orthoconv: applied black on project files

deel-ai · Apr 5, 2022 · 241cc2a · 241cc2a
1 parent 12d088a
commit 241cc2a
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Showing 4 changed files with 8 additions and 8 deletions.
diff --git a/deel/lip/compute_layer_sv.py b/deel/lip/compute_layer_sv.py
@@ -49,7 +49,7 @@ def _compute_sv_conv2d(w, Ks, N, padding="circular"):
 
     # Minimum Singular Value
 
-    bigConstant = 1.1 * sigma_max**2
+    bigConstant = 1.1 * sigma_max ** 2
     u = tf.random.uniform((batch_size,) + input_shape, minval=-1.0, maxval=1.0)
 
     u, v = _power_iteration_conv(

diff --git a/deel/lip/layers.py b/deel/lip/layers.py
@@ -890,7 +890,7 @@ def init_spectral_norm(self):
             if stride > 1:
                 N = int(0.5 + N / stride)
 
-        if C * stride**2 > M:
+        if C * stride ** 2 > M:
             self.spectral_input_shape = (N, N, M)
             self.ro_case = True
         else:

diff --git a/deel/lip/regularizers.py b/deel/lip/regularizers.py
@@ -47,9 +47,9 @@ def _get_kernel_shape(self):
     def _compute_delta(self):
         (R, C, M) = self._get_kernel_shape()
         if not self.flag_deconv:
-            delta = M - (self.stride**self.dim) * C
+            delta = M - (self.stride ** self.dim) * C
         else:
-            delta = C - (self.stride**self.dim) * M
+            delta = C - (self.stride ** self.dim) * M
         delta = max(0, delta)
         if delta > 0:
             print(
@@ -69,8 +69,8 @@ def _compute_delta(self):
     def _check_if_orthconv_exists(self):
         (R, C, M) = self._get_kernel_shape()
         # RO case
-        if C * self.stride**self.dim >= M:
-            if M > C * (R**self.dim):
+        if C * self.stride ** self.dim >= M:
+            if M > C * (R ** self.dim):
                 raise RuntimeError(
                     "Impossible RO configuration for orthogonal convolution"
                 )
@@ -80,7 +80,7 @@ def _check_if_orthconv_exists(self):
                     "Impossible CO configuration for orthogonal convolution"
                 )
 
-        if C * (self.stride**self.dim) == M:
+        if C * (self.stride ** self.dim) == M:
             warnings.warn(
                 "LorthRegularizer: Warning configuration C*S^2=M is hard to optimize"
             )

diff --git a/tests/test_normalizers.py b/tests/test_normalizers.py
@@ -90,7 +90,7 @@ def set_spectral_input_shape(self, kernel):
             if stride > 1:
                 N = int(0.5 + N / stride)
 
-        if C * stride**2 > M:
+        if C * stride ** 2 > M:
             self.spectral_input_shape = (N, N, M)
             self.RO_case = True
         else: