Migrate from TravisCI to Github Actions (#162)

* First workflow conifg

* Exclude impossible combinations

* Add opencv

* Fix gradcam graph

* Fix linter

* black pass

* Remove Travis and tox

.github/workflows/ci.yml

@@ -0,0 +1,66 @@
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
+
+name: Python package
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    branches: [ master ]
+
+jobs:
+  lint:
+
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python 3.7
+        uses: actions/setup-python@v1
+        with:
+          python-version: 3.7
+      - name: Update pip
+        run: python -m pip install --upgrade pip
+      - name: Cache dependencies
+        id: cache
+        uses: actions/cache@v1
+        with:
+          path: ~/.cache/pip
+          key: ${{ runner.os }}-3.7-${{ hashFiles('setup.py') }}-2.2.0
+      - name: Install dependencies
+        run: pip install -e ".[tests]" && pip install tensorflow==2.2.0
+      - name: Lint with pylint and black
+        run: make lint
+      - name: Check black
+        run: black tf_explain tests --check
+
+  tests:
+
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [3.6, 3.7, 3.8]
+        tensorflow-version: [2.1.0, 2.2.0, 2.3.0, 2.4.0]
+        exclude:
+          - tensorflow-version: 2.1.0
+            python-version: 3.8
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v1
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Update pip
+        run: python -m pip install --upgrade pip
+      - name: Cache dependencies
+        id: cache
+        uses: actions/cache@v1
+        with:
+          path: ~/.cache/pip
+          key: ${{ runner.os }}-${{ matrix.python-version }}-${{ hashFiles('setup.py') }}-${{ matrix.tensorflow-version }}
+      - name: Install dependencies
+        run: pip install -e ".[tests]" && pip install opencv-python && pip install tensorflow==${{ matrix.tensorflow-version }}
+      - name: Test with pytest
+        run: make test

.pylintrc

@@ -66,7 +66,8 @@ disable=bad-continuation,
         import-error,
         too-few-public-methods,
         too-many-arguments,
-        unused-argument
+        unused-argument,
+        not-context-manager
 
 # Enable the message, report, category or checker with the given id(s). You can
 # either give multiple identifier separated by comma (,) or put this option

tests/core/test_occlusion_sensitivity.py

@@ -9,13 +9,16 @@ def test_should_get_sensitivity_map(convolutional_model, random_data, mocker):
     x, y = random_data
     patch_size = 4
 
-    predict_return_value = np.ones(
-        (
-            math.ceil(x[0].shape[0] / patch_size)
-            * math.ceil(x[0].shape[1] / patch_size),
-            1,
+    predict_return_value = (
+        np.ones(
+            (
+                math.ceil(x[0].shape[0] / patch_size)
+                * math.ceil(x[0].shape[1] / patch_size),
+                1,
+            )
         )
-    ) * np.expand_dims([0.6, 0.4], axis=0)
+        * np.expand_dims([0.6, 0.4], axis=0)
+    )
     convolutional_model.predict = mocker.MagicMock(return_value=predict_return_value)
     mocker.patch(
         "tf_explain.core.occlusion_sensitivity.apply_grey_patch",

tf_explain/callbacks/activations_visualization.py

@@ -30,7 +30,7 @@ def __init__(
             layers_name (List[str]): List of layer names to inspect
             output_dir (str): Output directory path
         """
-        super(ActivationsVisualizationCallback, self).__init__()
+        super().__init__()
         self.validation_data = validation_data
         self.layers_name = layers_name
         self.output_dir = Path(output_dir) / datetime.now().strftime("%Y%m%d-%H%M%S.%f")

tf_explain/callbacks/grad_cam.py

@@ -38,7 +38,7 @@ def __init__(
             layer_name (str): Targeted layer for GradCAM
             output_dir (str): Output directory path
         """
-        super(GradCAMCallback, self).__init__()
+        super().__init__()
         self.validation_data = validation_data
         self.layer_name = layer_name
         self.class_index = class_index

tf_explain/callbacks/integrated_gradients.py

@@ -36,7 +36,7 @@ def __init__(
             n_steps (int): Number of steps in the path
             output_dir (str): Output directory path
         """
-        super(IntegratedGradientsCallback, self).__init__()
+        super().__init__()
         self.validation_data = validation_data
         self.class_index = class_index
         self.n_steps = n_steps

tf_explain/callbacks/occlusion_sensitivity.py

@@ -34,7 +34,7 @@ def __init__(
             patch_size (int): Size of patch to apply on the image
             output_dir (str): Output directory path
         """
-        super(OcclusionSensitivityCallback, self).__init__()
+        super().__init__()
         self.validation_data = validation_data
         self.class_index = class_index
         self.patch_size = patch_size

tf_explain/callbacks/smoothgrad.py

@@ -38,7 +38,7 @@ def __init__(
             noise (float): Standard deviation for noise normal distribution
             output_dir (str): Output directory path
         """
-        super(SmoothGradCallback, self).__init__()
+        super().__init__()
         self.validation_data = validation_data
         self.class_index = class_index
         self.num_samples = num_samples

tf_explain/callbacks/vanilla_gradients.py

@@ -33,7 +33,7 @@ def __init__(self, validation_data, class_index, output_dir=None):
             class_index (int): Index of targeted class
             num_samples (int): Number of noisy samples to generate for each input image
         """
-        super(VanillaGradientsCallback, self).__init__()
+        super().__init__()
         self.validation_data = validation_data
         self.class_index = class_index
         if not output_dir:

tf_explain/core/grad_cam.py

@@ -91,7 +91,6 @@ def infer_grad_cam_target_layer(model):
         )
 
     @staticmethod
-    @tf.function
     def get_gradients_and_filters(
         model, images, layer_name, class_index, use_guided_grads
     ):

tf_explain/core/smoothgrad.py

@@ -85,7 +85,12 @@ def get_averaged_gradients(noisy_images, model, class_index, num_samples):
         """
         num_classes = model.output.shape[1]
 
-        expected_output = tf.one_hot([class_index] * noisy_images.shape[0], num_classes)
+        expected_output = tf.one_hot(
+            [class_index] * noisy_images.shape[0],
+            num_classes,
+            on_value=None,
+            off_value=None,
+        )
 
         with tf.GradientTape() as tape:
             inputs = tf.cast(noisy_images, tf.float32)

tf_explain/core/vanilla_gradients.py

@@ -58,7 +58,12 @@ def compute_gradients(images, model, class_index):
         """
         num_classes = model.output.shape[1]
 
-        expected_output = tf.one_hot([class_index] * images.shape[0], num_classes)
+        expected_output = tf.one_hot(
+            [class_index] * images.shape[0],
+            num_classes,
+            on_value=None,
+            off_value=None,
+        )
 
         with tf.GradientTape() as tape:
             inputs = tf.cast(images, tf.float32)