Added test functions in convolutional_test.py and local_test.py

Author: AdityaKane2001

tensorflow/python/keras/layers/convolutional_test.py

@@ -166,6 +166,11 @@ def fn(inpt):
       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 @@ def test_conv2d_zero_kernel_size(self):
     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 @@ def test_conv3d_dynamic_shape(self):
             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 @@ def test_conv1d_transpose(self, kwargs, expected_output_shape=None):
         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 @@ def test_conv3d_transpose(self, kwargs, expected_output_shape=None):
     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):

tensorflow/python/keras/layers/local_test.py

@@ -158,6 +158,11 @@ def test_locallyconnected_1d_regularization(self, data_format, padding,
         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 @@ def test_locallyconnected_2d_regularization(self, data_format, padding,
         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,