| /external/tensorflow/tensorflow/contrib/memory_stats/python/kernel_tests/ |
| memory_stats_ops_test.py | 59 matrix_shape = tensor_shape.TensorShape([matrix_size, matrix_size])
61 matrix_size_in_bytes = matrix_shape.num_elements() * dtype.size
62 a = random_ops.random_uniform(matrix_shape, dtype=dtype)
63 b = random_ops.random_uniform(matrix_shape, dtype=dtype)
75 a = random_ops.random_uniform(matrix_shape, dtype=dtype)
79 b = random_ops.random_uniform(matrix_shape, dtype=dtype)
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| matrix_solve_op_test.py | 156 def _GenerateTestData(self, matrix_shape, num_rhs):
157 batch_shape = matrix_shape[:-2]
158 matrix_shape = matrix_shape[-2:]
159 assert matrix_shape[0] == matrix_shape[1]
160 n = matrix_shape[0]
161 matrix = (np.ones(matrix_shape).astype(np.float32) /
173 for matrix_shape in self.matrix_shapes:
174 for num_rhs in 1, 2, matrix_shape[-1]
[all...] |
| matrix_solve_ls_op_test.py | 45 def _GenerateTestData(matrix_shape, num_rhs):
46 batch_shape = matrix_shape[:-2]
47 matrix_shape = matrix_shape[-2:]
48 m = matrix_shape[-2]
52 size=np.prod(matrix_shape)).reshape(matrix_shape).astype(np.float32)
229 matrix_shape = (127, 127)
232 size=np.prod(matrix_shape)).reshape(matrix_shape).astype(np.float32
[all...] |
| tridiagonal_solve_op_test.py | 381 def test_with_matrix_shapes(matrix_shape):
387 diags_shape=matrix_shape,
394 test_with_matrix_shapes(matrix_shape=[4, 4])
395 test_with_matrix_shapes(matrix_shape=[None, 4])
396 test_with_matrix_shapes(matrix_shape=[4, None])
398 test_with_matrix_shapes(matrix_shape=[None, None])
|
| /external/tensorflow/tensorflow/python/ops/ |
| linalg_ops.py | 68 matrix_shape = array_ops.shape(matrix)
69 batch_shape = matrix_shape[:-2]
71 small_dim = matrix_shape[-1]
73 small_dim = matrix_shape[-2]
254 matrix_shape = tensor_shape[-2:]
258 is_io_bound = batch_shape.num_elements() > np.min(matrix_shape)
280 matrix_shape = matrix.get_shape()[-2:]
281 if matrix_shape.is_fully_defined():
282 if matrix_shape[-2] >= matrix_shape[-1]
[all...] |
| linalg_grad.py | 268 matrix_shape = op.inputs[0].get_shape()[-2:]
269 if matrix_shape.is_fully_defined():
270 if matrix_shape[-2] >= matrix_shape[-1]:
277 matrix_shape = array_ops.shape(op.inputs[0])[-2:]
278 return control_flow_ops.cond(matrix_shape[-2] >= matrix_shape[-1],
|
| array_grad.py | 334 matrix_shape = op.inputs[0].get_shape()[-2:]
335 if matrix_shape.is_fully_defined() and matrix_shape[0] == matrix_shape[1]:
347 matrix_shape = input_shape[-2:]
348 if batch_shape.is_fully_defined() and matrix_shape.is_fully_defined():
349 diag_shape = batch_shape.as_list() + [min(matrix_shape.as_list())]
355 matrix_shape = array_ops.slice(grad_shape, [grad_rank - 2], [2])
356 min_dim = math_ops.reduce_min(matrix_shape)
[all...] |
| /external/tensorflow/tensorflow/contrib/constrained_optimization/python/ |
| swap_regret_optimizer.py | 149 matrix_shape = matrix.get_shape()
150 if matrix_shape.ndims is None:
152 if matrix_shape.ndims != 2:
155 matrix_shape.ndims)
156 if matrix_shape[0] != matrix_shape[1]:
158 (matrix_shape[0], matrix_shape[1]))
159 dimension = matrix_shape.dims[0].value
|
| /external/tensorflow/tensorflow/python/ops/linalg/ |
| linear_operator_composition.py | 198 matrix_shape = tensor_shape.TensorShape(
209 return batch_shape.concatenate(matrix_shape)
