Backports for v0.10.8 (#2400)

* Fix numerical bug in `BinnedUniforms` (#2344) prob.cumsum() - prob is a numerically unsafe way to shift prob.cumsum() to the right. The numerical error will create small gaps or overlaps in the bins defined by lower and upper bounds. If a quantile falls in one of these overlap or gap the one hot bin indicator will have 0 or 2 hot bins and generate a shape mismatch error. The fix consists of doing a shift by copy. * Fix dominick dataset bug. (#2364) * Proposed fix to zero seed bug. (#2379) Co-authored-by: Sigrid Passano Hellan <[email protected]> Co-authored-by: Marc van Oudheusden <[email protected]> Co-authored-by: Bhaskar Dhariyal <[email protected]> Co-authored-by: Sigrid Passano Hellan <[email protected]> Co-authored-by: Sigrid Passano Hellan <[email protected]>
awslabs · Oct 28, 2022 · be1a39e · be1a39e
1 parent 0ef14a0
commit be1a39e
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Showing 3 changed files with 5 additions and 4 deletions.
diff --git a/src/gluonts/dataset/repository/_tsf_datasets.py b/src/gluonts/dataset/repository/_tsf_datasets.py
@@ -238,7 +238,7 @@ def default_prediction_length_from_frequency(freq: str) -> int:
         "T": 60,
         "H": 48,
         "D": 30,
-        "W": 8,
+        "W-SUN": 8,
         "M": 12,
         "Y": 4,
     }

diff --git a/src/gluonts/model/seq2seq/_mq_dnn_estimator.py b/src/gluonts/model/seq2seq/_mq_dnn_estimator.py
@@ -86,7 +86,7 @@ class MQCNNEstimator(ForkingSeq2SeqEstimator):
         It makes sense to disable this, if you don't have ``feat_dynamic_real``
         for the prediction range.
     seed
-        Will set the specified int seed for numpy anc MXNet if specified.
+        Will set the specified int seed for numpy and MXNet if specified.
         (default: None)
     decoder_mlp_dim_seq
         The dimensionalities of the Multi Layer Perceptron layers of the
@@ -216,7 +216,7 @@ def __init__(
             f"{len(self.dilation_seq)} vs. {len(self.kernel_size_seq)}"
         )
 
-        if seed:
+        if seed is not None:
             np.random.seed(seed)
             mx.random.seed(seed, trainer.ctx)
 

diff --git a/src/gluonts/torch/distributions/binned_uniforms.py b/src/gluonts/torch/distributions/binned_uniforms.py
@@ -268,7 +268,8 @@ def _icdf_binned(self, quantiles):
         # including the bin (upper)
         incomplete_cdf_upper = bins_prob.cumsum(dim=-1)
         # incomplete_cdf_upper.shape: (*batch_shape, numb_bins)
-        incomplete_cdf_lower = bins_prob.cumsum(dim=-1) - bins_prob
+        incomplete_cdf_lower = torch.zeros_like(incomplete_cdf_upper)
+        incomplete_cdf_lower[..., 1:] = incomplete_cdf_upper[..., :-1]
         # incomplete_cdf_lower.shape: (*batch_shape, numb_bins)
 
         one_hot_bin_indicator = (incomplete_cdf_lower <= quantiles) * (