row index": [[21, "by-row-index"]], "Observation": [[21, "observation"]], "Multiple discrete targets with the TUH EEG Corpus": [[22, "multiple-discrete-targets-with-the-tuh-eeg-corpus"]], "Creating Temple University Hospital (TUH) EEG Corpus Dataset": [[22, "creating-temple-university-hospital-tuh-eeg-corpus-dataset"]], "Exploring Data": [[22, "exploring-data"]], "Creating Windows": [[22, "creating-windows"]], "Exploring Windows": [[22, "exploring-windows"]], "DataLoader for Model Training": [[22, "dataloader-for-model-training"]], "Exploring DataLoader": [[22, "exploring-dataloader"]], "Examples": [[24, "examples"]], "Basic model building and training": [[24, "basic-model-building-and-training"], [25, "basic-model-building-and-training"]], "Simple training on MNE epochs": [[26, "simple-training-on-mne-epochs"]], "Finding the model you want": [[26, "finding-the-model-you-want"]], "Exploring the braindecode online documentation": [[26, "exploring-the-braindecode-online-documentation"]], "Examining the model": [[26, "examining-the-model"]], "Loading your own data with MNE": [[26, "loading-your-own-data-with-mne"]], "Training your model (scikit-learn compatible)": [[26, "training-your-model-scikit-learn-compatible"]], "Cropped Decoding on BCIC IV 2a Dataset": [[27, "cropped-decoding-on-bcic-iv-2a-dataset"]], "Create model and compute windowing parameters": [[27, "create-model-and-compute-windowing-parameters"]], "Cut the data into windows": [[27, "cut-the-data-into-windows"]], "Split the dataset": [[27, "split-the-dataset"]], "Plot Confusion Matrix": [[27, "plot-confusion-matrix"]], "Basic Brain Decoding on EEG Data": [[28, "basic-brain-decoding-on-eeg-data"]], "Loading and preparing the data": [[28, "loading-and-preparing-the-data"]], "Extracting Compute Windows": [[28, "extracting-compute-windows"]], "Splitting the dataset into training and validation sets": [[28, "splitting-the-dataset-into-training-and-validation-sets"]], "Creating a model": [[28, "creating-a-model"]], "Model Training": [[28, "model-training"]], "Plotting Results": [[28, "plotting-results"]], "Plotting a  Confusion Matrix": [[28, "plotting-a-confusion-matrix"]], "How to train, test and tune your model?": [[29, "how-to-train-test-and-tune-your-model"]], "Why should I care about model evaluation?": [[29, "why-should-i-care-about-model-evaluation"], [32, "why-should-i-care-about-model-evaluation"]], "Loading and preprocessing of data, defining a model, etc.": [[29, "loading-and-preprocessing-of-data-defining-a-model-etc"]], "Loading data": [[29, "loading-data"]], "Preprocessing data": [[29, "preprocessing-data"]], "Extraction of the Windows": [[29, "extraction-of-the-windows"], [30, "extraction-of-the-windows"]], "How to train and evaluate your model": [[29, "how-to-train-and-evaluate-your-model"], [32, "how-to-train-and-evaluate-your-model"]], "Option 1: Simple Train-Test Split": [[29, "option-1-simple-train-test-split"]], "Let\u2019s visualize the first option with a util function.": [[29, "let-s-visualize-the-first-option-with-a-util-function"]], "Option 2: Train-Val-Test Split": [[29, "option-2-train-val-test-split"]], "Let\u2019s visualize the second option with a util function.": [[29, "let-s-visualize-the-second-option-with-a-util-function"]], "Option 3: k-Fold Cross Validation": [[29, "option-3-k-fold-cross-validation"]], "Let\u2019s visualize the third option with a util function.": [[29, "let-s-visualize-the-third-option-with-a-util-function"]], "How to tune your hyperparameters": [[29, "how-to-tune-your-hyperparameters"]], "Option 1: Train-Val-Test Split": [[29, "option-1-train-val-test-split"]], "Option 2: k-Fold Cross Validation": [[29, "option-2-k-fold-cross-validation"]], "Hyperparameter tuning with scikit-learn": [[30, "hyperparameter-tuning-with-scikit-learn"]], "Why do you need to tune the neural networks model?": [[30, null]], "Extraction of the Compute Windows": [[30, "extraction-of-the-compute-windows"]], "Plotting the results": [[30, "plotting-the-results"]], "Get the best hyperparameters": [[30, "get-the-best-hyperparameters"]], "Convolutional neural network regression model on fake data.": [[31, "convolutional-neural-network-regression-model-on-fake-data"]], "Fake regression data": [[31, "fake-regression-data"]], "Generating fake regression dataset": [[31, "generating-fake-regression-dataset"]], "Defining a CNN regression model": [[31, "defining-a-cnn-regression-model"]], "Choosing between GPU and CPU processors": [[31, "choosing-between-gpu-and-cpu-processors"]], "Data windowing": [[31, "data-windowing"]], "Model training": [[31, "model-training"]], "Model evaluation": [[31, "model-evaluation"]], "Model testing": [[31, "model-testing"]], "Training a Braindecode model in PyTorch": [[32, "training-a-braindecode-model-in-pytorch"]], "Loading, preprocessing, defining a model, etc.": [[32, "loading-preprocessing-defining-a-model-etc"]], "Loading the Dataset Structure": [[32, "loading-the-dataset-structure"]], "Preprocessing, the offline transformation of the raw dataset": [[32, "preprocessing-the-offline-transformation-of-the-raw-dataset"]], "Create Pytorch model": [[32, "create-pytorch-model"]], "Option 1: Pure PyTorch training loop": [[32, "option-1-pure-pytorch-training-loop"]], "Option 2: Train it with PyTorch Lightning": [[32, "option-2-train-it-with-pytorch-lightning"]], "How to cite Braindecode": [[34, "how-to-cite-braindecode"]], "Citing the Braindecode": [[34, "citing-the-braindecode"]], "Citing the MNE": [[34, "citing-the-mne"]], "Citing