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PEP8 fixes

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This commit is contained in:
Michael Oliver
2017-02-22 16:47:38 -08:00
parent 18600c2c67
commit 36c0c9e600
2 changed files with 24 additions and 25 deletions
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keras_contrib/layers/convolutional.py
+1 -1
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@@ -458,4 +458,4 @@ class CosineConvolution2D(Layer):
CosineConv2D = CosineConvolution2D
get_custom_objects().update({"CosineConvolution2D": CosineConvolution2D})
get_custom_objects().update({"CosineConv2D": CosineConv2D})
get_custom_objects().update({"CosineConv2D": CosineConv2D})
tests/keras_contrib/layers/test_convolutional.py
+23 -24
View File
@@ -75,6 +75,7 @@ def test_deconvolution_3d():
'subsample': subsample},
input_shape=(nb_samples, stack_size, kernel_dim1, kernel_dim2, kernel_dim3))
@keras_test
def test_cosineconvolution_2d():
nb_samples = 2
@@ -85,30 +86,30 @@ def test_cosineconvolution_2d():
for border_mode in _convolution_border_modes:
for subsample in [(1, 1), (2, 2)]:
for bias_mode in [True, False]:
if border_mode == 'same' and subsample != (1, 1):
continue
for bias_mode in [True, False]:
if border_mode == 'same' and subsample != (1, 1):
continue
layer_test(convolutional.CosineConvolution2D,
kwargs={'nb_filter': nb_filter,
'nb_row': 3,
'nb_col': 3,
'border_mode': border_mode,
'subsample': subsample,
'bias': bias_mode},
input_shape=(nb_samples, nb_row, nb_col, stack_size))
layer_test(convolutional.CosineConvolution2D,
kwargs={'nb_filter': nb_filter,
'nb_row': 3,
'nb_col': 3,
'border_mode': border_mode,
'subsample': subsample,
'bias': bias_mode},
input_shape=(nb_samples, nb_row, nb_col, stack_size))
layer_test(convolutional.CosineConvolution2D,
kwargs={'nb_filter': nb_filter,
'nb_row': 3,
'nb_col': 3,
'border_mode': border_mode,
'W_regularizer': 'l2',
'b_regularizer': 'l2',
'activity_regularizer': 'activity_l2',
'subsample': subsample,
'bias': bias_mode},
input_shape=(nb_samples, nb_row, nb_col, stack_size))
layer_test(convolutional.CosineConvolution2D,
kwargs={'nb_filter': nb_filter,
'nb_row': 3,
'nb_col': 3,
'border_mode': border_mode,
'W_regularizer': 'l2',
'b_regularizer': 'l2',
'activity_regularizer': 'activity_l2',
'subsample': subsample,
'bias': bias_mode},
input_shape=(nb_samples, nb_row, nb_col, stack_size))
dim_ordering = K.image_dim_ordering()
assert dim_ordering in {'tf', 'th'}, 'dim_ordering must be in {tf, th}'
@@ -142,7 +143,5 @@ def test_cosineconvolution_2d():
assert_allclose(out, -np.ones((1, 1, 1, 1), dtype=K.floatx()), atol=1e-5)
if __name__ == '__main__':
pytest.main([__file__])