220 matrix_shape = array_ops.stack([
231 return array_ops.concat((batch_shape, matrix_shape), 0)
|
| linear_operator_identity.py | 291 matrix_shape = tensor_shape.TensorShape((self._num_rows_static,
294 return matrix_shape
297 return batch_shape.concatenate(matrix_shape)
300 matrix_shape = array_ops.stack((self._num_rows, self._num_rows), axis=0)
302 return matrix_shape
304 return array_ops.concat((self._batch_shape_arg, matrix_shape), 0)
627 matrix_shape = tensor_shape.TensorShape((self._num_rows_static,
631 return batch_shape.concatenate(matrix_shape)
634 matrix_shape = array_ops.stack((self._num_rows, self._num_rows), axis=0)
637 return array_ops.concat((batch_shape, matrix_shape), 0
[all...] |
| linear_operator_zeros.py | 231 matrix_shape = tensor_shape.TensorShape((self._num_rows_static,
234 return matrix_shape
237 return batch_shape.concatenate(matrix_shape)
240 matrix_shape = array_ops.stack((self._num_rows, self._num_columns), axis=0)
242 return matrix_shape
244 return array_ops.concat((self._batch_shape_arg, matrix_shape), 0)
|
| linear_operator_block_diag.py | 226 matrix_shape = tensor_shape.TensorShape([domain_dimension, range_dimension])
235 return batch_shape.concatenate(matrix_shape)
249 matrix_shape = array_ops.stack([domain_dimension, range_dimension])
257 return array_ops.concat((batch_shape, matrix_shape), 0)
|
| linear_operator_kronecker.py | 245 matrix_shape = tensor_shape.TensorShape([
255 return batch_shape.concatenate(matrix_shape)
266 matrix_shape = [range_dimension, domain_dimension]
275 return array_ops.concat((batch_shape, matrix_shape), 0)
|
| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| xla_hlo_profile_test.cc | 270 Shape matrix_shape = ShapeUtil::MakeShape(F32, {size, size}); local
272 ShapeUtil::MakeTupleShape({ShapeUtil::MakeShape(S32, {}), matrix_shape});
302 Parameter(&builder, 0, matrix_shape, "initial_value")});
305 Parameter(&builder, 1, matrix_shape, "other_value"));
310 ExecuteAndFetchProfile(&profile_output, client, computation, matrix_shape,
311 matrix_shape);
|
| tuple_test.cc | 171 auto matrix_shape = builder.GetShape(matrix_element).ConsumeValueOrDie(); local
180 ASSERT_TRUE(ShapeUtil::Equal(matrix_shape,
|
| while_test.cc | 1190 auto matrix_shape = ShapeUtil::MakeShape(F32, {2, 2}); local
[all...] |
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
| math_utils.py | 121 matrix_shape = array_ops.shape(matrix)
122 ret_columns_list.append(matrix_shape[-1])
127 matrix_shape = array_ops.shape(matrix)
129 current_column += matrix_shape[-1]
[all...] |
| /external/tensorflow/tensorflow/compiler/xla/service/ |
| shape_inference_test.cc | 104 Shape matrix_shape = ShapeUtil::MakeShape(F32, {128, 64}); local
106 ShapeInference::InferUnaryOpShape(HloOpcode::kNegate, matrix_shape);
108 ASSERT_TRUE(ShapeUtil::Equal(matrix_shape, inferred_status.ValueOrDie()));
303 Shape matrix_shape = ShapeUtil::MakeShape(F32, {8, 8}); local
320 matrix_shape, init_value_shape, window, to_apply);
834 Shape matrix_shape = ShapeUtil::MakeShape(F32, {128, 64}); local
843 Shape matrix_shape = ShapeUtil::MakeShape(F32, {128, 64}); local
852 Shape matrix_shape = ShapeUtil::MakeShape(F32, {128, 64}); local
861 Shape matrix_shape = ShapeUtil::MakeShape(F32, {128, 64}); local
870 Shape matrix_shape = ShapeUtil::MakeShape(F32, {128, 64}); local
[all...] |
