| /external/tensorflow/tensorflow/compiler/xla/service/cpu/ |
| ir_emission_utils.cc | 37 const Shape& kernel_shape = convolution.operand(0)->shape(); local
39 ShapeUtil::HasZeroElements(kernel_shape)) {
44 ShapeUtil::ElementIsComplex(kernel_shape)) {
79 kernel_shape.dimensions_size() - 2 &&
81 kernel_shape.dimensions_size() - 1;
|
| ir_emitter.cc | 890 const Shape& kernel_shape = convolution->operand(1)->shape(); local
[all...] |
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| morphological_ops_test.py | 184 def _ConstructAndTestGradient(self, image_shape, kernel_shape, strides, rates,
190 kernel_shape: Filter shape, [filter_height, filter_width, channels].
196 assert image_shape[3] == kernel_shape[2]
200 kernel = np.random.random_sample(kernel_shape).astype(np.float32)
202 kernel_init = np.random.random_sample(kernel_shape).astype(np.float32)
211 kernel, shape=kernel_shape, name="filter")
223 [image_tensor, kernel_tensor], [image_shape, kernel_shape],
234 kernel_shape=[1, 1, 1],
243 kernel_shape=[1, 1, 1],
252 kernel_shape=[1, 1, 2]
[all...] |
| /external/tensorflow/tensorflow/python/profiler/internal/ |
| flops_registry.py | 319 kernel_shape = list(node.attr["ksize"].list.i)
320 kernel_area = _list_product(kernel_shape)
344 kernel_shape = list(node.attr["ksize"].list.i)
345 kernel_area = _list_product(kernel_shape)
372 kernel_shape = list(node.attr["ksize"].list.i)
373 kernel_area = _list_product(kernel_shape)
400 # kernel_shape = [kernel_y_dim, kernel_x_dim, input_depth, output_depth]
401 kernel_shape = graph_util.tensor_shape_from_node_def_name(graph,
403 kernel_shape.assert_is_fully_defined()
409 * kernel_shape.num_elements(
[all...] |
| /external/tensorflow/tensorflow/contrib/bayesflow/python/kernel_tests/ |
| layers_conv_variational_test.py | 187 kernel_shape = kernel_size + (channels, filters)
189 loc=random_ops.random_uniform(kernel_shape, seed=seed()),
190 scale=random_ops.random_uniform(kernel_shape, seed=seed()),
191 result_log_prob=random_ops.random_uniform(kernel_shape, seed=seed()),
192 result_sample=random_ops.random_uniform(kernel_shape, seed=seed()))
194 result_log_prob=random_ops.random_uniform(kernel_shape, seed=seed()),
195 result_sample=random_ops.random_uniform(kernel_shape, seed=seed()))
197 result=random_ops.random_uniform(kernel_shape, seed=seed()))
228 layer, inputs, outputs, kl_penalty, kernel_shape)
235 outputs, kl_penalty, kernel_shape) = self._testConvSetUp
[all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
| convolutional_recurrent.py | 386 kernel_shape = self.kernel_size + (input_dim, self.filters * 4)
387 self.kernel_shape = kernel_shape
391 shape=kernel_shape,
444 shape = list(self.kernel_shape)
502 shape = list(self.kernel_shape)
|
| local.py | 131 self.kernel_shape = (output_length, self.kernel_size[0] * input_dim,
134 shape=self.kernel_shape,
329 self.kernel_shape = (
333 shape=self.kernel_shape,
|
| /external/tensorflow/tensorflow/contrib/model_pruning/python/layers/ |
| core_layers.py | 131 kernel_shape = self.kernel_size + (input_dim, self.filters)
134 shape=kernel_shape,
141 shape=kernel_shape,
|
| /external/tensorflow/tensorflow/python/layers/ |
| convolutional.py | 136 kernel_shape = self.kernel_size + (input_dim, self.filters)
139 shape=kernel_shape,
[all...] |
| /external/tensorflow/tensorflow/contrib/bayesflow/python/ops/ |
| layers_conv_variational.py | 194 kernel_shape = self.kernel_size + (input_dim, self.filters)
199 dtype, kernel_shape, "kernel_posterior",
206 dtype, kernel_shape, "kernel_prior",
229 filter_shape=tensor_shape.TensorShape(kernel_shape),
[all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/ |
| backend.py | [all...] |
| /external/tensorflow/tensorflow/compiler/tests/ |
| randomized_tests.cc | [all...] |
| /external/tensorflow/tensorflow/contrib/rnn/python/kernel_tests/ |
| rnn_cell_test.py | [all...] |
| /external/tensorflow/tensorflow/contrib/rnn/python/ops/ |
| rnn_cell.py | [all...] |