other algorithms": [[34, "citing-other-algorithms"]], "braindecode.augmentation.AugmentedDataLoader": [[35, "braindecode-augmentation-augmenteddataloader"]], "Examples using braindecode.augmentation.AugmentedDataLoader": [[35, "examples-using-braindecode-augmentation-augmenteddataloader"]], "braindecode.augmentation.BandstopFilter": [[36, "braindecode-augmentation-bandstopfilter"]], "braindecode.augmentation.ChannelsDropout": [[37, "braindecode-augmentation-channelsdropout"]], "Examples using braindecode.augmentation.ChannelsDropout": [[37, "examples-using-braindecode-augmentation-channelsdropout"]], "braindecode.augmentation.ChannelsShuffle": [[38, "braindecode-augmentation-channelsshuffle"]], "braindecode.augmentation.ChannelsSymmetry": [[39, "braindecode-augmentation-channelssymmetry"]], "braindecode.augmentation.Compose": [[40, "braindecode-augmentation-compose"]], "Examples using braindecode.augmentation.Compose": [[40, "examples-using-braindecode-augmentation-compose"]], "braindecode.augmentation.FTSurrogate": [[41, "braindecode-augmentation-ftsurrogate"]], "Examples using braindecode.augmentation.FTSurrogate": [[41, "examples-using-braindecode-augmentation-ftsurrogate"]], "braindecode.augmentation.FrequencyShift": [[42, "braindecode-augmentation-frequencyshift"]], "Examples using braindecode.augmentation.FrequencyShift": [[42, "examples-using-braindecode-augmentation-frequencyshift"]], "braindecode.augmentation.GaussianNoise": [[43, "braindecode-augmentation-gaussiannoise"]], "braindecode.augmentation.IdentityTransform": [[44, "braindecode-augmentation-identitytransform"]], "braindecode.augmentation.Mixup": [[45, "braindecode-augmentation-mixup"]], "braindecode.augmentation.SensorsRotation": [[46, "braindecode-augmentation-sensorsrotation"]], "braindecode.augmentation.SensorsXRotation": [[47, "braindecode-augmentation-sensorsxrotation"]], "braindecode.augmentation.SensorsYRotation": [[48, "braindecode-augmentation-sensorsyrotation"]], "braindecode.augmentation.SensorsZRotation": [[49, "braindecode-augmentation-sensorszrotation"]], "braindecode.augmentation.SignFlip": [[50, "braindecode-augmentation-signflip"]], "Examples using braindecode.augmentation.SignFlip": [[50, "examples-using-braindecode-augmentation-signflip"]], "braindecode.augmentation.SmoothTimeMask": [[51, "braindecode-augmentation-smoothtimemask"]], "Examples using braindecode.augmentation.SmoothTimeMask": [[51, "examples-using-braindecode-augmentation-smoothtimemask"]], "braindecode.augmentation.TimeReverse": [[52, "braindecode-augmentation-timereverse"]], "braindecode.augmentation.Transform": [[53, "braindecode-augmentation-transform"]], "Examples using braindecode.augmentation.Transform": [[53, "examples-using-braindecode-augmentation-transform"]], "braindecode.augmentation.functional.bandstop_filter": [[54, "braindecode-augmentation-functional-bandstop-filter"]], "braindecode.augmentation.functional.channels_dropout": [[55, "braindecode-augmentation-functional-channels-dropout"]], "braindecode.augmentation.functional.channels_permute": [[56, "braindecode-augmentation-functional-channels-permute"]], "braindecode.augmentation.functional.channels_shuffle": [[57, "braindecode-augmentation-functional-channels-shuffle"]], "braindecode.augmentation.functional.frequency_shift": [[58, "braindecode-augmentation-functional-frequency-shift"]], "braindecode.augmentation.functional.ft_surrogate": [[59, "braindecode-augmentation-functional-ft-surrogate"]], "braindecode.augmentation.functional.gaussian_noise": [[60, "braindecode-augmentation-functional-gaussian-noise"]], "braindecode.augmentation.functional.identity": [[61, "braindecode-augmentation-functional-identity"]], "braindecode.augmentation.functional.mixup": [[62, "braindecode-augmentation-functional-mixup"]], "braindecode.augmentation.functional.sensors_rotation": [[63, "braindecode-augmentation-functional-sensors-rotation"]], "braindecode.augmentation.functional.sign_flip": [[64, "braindecode-augmentation-functional-sign-flip"]], "braindecode.augmentation.functional.smooth_time_mask": [[65, "braindecode-augmentation-functional-smooth-time-mask"]], "braindecode.augmentation.functional.time_reverse": [[66, "braindecode-augmentation-functional-time-reverse"]], "braindecode.classifier.EEGClassifier": [[67, "braindecode-classifier-eegclassifier"]], "braindecode.datasets.BCICompetitionIVDataset4": [[68, "braindecode-datasets-bcicompetitionivdataset4"]], "Examples using braindecode.datasets.BCICompetitionIVDataset4": [[68, "examples-using-braindecode-datasets-bcicompetitionivdataset4"]], "braindecode.datasets.BNCI2014001": [[69, "braindecode-datasets-bnci2014001"]], "Dataset summary": [[69, null], [72, null]], "braindecode.datasets.BaseConcatDataset": [[70, "braindecode-datasets-baseconcatdataset"]], "Examples using braindecode.datasets.BaseConcatDataset": [[70, "examples-using-braindecode-datasets-baseconcatdataset"]], "braindecode.datasets.BaseDataset": [[71, "braindecode-datasets-basedataset"]], "Examples using braindecode.datasets.BaseDataset": [[71, "examples-using-braindecode-datasets-basedataset"]], "braindecode.datasets.HGD": [[72, "braindecode-datasets-hgd"]], "braindecode.datasets.MOABBDataset": [[73, "braindecode-datasets-moabbdataset"]], "Examples using braindecode.datasets.MOABBDataset": [[73, "examples-using-braindecode-datasets-moabbdataset"]], "braindecode.datasets.SleepPhysionet": [[74, "braindecode-datasets-sleepphysionet"]], "Examples using braindecode.datasets.SleepPhysionet": [[74, "examples-using-braindecode-datasets-sleepphysionet"]], "braindecode.datasets.TUH": [[75, "braindecode-datasets-tuh"]], "Examples using braindecode.datasets.TUH": [[75, "examples-using-braindecode-datasets-tuh"]], "braindecode.datasets.TUHAbnormal": [[76, "braindecode-datasets-tuhabnormal"]], "Examples using braindecode.datasets.TUHAbnormal": [[76, "examples-using-braindecode-datasets-tuhabnormal"]], "braindecode.datasets.WindowsDataset": [[77, "braindecode-datasets-windowsdataset"]], "braindecode.datasets.create_from_X_y": [[78, "braindecode-datasets-create-from-x-y"]], "Examples using braindecode.datasets.create_from_X_y": [[78, "examples-using-braindecode-datasets-create-from-x-y"]], "braindecode.datasets.create_from_mne_epochs": [[79, "braindecode-datasets-create-from-mne-epochs"]], "Examples using braindecode.datasets.create_from_mne_epochs": [[79, "examples-using-braindecode-datasets-create-from-mne-epochs"]], "braindecode.datasets.create_from_mne_raw": [[80, "braindecode-datasets-create-from-mne-raw"]], "Examples using braindecode.datasets.create_from_mne_raw": [[80, "examples-using-braindecode-datasets-create-from-mne-raw"]], "braindecode.datautil.load_concat_dataset": [[81, "braindecode-datautil-load-concat-dataset"]], "Examples using braindecode.datautil.load_concat_dataset": [[81, "examples-using-braindecode-datautil-load-concat-dataset"]], "braindecode.datautil.save_concat_dataset": [[82, "braindecode-datautil-save-concat-dataset"]], "braindecode.models.ATCNet": [[83, "braindecode-models-atcnet"]], "braindecode.models.Deep4Net": [[84, "braindecode-models-deep4net"]], "Examples using braindecode.models.Deep4Net": [[84, "examples-using-braindecode-models-deep4net"]], "braindecode.models.DeepSleepNet": [[85, "braindecode-models-deepsleepnet"]], "braindecode.models.EEGConformer": [[86, "braindecode-models-eegconformer"]], "braindecode.models.EEGITNet": [[87, "braindecode-models-eegitnet"]], "braindecode.models.EEGInception": [[88, "braindecode-models-eeginception"]], "braindecode.models.EEGInceptionERP": [[89, "braindecode-models-eeginceptionerp"]], "braindecode.models.EEGInceptionMI": [[90, "braindecode-models-eeginceptionmi"]], "braindecode.models.EEGModuleMixin": [[91, "braindecode-models-eegmodulemixin"]], "Examples using braindecode.models.EEGModuleMixin": [[91, "examples-using-braindecode-models-eegmodulemixin"]], "braindecode.models.EEGNetv1": [[92, "braindecode-models-eegnetv1"]], "braindecode.models.EEGNetv4": [[93, "braindecode-models-eegnetv4"]], "braindecode.models.EEGResNet": [[94, "braindecode-models-eegresnet"]], "braindecode.models.HybridNet": [[95, "braindecode-models-hybridnet"]], "braindecode.models.ShallowFBCSPNet": [[96, "braindecode-models-shallowfbcspnet"]], "Examples using braindecode.models.ShallowFBCSPNet": [[96, "examples-using-braindecode-models-shallowfbcspnet"]], "braindecode.models.SleepStagerBlanco2020": [[97, "braindecode-models-sleepstagerblanco2020"]], "braindecode.models.SleepStagerChambon2018": [[98, "braindecode-models-sleepstagerchambon2018"]], "Examples using braindecode.models.SleepStagerChambon2018": [[98, "examples-using-braindecode-models-sleepstagerchambon2018"]], "braindecode.models.SleepStagerEldele2021": [[99, "braindecode-models-sleepstagereldele2021"]], "Examples using braindecode.models.SleepStagerEldele2021": [[99, "examples-using-braindecode-models-sleepstagereldele2021"]], "braindecode.models.TCN": [[100, "braindecode-models-tcn"]], "braindecode.models.TIDNet": [[101, "braindecode-models-tidnet"]], "braindecode.models.TimeDistributed": [[102, "braindecode-models-timedistributed"]], "Examples using braindecode.models.TimeDistributed": [[102, "examples-using-braindecode-models-timedistributed"]], "braindecode.models.USleep": [[103, "braindecode-models-usleep"]], "Examples using braindecode.models.USleep": [[103, "examples-using-braindecode-models-usleep"]], "braindecode.models.get_output_shape": [[104, "braindecode-models-get-output-shape"]], "Examples using braindecode.models.get_output_shape": [[104, "examples-using-braindecode-models-get-output-shape"]], "braindecode.preprocessing.Crop": [[105, "braindecode-preprocessing-crop"]], "braindecode.preprocessing.DropChannels": [[106, "braindecode-preprocessing-dropchannels"]], "braindecode.preprocessing.Filter": [[107, "braindecode-preprocessing-filter"]], "braindecode.preprocessing.Pick": [[108, "braindecode-preprocessing-pick"]], "braindecode.preprocessing.Preprocessor": [[109, "braindecode-preprocessing-preprocessor"]], "Examples using braindecode.preprocessing.Preprocessor": [[109, "examples-using-braindecode-preprocessing-preprocessor"]], "braindecode.preprocessing.Resample": [[110, "braindecode-preprocessing-resample"]], "braindecode.preprocessing.SetEEGReference": [[111, "braindecode-preprocessing-seteegreference"]], "braindecode.preprocessing.create_fixed_length_windows": [[112, "braindecode-preprocessing-create-fixed-length-windows"]], "Examples using braindecode.preprocessing.create_fixed_length_windows": [[112, "examples-using-braindecode-preprocessing-create-fixed-length-windows"]], "braindecode.preprocessing.create_windows_from_events": [[113, "braindecode-preprocessing-create-windows-from-events"]], "Examples using braindecode.preprocessing.create_windows_from_events": [[113, "examples-using-braindecode-preprocessing-create-windows-from-events"]], "braindecode.preprocessing.create_windows_from_target_channels": [[114, "braindecode-preprocessing-create-windows-from-target-channels"]], "Examples using