Merge pull request #13 from deel-ai/fix-ci

Fix Github Action

.github/workflows/python-linters.yml

@@ -19,6 +19,6 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        pip install tox tox-gh-actions
+        pip install tox
     - name: Test with tox
       run: tox -e py36-lint

deel/lip/initializers.py

@@ -12,9 +12,7 @@
 @_deel_export
 class SpectralInitializer(Initializer):
     def __init__(
-        self,
-        niter_spectral=3,
-        base_initializer=Orthogonal(gain=1., seed=None),
+        self, niter_spectral=3, base_initializer=Orthogonal(gain=1.0, seed=None),
     ) -> None:
         """
         Initialize a kernel to be 1-lipschitz using spectral normalization (iterative
@@ -48,7 +46,7 @@ def __init__(
         self,
         niter_spectral=3,
         niter_bjorck=15,
-        base_initializer=Orthogonal(gain=1., seed=None),
+        base_initializer=Orthogonal(gain=1.0, seed=None),
     ) -> None:
         """
         Initialize a kernel to be 1-lipschitz almost everywhere using bjorck

deel/lip/layers.py

@@ -246,14 +246,14 @@ def build(self, input_shape):
             initializer=RandomNormal(0, 1),
             name="sn",
             trainable=False,
-            dtype=self.dtype
+            dtype=self.dtype,
         )
 
         self.sig = self.add_weight(
             shape=tuple([1, 1]),  # maximum spectral  value
             name="sigma",
             trainable=False,
-            dtype=self.dtype
+            dtype=self.dtype,
         )
         self.sig.assign([[1.0]])
         self.built = True
@@ -462,14 +462,14 @@ def build(self, input_shape):
             initializer=RandomNormal(0, 1),
             name="sn",
             trainable=False,
-            dtype=self.dtype
+            dtype=self.dtype,
         )
 
         self.sig = self.add_weight(
             shape=tuple([1, 1]),  # maximum spectral  value
             name="sigma",
             trainable=False,
-            dtype=self.dtype
+            dtype=self.dtype,
         )
         self.sig.assign([[1.0]])
         self.built = True

setup.cfg

@@ -15,6 +15,7 @@ commands =
     python -m unittest
 
 [testenv:py36-lint]
+skip_install = true
 deps =
     black
     flake8

tests/test_initializers.py

@@ -9,9 +9,7 @@
 from tensorflow.keras import backend as K, metrics
 from tensorflow.keras.layers import Dense
 from tensorflow.keras.optimizers import Adam
-from tests.test_layers import linear_generator, build_kernel
 from deel.lip.initializers import SpectralInitializer, BjorckInitializer
-from deel.lip.utils import evaluate_lip_const
 
 FIT = "fit_generator" if tf.__version__.startswith("2.0") else "fit"
 EVALUATE = "evaluate_generator" if tf.__version__.startswith("2.0") else "evaluate"
@@ -45,9 +43,7 @@ def _test_model(self, model, input_shape):
         )
         model.build((batch_size,) + input_shape)
         sigmas = tf.linalg.svd(
-            model.layers[0].kernel,
-            full_matrices=False,
-            compute_uv=False,
+            model.layers[0].kernel, full_matrices=False, compute_uv=False,
         ).numpy()
         np.testing.assert_allclose(sigmas, np.ones_like(sigmas), 1e-6, 0)