experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Internal change

Browse Source 
PiperOrigin-RevId: 350819073
Change-Id: I0845756b8d539709152f81d1b485f37d27e0a4f5
This commit is contained in:
A. Unique TensorFlower 2021-01-08 12:52:15 -08:00 committed by TensorFlower Gardener
parent 0d720fa421
commit 9fa88362d4
2 changed files with 9 additions and 40 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

7
tensorflow/python/keras/layers/convolutional.py
View File

@ -242,8 +242,6 @@ class Conv(Layer):
self.built = True
def call(self, inputs):
input_shape = inputs.shape
if self._is_causal: # Apply causal padding to inputs for Conv1D.
inputs = array_ops.pad(inputs, self._compute_causal_padding(inputs))
@ -268,11 +266,6 @@ class Conv(Layer):
outputs = nn.bias_add(
outputs, self.bias, data_format=self._tf_data_format)
if not context.executing_eagerly():
# Infer the static output shape:
out_shape = self.compute_output_shape(input_shape)
outputs.set_shape(out_shape)
if self.activation is not None:
return self.activation(outputs)
return outputs

42
tensorflow/python/keras/layers/convolutional_test.py
View File

@ -174,36 +174,24 @@ class Conv1DTest(keras_parameterized.TestCase):
@keras_parameterized.run_all_keras_modes
class Conv2DTest(keras_parameterized.TestCase):
def _run_test(self, kwargs, expected_output_shape, spatial_shape=(7, 6)):
def _run_test(self, kwargs, expected_output_shape):
num_samples = 2
stack_size = 3
num_row, num_col = spatial_shape
input_data = None
# Generate valid input data.
if None in spatial_shape:
input_data_shape = (num_samples, num_row or 7, num_col or 6, stack_size)
input_data = 10 * np.random.random(input_data_shape).astype(np.float32)
num_row = 7
num_col = 6
with self.cached_session(use_gpu=True):
testing_utils.layer_test(
keras.layers.Conv2D,
kwargs=kwargs,
input_shape=(num_samples, num_row, num_col, stack_size),
input_data=input_data,
expected_output_shape=expected_output_shape)
def _run_test_extra_batch_dim(self,
kwargs,
expected_output_shape,
spatial_shape=(7, 6)):
def _run_test_extra_batch_dim(self, kwargs, expected_output_shape):
batch_shape = (2, 11)
stack_size = 3
num_row, num_col = spatial_shape
input_data = None
# Generate valid input data.
if None in spatial_shape:
input_data_shape = batch_shape + (num_row or 7, num_col or 6, stack_size)
input_data = 10 * np.random.random(input_data_shape).astype(np.float32)
num_row = 7
num_col = 6
with self.cached_session(use_gpu=True):
if expected_output_shape is not None:
@ -212,7 +200,6 @@ class Conv2DTest(keras_parameterized.TestCase):
keras.layers.Conv2D,
kwargs=kwargs,
input_shape=batch_shape + (num_row, num_col, stack_size),
input_data=input_data,
expected_output_shape=expected_output_shape)
@parameterized.named_parameters(
@ -243,24 +230,13 @@ class Conv2DTest(keras_parameterized.TestCase):
'groups': 3,
'filters': 6
}, (None, 5, 4, 6), True),
('dilation_2_unknown_width', {
'dilation_rate': (2, 2)
}, (None, None, 2, 2), False, (None, 6)),
('dilation_2_unknown_height', {
'dilation_rate': (2, 2)
}, (None, 3, None, 2), False, (7, None)),
)
def test_conv2d(self,
kwargs,
expected_output_shape=None,
requires_gpu=False,
spatial_shape=(7, 6)):
def test_conv2d(self, kwargs, expected_output_shape=None, requires_gpu=False):
kwargs['filters'] = kwargs.get('filters', 2)
kwargs['kernel_size'] = (3, 3)
if not requires_gpu or test.is_gpu_available(cuda_only=True):
self._run_test(kwargs, expected_output_shape, spatial_shape)
self._run_test_extra_batch_dim(kwargs, expected_output_shape,
spatial_shape)
self._run_test(kwargs, expected_output_shape)
self._run_test_extra_batch_dim(kwargs, expected_output_shape)
def test_conv2d_regularizers(self):
kwargs = {