braindecode.preprocessing.create_windows_from_target_channels": [[114, "examples-using-braindecode-preprocessing-create-windows-from-target-channels"]], "braindecode.preprocessing.exponential_moving_demean": [[115, "braindecode-preprocessing-exponential-moving-demean"]], "braindecode.preprocessing.exponential_moving_standardize": [[116, "braindecode-preprocessing-exponential-moving-standardize"]], "Examples using braindecode.preprocessing.exponential_moving_standardize": [[116, "examples-using-braindecode-preprocessing-exponential-moving-standardize"]], "braindecode.preprocessing.filterbank": [[117, "braindecode-preprocessing-filterbank"]], "braindecode.preprocessing.preprocess": [[118, "braindecode-preprocessing-preprocess"]], "Examples using braindecode.preprocessing.preprocess": [[118, "examples-using-braindecode-preprocessing-preprocess"]], "braindecode.regressor.EEGRegressor": [[119, "braindecode-regressor-eegregressor"]], "braindecode.samplers.BalancedSequenceSampler": [[120, "braindecode-samplers-balancedsequencesampler"]], "braindecode.samplers.RecordingSampler": [[121, "braindecode-samplers-recordingsampler"]], "Examples using braindecode.samplers.RecordingSampler": [[121, "examples-using-braindecode-samplers-recordingsampler"]], "braindecode.samplers.RelativePositioningSampler": [[122, "braindecode-samplers-relativepositioningsampler"]], "Examples using braindecode.samplers.RelativePositioningSampler": [[122, "examples-using-braindecode-samplers-relativepositioningsampler"]], "braindecode.samplers.SequenceSampler": [[123, "braindecode-samplers-sequencesampler"]], "Examples using braindecode.samplers.SequenceSampler": [[123, "examples-using-braindecode-samplers-sequencesampler"]], "braindecode.training.CroppedLoss": [[124, "braindecode-training-croppedloss"]], "Examples using braindecode.training.CroppedLoss": [[124, "examples-using-braindecode-training-croppedloss"]], "braindecode.training.CroppedTimeSeriesEpochScoring": [[125, "braindecode-training-croppedtimeseriesepochscoring"]], "Examples using braindecode.training.CroppedTimeSeriesEpochScoring": [[125, "examples-using-braindecode-training-croppedtimeseriesepochscoring"]], "braindecode.training.CroppedTrialEpochScoring": [[126, "braindecode-training-croppedtrialepochscoring"]], "Examples using braindecode.training.CroppedTrialEpochScoring": [[126, "examples-using-braindecode-training-croppedtrialepochscoring"]], "braindecode.training.PostEpochTrainScoring": [[127, "braindecode-training-postepochtrainscoring"]], "braindecode.training.TimeSeriesLoss": [[128, "braindecode-training-timeseriesloss"]], "Examples using braindecode.training.TimeSeriesLoss": [[128, "examples-using-braindecode-training-timeseriesloss"]], "braindecode.training.mixup_criterion": [[129, "braindecode-training-mixup-criterion"]], "braindecode.training.predict_trials": [[130, "braindecode-training-predict-trials"]], "braindecode.training.trial_preds_from_window_preds": [[131, "braindecode-training-trial-preds-from-window-preds"]], "braindecode.util.set_random_seeds": [[132, "braindecode-util-set-random-seeds"]], "Examples using braindecode.util.set_random_seeds": [[132, "examples-using-braindecode-util-set-random-seeds"]], "braindecode.visualization.compute_amplitude_gradients": [[133, "braindecode-visualization-compute-amplitude-gradients"]], "braindecode.visualization.plot_confusion_matrix": [[134, "braindecode-visualization-plot-confusion-matrix"]], "Examples using braindecode.visualization.plot_confusion_matrix": [[134, "examples-using-braindecode-visualization-plot-confusion-matrix"]], "Frequently Asked Questions (FAQ)": [[135, "frequently-asked-questions-faq"]], "How do I cite Braindecode?": [[135, "how-do-i-cite-braindecode"]], "Help! I can\u2019t get Python and Braindecode working!": [[135, "help-i-can-t-get-python-and-braindecode-working"]], "I still can\u2019t get it to work!": [[135, "i-still-can-t-get-it-to-work"]], "I think I found a bug, what do I do?": [[135, "i-think-i-found-a-bug-what-do-i-do"]], "Braindecode Homepage": [[136, "braindecode-homepage"]], "Installation": [[137, "installation"]], "Installing from PyPI": [[138, "installing-from-pypi"]], "Installing from sources": [[139, "installing-from-sources"]], "Clone the repository from GitHub": [[139, "clone-the-repository-from-github"]], "Installing Braindecode from the source": [[139, "installing-braindecode-from-the-source"]], "Testing if your installation is working": [[139, "testing-if-your-installation-is-working"]], "What\u2019s new": [[140, "what-s-new"]], "Current 0.9 (dev0)": [[140, "current-0-9-dev0"]], "Enhancements": [[140, "enhancements"], [140, "id1"], [140, "id8"], [140, "id11"], [140, "id14"]], "Bugs": [[140, "bugs"], [140, "id6"], [140, "id9"], [140, "id12"], [140, "id15"]], "API changes": [[140, "api-changes"], [140, "id7"], [140, "id10"], [140, "id13"], [140, "id16"]], "Current 0.8 (11-2022)": [[140, "current-0-8-11-2022"]], "Current 0.7 (10-2022)": [[140, "current-0-7-10-2022"]], "Version 0.6 (2021-12-06)": [[140, "version-0-6-2021-12-06"]], "Version 0.5.1 (2021-07-14)": [[140, "version-0-5-1-2021-07-14"]], "Authors": [[140, "authors"]]}, "indexentries": {"braindecode": [[0, "module-braindecode"]], "module": [[0, "module-braindecode"]], "augmenteddataloader (class in braindecode.augmentation)": [[35, "braindecode.augmentation.AugmentedDataLoader"]], "bandstopfilter (class in braindecode.augmentation)": [[36, "braindecode.augmentation.BandstopFilter"]], "get_augmentation_params() (braindecode.augmentation.bandstopfilter method)": [[36, "braindecode.augmentation.BandstopFilter.get_augmentation_params"]], "operation() (braindecode.augmentation.bandstopfilter static method)": [[36, "braindecode.augmentation.BandstopFilter.operation"]], "channelsdropout (class in braindecode.augmentation)": [[37, "braindecode.augmentation.ChannelsDropout"]], "get_augmentation_params() (braindecode.augmentation.channelsdropout method)": [[37, "braindecode.augmentation.ChannelsDropout.get_augmentation_params"]], "operation() (braindecode.augmentation.channelsdropout static method)": [[37, "braindecode.augmentation.ChannelsDropout.operation"]], "channelsshuffle (class in braindecode.augmentation)": [[38, "braindecode.augmentation.ChannelsShuffle"]], "get_augmentation_params() (braindecode.augmentation.channelsshuffle method)": [[38, "braindecode.augmentation.ChannelsShuffle.get_augmentation_params"]], "operation() (braindecode.augmentation.channelsshuffle static method)": [[38, "braindecode.augmentation.ChannelsShuffle.operation"]], "channelssymmetry (class in braindecode.augmentation)": [[39, "braindecode.augmentation.ChannelsSymmetry"]], "get_augmentation_params() (braindecode.augmentation.channelssymmetry method)": [[39, "braindecode.augmentation.ChannelsSymmetry.get_augmentation_params"]], "operation() (braindecode.augmentation.channelssymmetry static method)": [[39, "braindecode.augmentation.ChannelsSymmetry.operation"]], "compose (class in braindecode.augmentation)": [[40, "braindecode.augmentation.Compose"]], "forward() (braindecode.augmentation.compose method)": [[40, "braindecode.augmentation.Compose.forward"]], "ftsurrogate (class in braindecode.augmentation)": [[41, "braindecode.augmentation.FTSurrogate"]], "get_augmentation_params() (braindecode.augmentation.ftsurrogate method)": [[41, "braindecode.augmentation.FTSurrogate.get_augmentation_params"]], "operation() (braindecode.augmentation.ftsurrogate static method)": [[41, "braindecode.augmentation.FTSurrogate.operation"]], "frequencyshift (class in braindecode.augmentation)": [[42, "braindecode.augmentation.FrequencyShift"]], "get_augmentation_params() (braindecode.augmentation.frequencyshift method)": [[42, "braindecode.augmentation.FrequencyShift.get_augmentation_params"]], "operation() (braindecode.augmentation.frequencyshift static method)": [[42, "braindecode.augmentation.FrequencyShift.operation"]], "gaussiannoise (class in braindecode.augmentation)": [[43, "braindecode.augmentation.GaussianNoise"]], "get_augmentation_params() (braindecode.augmentation.gaussiannoise method)": [[43, "braindecode.augmentation.GaussianNoise.get_augmentation_params"]], "operation() (braindecode.augmentation.gaussiannoise static method)": [[43, "braindecode.augmentation.GaussianNoise.operation"]], "identitytransform (class in braindecode.augmentation)": [[44, "braindecode.augmentation.IdentityTransform"]], "operation() (braindecode.augmentation.identitytransform static method)": [[44, "braindecode.augmentation.IdentityTransform.operation"]], "mixup (class in braindecode.augmentation)": [[45, "braindecode.augmentation.Mixup"]], "get_augmentation_params() (braindecode.augmentation.mixup method)": [[45, "braindecode.augmentation.Mixup.get_augmentation_params"]], "operation() (braindecode.augmentation.mixup static method)": [[45, "braindecode.augmentation.Mixup.operation"]], "sensorsrotation (class in braindecode.augmentation)": [[46, "braindecode.augmentation.SensorsRotation"]], "get_augmentation_params() (braindecode.augmentation.sensorsrotation method)": [[46, "braindecode.augmentation.SensorsRotation.get_augmentation_params"]], "operation() (braindecode.augmentation.sensorsrotation static method)": [[46, "braindecode.augmentation.SensorsRotation.operation"]], "sensorsxrotation (class in braindecode.augmentation)": [[47, "braindecode.augmentation.SensorsXRotation"]], "sensorsyrotation (class in braindecode.augmentation)": [[48, "braindecode.augmentation.SensorsYRotation"]], "sensorszrotation (class in braindecode.augmentation)": [[49, "braindecode.augmentation.SensorsZRotation"]], "signflip (class in braindecode.augmentation)": [[50, "braindecode.augmentation.SignFlip"]], "operation() (braindecode.augmentation.signflip static method)": [[50, "braindecode.augmentation.SignFlip.operation"]], "smoothtimemask (class in braindecode.augmentation)": [[51, "braindecode.augmentation.SmoothTimeMask"]], "get_augmentation_params() (braindecode.augmentation.smoothtimemask method)": [[51, "braindecode.augmentation.SmoothTimeMask.get_augmentation_params"]], "operation() (braindecode.augmentation.smoothtimemask static method)": [[51, "braindecode.augmentation.SmoothTimeMask.operation"]], "timereverse (class in braindecode.augmentation)": [[52, "braindecode.augmentation.TimeReverse"]], "operation() (braindecode.augmentation.timereverse static method)": [[52, "braindecode.augmentation.TimeReverse.operation"]], "transform (class in braindecode.augmentation)": [[53, "braindecode.augmentation.Transform"]], "forward() (braindecode.augmentation.transform method)": [[53, "braindecode.augmentation.Transform.forward"]], "get_augmentation_params() (braindecode.augmentation.transform method)": [[53, "braindecode.augmentation.Transform.get_augmentation_params"]], "bandstop_filter() (in module braindecode.augmentation.functional)": [[54, "braindecode.augmentation.functional.bandstop_filter"]], "channels_dropout() (in module braindecode.augmentation.functional)": [[55, "braindecode.augmentation.functional.channels_dropout"]], "channels_permute() (in