Added test functions in convolutional_test.py and local_test.py
diff --git a/tensorflow/python/keras/layers/convolutional_test.py b/tensorflow/python/keras/layers/convolutional_test.py
index 8c5ce10..f7d4da7 100644
--- a/tensorflow/python/keras/layers/convolutional_test.py
+++ b/tensorflow/python/keras/layers/convolutional_test.py
@@ -166,6 +166,11 @@
fn(inpt2)
self.assertEqual(outp1_shape, layer(inpt1).shape)
+ def test_conv1d_valid_output_shapes(self):
+ kwargs = {'filters': 2 , 'kernel_size': 10}
+ with self.assertRaises(ValueError):
+ keras.layers.Conv1D(**kwargs)
+
@keras_parameterized.run_all_keras_modes
class Conv2DTest(keras_parameterized.TestCase):
@@ -298,6 +303,11 @@
with self.assertRaises(ValueError):
keras.layers.Conv2D(**kwargs)
+ def test_conv2d_valid_output_shapes(self):
+ kwargs = {'filters': 2 , 'kernel_size': 10}
+ with self.assertRaises(ValueError):
+ keras.layers.Conv2D(**kwargs)
+
@keras_parameterized.run_all_keras_modes
class Conv3DTest(keras_parameterized.TestCase):
@@ -433,6 +443,11 @@
input_shape=(None, 3, None, None, None),
input_data=input_data)
+ def test_conv3d_valid_output_shapes(self):
+ kwargs = {'filters': 2 , 'kernel_size': 10}
+ with self.assertRaises(ValueError):
+ keras.layers.Conv3D(**kwargs)
+
@keras_parameterized.run_all_keras_modes(always_skip_v1=True)
class GroupedConvTest(keras_parameterized.TestCase):
@@ -518,6 +533,11 @@
test.is_gpu_available(cuda_only=True)):
self._run_test(kwargs, expected_output_shape)
+ def test_conv1dtranspose_valid_output_shapes(self):
+ kwargs = {'filters': 2 , 'kernel_size': 10}
+ with self.assertRaises(ValueError):
+ keras.layers.Conv1DTranspose(**kwargs)
+
@keras_parameterized.run_all_keras_modes
class Conv3DTransposeTest(keras_parameterized.TestCase):
@@ -551,6 +571,11 @@
if 'data_format' not in kwargs or test.is_gpu_available(cuda_only=True):
self._run_test(kwargs, expected_output_shape)
+ def test_conv3dtanspose_valid_output_shapes(self):
+ kwargs = {'filters': 2 , 'kernel_size': 10}
+ with self.assertRaises(ValueError):
+ keras.layers.Conv3DTranspose(**kwargs)
+
@keras_parameterized.run_all_keras_modes
class ConvSequentialTest(keras_parameterized.TestCase):
diff --git a/tensorflow/python/keras/layers/local_test.py b/tensorflow/python/keras/layers/local_test.py
index b3f78f8..14fcf0a 100644
--- a/tensorflow/python/keras/layers/local_test.py
+++ b/tensorflow/python/keras/layers/local_test.py
@@ -158,6 +158,11 @@
self.assertEqual(layer.kernel.constraint, k_constraint)
self.assertEqual(layer.bias.constraint, b_constraint)
+ def test_locallyconnected1d_valid_output_shapes(self):
+ kwargs = {'filters': 2 , 'kernel_size': 10}
+ with self.assertRaises(ValueError):
+ keras.layers.LocallyConnected1D(**kwargs)
+
@combinations.generate(combinations.combine(mode=['graph', 'eager']))
class LocallyConnected2DLayersTest(test.TestCase, parameterized.TestCase):
@@ -265,6 +270,12 @@
self.assertEqual(layer.kernel.constraint, k_constraint)
self.assertEqual(layer.bias.constraint, b_constraint)
+ def test_locallyconnected2d_valid_output_shapes(self):
+ kwargs = {'filters': 2 , 'kernel_size': 10}
+ with self.assertRaises(ValueError):
+ keras.layers.LocallyConnected2D(**kwargs)
+
+
@combinations.generate(combinations.combine(mode=['graph', 'eager']))
class LocallyConnectedImplementationModeTest(test.TestCase,
