| /external/webrtc/rtc_tools/ |
| D | metrics_plotter.py | 54 x_values = []
61 x_values.append((sample['time'] - start_x) / MICROSECONDS_IN_SECOND)
67 plt.plot(x_values, y_values)
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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/keras/distribute/ |
| D | distributed_training_utils_v1.py | 347 x_values = distribution_strategy.unwrap(x)
348 for value in x_values:
355 validate_all_tensor_shapes(x, x_values)
356 validate_all_tensor_types(x, x_values)
358 x_values_list.append(x_values[0])
362 def validate_all_tensor_types(x, x_values): argument
363 x_dtype = x_values[0].dtype
364 for i in range(1, len(x_values)):
365 if x_dtype != x_values[i].dtype:
370 def validate_all_tensor_shapes(x, x_values): argument
[all …]
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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)
115 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,
133 x_indices, x_values, x_shape_inconsistent)
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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 | sparse_conditional_accumulator_test.py | 491 x_values = array_ops.placeholder(dtypes_lib.float32)
493 accum_op = q.apply_grad(grad_indices=x_indices, grad_values=x_values)
501 x_values: np.array([1, 2]).astype(np.float32)
511 x_values = array_ops.placeholder(dtypes_lib.float32)
513 accum_op = q.apply_grad(grad_indices=x_indices, grad_values=x_values)
520 x_values: np.array([[0, 1, 1]]).astype(np.float32)
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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 | 51 x_values = x[non_zero]
55 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_binary_test.py | 54 x_values = x[non_zero]
58 indices=x_indices, values=x_values, dense_shape=x_shape), x_values
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| D | cwise_ops_test.py | 61 x_values = x[non_zero]
65 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/webrtc/rtc_tools/rtc_event_log_visualizer/proto/ |
| D | chart.proto | 9 repeated float x_values = 1; field
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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/debug/lib/ |
| D | debug_v2_ops_test.py | 169 x_values = []
181 x_values.append(int(tensor_util.MakeNdarray(trace.tensor_proto)))
187 self.assertAllEqual(x_values, [16, 8, 4, 2])
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| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | ragged_dispatch.py | 225 x_values = x.flat_values if ragged_tensor.is_ragged(x) else x
227 mapped_values = self._original_op(x_values, y_values, *args, **kwargs)
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| /external/tensorflow/tensorflow/python/ops/ |
| D | gradients_test.py | 767 x_values = [rng.randn(m).astype("float32") for _ in range(n)]
771 xs = [constant_op.constant(x_value) for x_value in x_values]
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| /external/tensorflow/tensorflow/lite/micro/examples/hello_world/train/ |
| D | train_hello_world_model.ipynb | 213 "x_values = np.random.uniform(\n",
217 "np.random.shuffle(x_values)\n",
220 "y_values = np.sin(x_values).astype(np.float32)\n",
223 "plt.plot(x_values, y_values, 'b.')\n",
272 "plt.plot(x_values, y_values, 'b.')\n",
330 "x_train, x_test, x_validate = np.split(x_values, [TRAIN_SPLIT, TEST_SPLIT])\n",
|