module braindecode.augmentation.functional)": [[56, "braindecode.augmentation.functional.channels_permute"]], "channels_shuffle() (in module braindecode.augmentation.functional)": [[57, "braindecode.augmentation.functional.channels_shuffle"]], "frequency_shift() (in module braindecode.augmentation.functional)": [[58, "braindecode.augmentation.functional.frequency_shift"]], "ft_surrogate() (in module braindecode.augmentation.functional)": [[59, "braindecode.augmentation.functional.ft_surrogate"]], "gaussian_noise() (in module braindecode.augmentation.functional)": [[60, "braindecode.augmentation.functional.gaussian_noise"]], "identity() (in module braindecode.augmentation.functional)": [[61, "braindecode.augmentation.functional.identity"]], "mixup() (in module braindecode.augmentation.functional)": [[62, "braindecode.augmentation.functional.mixup"]], "sensors_rotation() (in module braindecode.augmentation.functional)": [[63, "braindecode.augmentation.functional.sensors_rotation"]], "sign_flip() (in module braindecode.augmentation.functional)": [[64, "braindecode.augmentation.functional.sign_flip"]], "smooth_time_mask() (in module braindecode.augmentation.functional)": [[65, "braindecode.augmentation.functional.smooth_time_mask"]], "time_reverse() (in module braindecode.augmentation.functional)": [[66, "braindecode.augmentation.functional.time_reverse"]], "eegclassifier (class in braindecode.classifier)": [[67, "braindecode.classifier.EEGClassifier"]], "_criteria (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier._criteria"]], "_modules (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier._modules"]], "_optimizers (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier._optimizers"]], "callbacks_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.callbacks_"]], "classes_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.classes_"]], "criterion_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.criterion_"]], "cuda_dependent_attributes_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.cuda_dependent_attributes_"]], "get_iterator() (braindecode.classifier.eegclassifier method)": [[67, "braindecode.classifier.EEGClassifier.get_iterator"]], "get_loss() (braindecode.classifier.eegclassifier method)": [[67, "braindecode.classifier.EEGClassifier.get_loss"]], "initialized_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.initialized_"]], "module_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.module_"]], "predict() (braindecode.classifier.eegclassifier method)": [[67, "braindecode.classifier.EEGClassifier.predict"]], "predict_proba() (braindecode.classifier.eegclassifier method)": [[67, "braindecode.classifier.EEGClassifier.predict_proba"]], "predict_trials() (braindecode.classifier.eegclassifier method)": [[67, "braindecode.classifier.EEGClassifier.predict_trials"]], "prefixes_ (braindecode.classifier.eegclassifier attribute)": [[67, "braindecode.classifier.EEGClassifier.prefixes_"]], "bcicompetitionivdataset4 (class in braindecode.datasets)": [[68, "braindecode.datasets.BCICompetitionIVDataset4"]], "download() (braindecode.datasets.bcicompetitionivdataset4 static method)": [[68, "braindecode.datasets.BCICompetitionIVDataset4.download"]], "bnci2014001 (class in braindecode.datasets)": [[69, "braindecode.datasets.BNCI2014001"]], "baseconcatdataset (class in braindecode.datasets)": [[70, "braindecode.datasets.BaseConcatDataset"]], "get_metadata() (braindecode.datasets.baseconcatdataset method)": [[70, "braindecode.datasets.BaseConcatDataset.get_metadata"]], "save() (braindecode.datasets.baseconcatdataset method)": [[70, "braindecode.datasets.BaseConcatDataset.save"]], "set_description() (braindecode.datasets.baseconcatdataset method)": [[70, "braindecode.datasets.BaseConcatDataset.set_description"]], "split() (braindecode.datasets.baseconcatdataset method)": [[70, "braindecode.datasets.BaseConcatDataset.split"]], "basedataset (class in braindecode.datasets)": [[71, "braindecode.datasets.BaseDataset"]], "set_description() (braindecode.datasets.basedataset method)": [[71, "braindecode.datasets.BaseDataset.set_description"]], "hgd (class in braindecode.datasets)": [[72, "braindecode.datasets.HGD"]], "moabbdataset (class in braindecode.datasets)": [[73, "braindecode.datasets.MOABBDataset"]], "sleepphysionet (class in braindecode.datasets)": [[74, "braindecode.datasets.SleepPhysionet"]], "tuh (class in braindecode.datasets)": [[75, "braindecode.datasets.TUH"]], "tuhabnormal (class in braindecode.datasets)": [[76, "braindecode.datasets.TUHAbnormal"]], "windowsdataset (class in braindecode.datasets)": [[77, "braindecode.datasets.WindowsDataset"]], "set_description() (braindecode.datasets.windowsdataset method)": [[77, "braindecode.datasets.WindowsDataset.set_description"]], "create_from_x_y() (in module braindecode.datasets)": [[78, "braindecode.datasets.create_from_X_y"]], "create_from_mne_epochs() (in module braindecode.datasets)": [[79, "braindecode.datasets.create_from_mne_epochs"]], "create_from_mne_raw() (in module braindecode.datasets)": [[80, "braindecode.datasets.create_from_mne_raw"]], "load_concat_dataset() (in module braindecode.datautil)": [[81, "braindecode.datautil.load_concat_dataset"]], "save_concat_dataset() (in module braindecode.datautil)": [[82, "braindecode.datautil.save_concat_dataset"]], "atcnet (class in braindecode.models)": [[83, "braindecode.models.ATCNet"]], "forward() (braindecode.models.atcnet method)": [[83, "braindecode.models.ATCNet.forward"]], "deep4net (class in