| /external/autotest/cli/ |
| D | compose_query | 33 data_column_width = max([max(13,len(x)) for x in test_data.x_values])
34 column_widths = [widest_row_header] + [data_column_width] * len(test_data.x_values)
37 print format % tuple([''] + test_data.x_values)
42 for x in test_data.x_values:
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| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | distributed_training_utils.py | 293 x_values = distribution_strategy.unwrap(x)
296 validate_all_tensor_shapes(x, x_values)
297 validate_all_tensor_types(x, x_values)
299 x_values_list.append(x_values[0])
303 def validate_all_tensor_types(x, x_values): argument
304 x_dtype = x_values[0].dtype
305 for i in range(1, len(x_values)):
306 if x_dtype != x_values[i].dtype:
311 def validate_all_tensor_shapes(x, x_values): argument
313 x_shape = x_values[0].get_shape().as_list()
[all …]
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | quantized_mul_op_test.cc | 39 const std::vector<float>& x_values, float x_min_value, in TestMul() argument
47 test::FillValues<float>(&x_float_tensor, x_values); in TestMul()
90 std::vector<float> x_values(x_num_elements); in TestMulShape() local
92 x_values[i] = i % 256; in TestMulShape()
108 test::FillValues<float>(&x_float_tensor, x_values); in TestMulShape()
133 TestMul(x_shape, x_values, x_min_value, x_max_value, y_shape, y_values, in TestMulShape()
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| D | quantized_add_op_test.cc | 39 const std::vector<float>& x_values, float x_min_value, in TestAdd() argument
47 test::FillValues<float>(&x_float_tensor, x_values); in TestAdd()
90 std::vector<float> x_values(x_num_elements); in TestAddShape() local
92 x_values[i] = i % 256; in TestAddShape()
108 test::FillValues<float>(&x_float_tensor, x_values); in TestAddShape()
133 TestAdd(x_shape, x_values, x_min_value, x_max_value, y_shape, y_values, in TestAddShape()
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | sparse_tensor_dense_matmul_grad_test.py | 39 x_values = x[non_zero]
43 indices=x_indices, values=x_values, dense_shape=x_shape), len(x_values)
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| D | sparse_tensor_dense_matmul_op_test.py | 66 x_values = x[np.where(x)]
71 indices=x_indices, values=x_values, dense_shape=x_shape)
117 x_values = x[np.where(x)]
119 x_st = sparse_tensor.SparseTensor(x_indices, x_values, x_shape)
124 x_st_shape_unknown = sparse_tensor.SparseTensor(x_indices, x_values,
132 x_st_shape_inconsistent = sparse_tensor.SparseTensor(x_indices, x_values,
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| D | sparse_conditional_accumulator_test.py | 476 x_values = array_ops.placeholder(dtypes_lib.float32)
478 accum_op = q.apply_grad(grad_indices=x_indices, grad_values=x_values)
486 x_values: np.array([1, 2]).astype(np.float32)
496 x_values = array_ops.placeholder(dtypes_lib.float32)
498 accum_op = q.apply_grad(grad_indices=x_indices, grad_values=x_values)
505 x_values: np.array([[0, 1, 1]]).astype(np.float32)
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| D | sparse_add_op_test.py | 44 x_values = x[non_zero]
48 indices=x_indices, values=x_values, dense_shape=x_shape), len(x_values)
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| D | shape_ops_test.py | 44 x_values = x[non_zero]
48 indices=x_indices, values=x_values, dense_shape=x_shape), len(x_values)
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| D | cwise_ops_unary_test.py | 48 x_values = x[non_zero]
52 indices=x_indices, values=x_values, dense_shape=x_shape), x_values
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| D | cwise_ops_binary_test.py | 53 x_values = x[non_zero]
57 indices=x_indices, values=x_values, dense_shape=x_shape), x_values
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| D | sparse_ops_test.py | 46 x_values = x[non_zero]
50 indices=x_indices, values=x_values, dense_shape=x_shape), len(x_values)
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| D | cwise_ops_test.py | 63 x_values = x[non_zero]
67 indices=x_indices, values=x_values, dense_shape=x_shape), x_values
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| /external/autotest/tko/ |
| D | compose_query.cgi | 295 if not f_column in test_data.x_values:
296 test_data.x_values.append(f_column)
308 for x in test_data.x_values:
325 for x in test_data.x_values:
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| D | frontend.py | 64 self.x_values = smart_sort(data.keys(), x_field)
67 nCells = len(self.y_values)*len(self.x_values)
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| /external/tensorflow/tensorflow/contrib/rnn/python/kernel_tests/ |
| D | lstm_ops_test.py | 303 x_values = np.random.randn(1, 2)
322 x.name: x_values,
339 x.name: x_values,
353 x_values = np.random.randn(1, 2)
375 x.name: x_values,
392 x.name: x_values,
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| D | gru_ops_test.py | 111 x_values = np.random.rand(time_steps, batch_size, input_size)
123 feeds = {concat_x: x_values, h: h_value}
136 feeds = {concat_x: x_values, h: h_value}
235 x_values = np.random.rand(time_steps, batch_size, input_size)
237 feeds = {concat_x: x_values, h: h_value}
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| /external/tensorflow/tensorflow/tools/graph_transforms/ |
| D | quantize_nodes_test.cc | 250 std::vector<float> x_values(x_num_elements); in TestQuantizeMul() local
252 x_values[i] = (i % 256) / 256.0f; in TestQuantizeMul()
265 test::FillValues<float>(&x_float_tensor, x_values); in TestQuantizeMul()
285 std::vector<float> x_values(x_num_elements); in TestQuantizeAdd() local
287 x_values[i] = (i % 256) / 256.0f; in TestQuantizeAdd()
300 test::FillValues<float>(&x_float_tensor, x_values); in TestQuantizeAdd()
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| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | ragged_dispatch.py | 211 x_values = x.flat_values if ragged_tensor.is_ragged(x) else x
213 mapped_values = self._original_op(x_values, y_values, *args, **kwargs)
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| /external/tensorflow/tensorflow/python/ops/ |
| D | gradients_test.py | 674 x_values = [rng.randn(m).astype("float32") for _ in range(n)]
678 xs = [constant_op.constant(x_value) for x_value in x_values]
|