braindecode.models)": [[84, "braindecode.models.Deep4Net"]], "deepsleepnet (class in braindecode.models)": [[85, "braindecode.models.DeepSleepNet"]], "forward() (braindecode.models.deepsleepnet method)": [[85, "braindecode.models.DeepSleepNet.forward"]], "eegconformer (class in braindecode.models)": [[86, "braindecode.models.EEGConformer"]], "forward() (braindecode.models.eegconformer method)": [[86, "braindecode.models.EEGConformer.forward"]], "get_fc_size() (braindecode.models.eegconformer method)": [[86, "braindecode.models.EEGConformer.get_fc_size"]], "eegitnet (class in braindecode.models)": [[87, "braindecode.models.EEGITNet"]], "eeginception (class in braindecode.models)": [[88, "braindecode.models.EEGInception"]], "eeginceptionerp (class in braindecode.models)": [[89, "braindecode.models.EEGInceptionERP"]], "eeginceptionmi (class in braindecode.models)": [[90, "braindecode.models.EEGInceptionMI"]], "forward() (braindecode.models.eeginceptionmi method)": [[90, "braindecode.models.EEGInceptionMI.forward"]], "eegmodulemixin (class in braindecode.models)": [[91, "braindecode.models.EEGModuleMixin"]], "get_output_shape() (braindecode.models.eegmodulemixin method)": [[91, "braindecode.models.EEGModuleMixin.get_output_shape"]], "get_torchinfo_statistics() (braindecode.models.eegmodulemixin method)": [[91, "braindecode.models.EEGModuleMixin.get_torchinfo_statistics"]], "load_state_dict() (braindecode.models.eegmodulemixin method)": [[91, "braindecode.models.EEGModuleMixin.load_state_dict"]], "to_dense_prediction_model() (braindecode.models.eegmodulemixin method)": [[91, "braindecode.models.EEGModuleMixin.to_dense_prediction_model"]], "eegnetv1 (class in braindecode.models)": [[92, "braindecode.models.EEGNetv1"]], "eegnetv4 (class in braindecode.models)": [[93, "braindecode.models.EEGNetv4"]], "eegresnet (class in braindecode.models)": [[94, "braindecode.models.EEGResNet"]], "hybridnet (class in braindecode.models)": [[95, "braindecode.models.HybridNet"]], "forward() (braindecode.models.hybridnet method)": [[95, "braindecode.models.HybridNet.forward"]], "shallowfbcspnet (class in braindecode.models)": [[96, "braindecode.models.ShallowFBCSPNet"]], "sleepstagerblanco2020 (class in braindecode.models)": [[97, "braindecode.models.SleepStagerBlanco2020"]], "forward() (braindecode.models.sleepstagerblanco2020 method)": [[97, "braindecode.models.SleepStagerBlanco2020.forward"]], "sleepstagerchambon2018 (class in braindecode.models)": [[98, "braindecode.models.SleepStagerChambon2018"]], "forward() (braindecode.models.sleepstagerchambon2018 method)": [[98, "braindecode.models.SleepStagerChambon2018.forward"]], "sleepstagereldele2021 (class in braindecode.models)": [[99, "braindecode.models.SleepStagerEldele2021"]], "forward() (braindecode.models.sleepstagereldele2021 method)": [[99, "braindecode.models.SleepStagerEldele2021.forward"]], "tcn (class in braindecode.models)": [[100, "braindecode.models.TCN"]], "forward() (braindecode.models.tcn method)": [[100, "braindecode.models.TCN.forward"]], "tidnet (class in braindecode.models)": [[101, "braindecode.models.TIDNet"]], "forward() (braindecode.models.tidnet method)": [[101, "braindecode.models.TIDNet.forward"]], "timedistributed (class in braindecode.models)": [[102, "braindecode.models.TimeDistributed"]], "forward() (braindecode.models.timedistributed method)": [[102, "braindecode.models.TimeDistributed.forward"]], "usleep (class in braindecode.models)": [[103, "braindecode.models.USleep"]], "forward() (braindecode.models.usleep method)": [[103, "braindecode.models.USleep.forward"]], "get_output_shape() (in module braindecode.models)": [[104, "braindecode.models.get_output_shape"]], "crop (class in braindecode.preprocessing)": [[105, "braindecode.preprocessing.Crop"]], "dropchannels (class in braindecode.preprocessing)": [[106, "braindecode.preprocessing.DropChannels"]], "filter (class in braindecode.preprocessing)": [[107, "braindecode.preprocessing.Filter"]], "pick (class in braindecode.preprocessing)": [[108, "braindecode.preprocessing.Pick"]], "preprocessor (class in braindecode.preprocessing)": [[109, "braindecode.preprocessing.Preprocessor"]], "apply() (braindecode.preprocessing.preprocessor method)": [[109, "braindecode.preprocessing.Preprocessor.apply"]], "resample (class in braindecode.preprocessing)": [[110, "braindecode.preprocessing.Resample"]], "seteegreference (class in braindecode.preprocessing)": [[111, "braindecode.preprocessing.SetEEGReference"]], "create_fixed_length_windows() (in module braindecode.preprocessing)": [[112, "braindecode.preprocessing.create_fixed_length_windows"]], "create_windows_from_events() (in module braindecode.preprocessing)": [[113, "braindecode.preprocessing.create_windows_from_events"]], "create_windows_from_target_channels() (in module braindecode.preprocessing)": [[114, "braindecode.preprocessing.create_windows_from_target_channels"]], "exponential_moving_demean() (in module braindecode.preprocessing)": [[115, "braindecode.preprocessing.exponential_moving_demean"]], "exponential_moving_standardize() (in module braindecode.preprocessing)": [[116, "braindecode.preprocessing.exponential_moving_standardize"]], "filterbank() (in module braindecode.preprocessing)": [[117, "braindecode.preprocessing.filterbank"]], "preprocess() (in module braindecode.preprocessing)": [[118, "braindecode.preprocessing.preprocess"]], "eegregressor (class in braindecode.regressor)": [[119, "braindecode.regressor.EEGRegressor"]], "_criteria (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor._criteria"]], "_modules (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor._modules"]], "_optimizers (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor._optimizers"]], "callbacks_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.callbacks_"]], "criterion_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.criterion_"]], "cuda_dependent_attributes_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.cuda_dependent_attributes_"]], "fit() (braindecode.regressor.eegregressor method)": [[119, "braindecode.regressor.EEGRegressor.fit"]], "get_iterator() (braindecode.regressor.eegregressor method)": [[119, "braindecode.regressor.EEGRegressor.get_iterator"]], "initialized_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.initialized_"]], "module_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.module_"]], "predict_proba() (braindecode.regressor.eegregressor method)": [[119, "braindecode.regressor.EEGRegressor.predict_proba"]], "predict_trials() (braindecode.regressor.eegregressor method)": [[119, "braindecode.regressor.EEGRegressor.predict_trials"]], "prefixes_ (braindecode.regressor.eegregressor attribute)": [[119, "braindecode.regressor.EEGRegressor.prefixes_"]], "balancedsequencesampler (class in braindecode.samplers)": [[120, "braindecode.samplers.BalancedSequenceSampler"]], "sample_class() (braindecode.samplers.balancedsequencesampler method)": [[120, "braindecode.samplers.BalancedSequenceSampler.sample_class"]], "recordingsampler (class in braindecode.samplers)": [[121, "braindecode.samplers.RecordingSampler"]], "info (braindecode.samplers.recordingsampler attribute)": [[121, "braindecode.samplers.RecordingSampler.info"]], "n_recordings (braindecode.samplers.recordingsampler attribute)": [[121, "braindecode.samplers.RecordingSampler.n_recordings"]], "sample_recording() (braindecode.samplers.recordingsampler method)": [[121, "braindecode.samplers.RecordingSampler.sample_recording"]], "sample_window() (braindecode.samplers.recordingsampler method)": [[121, "braindecode.samplers.RecordingSampler.sample_window"]], "relativepositioningsampler (class in braindecode.samplers)": [[122, "braindecode.samplers.RelativePositioningSampler"]], "presample() (braindecode.samplers.relativepositioningsampler method)": [[122, "braindecode.samplers.RelativePositioningSampler.presample"]], "sequencesampler (class in braindecode.samplers)": [[123, "braindecode.samplers.SequenceSampler"]], "file_ids (braindecode.samplers.sequencesampler attribute)": [[123, "braindecode.samplers.SequenceSampler.file_ids"]], "info (braindecode.samplers.sequencesampler attribute)": [[123, "braindecode.samplers.SequenceSampler.info"]], "croppedloss (class in braindecode.training)": [[124, "braindecode.training.CroppedLoss"]], "forward() (braindecode.training.croppedloss method)": [[124, "braindecode.training.CroppedLoss.forward"]], "croppedtimeseriesepochscoring (class in braindecode.training)": [[125, "braindecode.training.CroppedTimeSeriesEpochScoring"]], "on_epoch_end() (braindecode.training.croppedtimeseriesepochscoring method)": [[125, "braindecode.training.CroppedTimeSeriesEpochScoring.on_epoch_end"]], "croppedtrialepochscoring (class in braindecode.training)": [[126, "braindecode.training.CroppedTrialEpochScoring"]], "on_batch_end() (braindecode.training.croppedtrialepochscoring method)": [[126, "braindecode.training.CroppedTrialEpochScoring.on_batch_end"]], "on_epoch_end() (braindecode.training.croppedtrialepochscoring method)": [[126, "braindecode.training.CroppedTrialEpochScoring.on_epoch_end"]], "postepochtrainscoring (class in braindecode.training)": [[127, "braindecode.training.PostEpochTrainScoring"]], "on_epoch_end() (braindecode.training.postepochtrainscoring method)": [[127, "braindecode.training.PostEpochTrainScoring.on_epoch_end"]], "timeseriesloss (class in braindecode.training)": [[128, "braindecode.training.TimeSeriesLoss"]], "forward() (braindecode.training.timeseriesloss method)": [[128, "braindecode.training.TimeSeriesLoss.forward"]], "mixup_criterion() (in module braindecode.training)": [[129, "braindecode.training.mixup_criterion"]], "predict_trials() (in module braindecode.training)": [[130, "braindecode.training.predict_trials"]], "trial_preds_from_window_preds() (in module braindecode.training)": [[131, "braindecode.training.trial_preds_from_window_preds"]], "set_random_seeds() (in module braindecode.util)": [[132, "braindecode.util.set_random_seeds"]], "compute_amplitude_gradients() (in module braindecode.visualization)": [[133, "braindecode.visualization.compute_amplitude_gradients"]], "plot_confusion_matrix() (in module braindecode.visualization)": [[134, "braindecode.visualization.plot_confusion_matrix"]]}})
\ No newline at end of file
diff --git a/dev/whats_new.html b/dev/whats_new.html
index 6e7e35fb..1445bd3c 100644
--- a/dev/whats_new.html
+++ b/dev/whats_new.html
@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>What’s new &#8212; Braindecode 0.8 documentation</title>
+    <title>What’s new &#8212; Braindecode 0.8.1 documentation</title>
   
   
   
@@ -41,7 +41,7 @@
 <link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=365ca57ee442770a23c6" />
   <script src="_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=365ca57ee442770a23c6"></script>
 
-    <script src="_static/documentation_options.js?v=aad85e6b"></script>
+    <script src="_static/documentation_options.js?v=cc929139"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/design-tabs.js?v=36754332"></script>