/external/tensorflow/tensorflow/python/distribute/ |
D | all_reduce.py | 288 output_tensors = _build_ring_scatter(pred_by_s_d, rank_by_s_d, 291 output_tensors = _strip_padding(output_tensors, pad_len) 293 output_tensors = _reshape_tensors(output_tensors, shape) 294 return output_tensors 468 output_tensors = _build_recursive_hd_scatter(reduced_shards, devices) 470 output_tensors = _reshape_tensors(output_tensors, shape) 471 return output_tensors 580 output_tensors = _build_shuffle_scatter(reduced_shards, dst_devices) 582 output_tensors = _reshape_tensors(output_tensors, shape) 583 return output_tensors [all …]
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D | all_reduce_test.py | 109 output_tensors = ar._build_ring_gather(input_tensors, device_names, 1, 112 self.assertEqual(output_tensors, input_tensors) 116 output_tensors, pad_len = ar._build_ring_gather( 120 self.assertEqual(len(output_tensors), len(input_tensors)) 123 for otl in output_tensors: 161 output_tensors = build_f(input_tensors, un_op) 162 sum_reduced = math_ops.add_n(output_tensors)
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/external/tensorflow/tensorflow/contrib/learn/python/learn/utils/ |
D | saved_model_export_utils.py | 86 def build_standardized_signature_def(input_tensors, output_tensors, argument 110 if not output_tensors: 114 if _is_classification_problem(problem_type, input_tensors, output_tensors): 116 classes = _get_classification_classes(output_tensors) 117 scores = _get_classification_scores(output_tensors) 119 items = list(output_tensors.items()) 126 elif _is_regression_problem(problem_type, input_tensors, output_tensors): 128 (_, predictions), = output_tensors.items() 132 output_tensors) 135 def _get_classification_scores(output_tensors): argument [all …]
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D | saved_model_export_utils_test.py | 80 output_tensors = { 87 input_tensors, output_tensors, problem_type)) 111 output_tensors = { 118 input_tensors, output_tensors, problem_type)) 143 output_tensors = { 158 input_tensors, output_tensors, problem_type)) 190 output_tensors = { 204 input_tensors, output_tensors, problem_type)) 236 output_tensors = { 247 input_tensors, output_tensors, problem_type)) [all …]
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/external/tensorflow/tensorflow/python/tpu/ |
D | training_loop.py | 134 output_tensors = [o for o in outputs 137 if outputs != output_tensors + output_operations: 142 output_types = [op.dtype for op in output_tensors] 153 if not output_tensors: 154 output_tensors = array_ops.constant(0) 160 output_tensors = control_flow_ops.tuple(output_tensors, 168 output_tensors = tt.trace_tpu(ops.get_default_graph(), 169 output_tensors, None, 171 return output_tensors
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D | tpu.py | 908 output_tensors, control_deps = _postprocess_flat_outputs(outputs) 910 output_tensors, control_deps = _postprocess_non_flat_outputs(outputs) 919 output_tensors = tt.trace_tpu(ops.get_default_graph(), 920 output_tensors, control_deps, 923 context.ExitResult(output_tensors) 943 if not output_tensors: 956 for i, t in enumerate(output_tensors): 1016 output_tensors = [o for o in outputs if not isinstance(o, ops.Operation)] 1018 if outputs != output_tensors + output_operations: 1029 for t in output_tensors:
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/external/tensorflow/tensorflow/lite/python/ |
D | lite.py | 251 output_tensors = frozen_func.outputs 255 input_tensors, output_tensors, 302 output_tensors=output_tensors, 406 output_tensors, argument 430 self._output_tensors = output_tensors 457 def from_session(cls, sess, input_tensors, output_tensors): argument 469 graph_def = _freeze_graph(sess, output_tensors) 470 return cls(graph_def, input_tensors, output_tensors) 543 output_tensors = _get_tensors_from_tensor_names( 547 return cls(sess.graph_def, input_tensors, output_tensors) [all …]
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D | convert.py | 233 output_tensors, argument 365 for output_tensor in output_tensors: 402 input_tensors=[], output_tensors=[], *args, **kwargs) 425 def toco_convert_impl(input_data, input_tensors, output_tensors, *args, argument 449 input_tensors, output_tensors, *args, **kwargs) 458 def toco_convert(input_data, input_tensors, output_tensors, *args, **kwargs): argument 481 return toco_convert_impl(input_data, input_tensors, output_tensors, *args,
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/external/tensorflow/tensorflow/lite/ |
D | graph_info_test.cc | 98 EXPECT_EQ(generated_subgraphs[subgraph_index].output_tensors, in CheckPartitionSubgraphs() 99 expected_subgraphs[subgraph_index].output_tensors); in CheckPartitionSubgraphs() 142 expected_subgraph.output_tensors = {1}; in TEST() 162 expected_subgraph.output_tensors = {0}; in TEST() 182 expected_subgraph.output_tensors = {1}; in TEST() 205 expected_subgraph0.output_tensors = {1}; in TEST() 210 expected_subgraph1.output_tensors = {2}; in TEST() 233 expected_subgraph0.output_tensors = {2}; in TEST() 264 expected_subgraph0.output_tensors = {1}; in TEST() 269 expected_subgraph1.output_tensors = {2}; in TEST() [all …]
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D | graph_info.cc | 103 output_subset.output_tensors.push_back(output_index); in Partition() 116 uniquefy(&node_subset.output_tensors); in Partition() 183 input_subset.output_tensors.push_back(input_tensor_index); in UpdateNode()
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/external/tensorflow/tensorflow/lite/tools/accuracy/ |
D | run_tflite_model_op.cc | 90 OpOutputList output_tensors; in Compute() local 92 context->output_list("model_output", &output_tensors)); in Compute() 94 OP_REQUIRES(context, output_tensors.size() == tfl_outputs.size(), in Compute() 97 " got: ", output_tensors.size())); in Compute() 98 for (int i = 0; i < output_tensors.size(); i++) { in Compute() 101 DataType otype = output_tensors.expected_output_dtype(i); in Compute() 125 for (int i = 0; i < output_tensors.size(); i++) { in Compute() 129 OP_REQUIRES_OK(context, output_tensors.allocate(i, shape, &output)); in Compute()
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/external/tensorflow/tensorflow/contrib/compiler/ |
D | xla.py | 347 output_tensors, control_deps = _postprocess_flat_outputs(outputs) 349 output_tensors, control_deps = _postprocess_non_flat_outputs(outputs) 351 context.ExitResult(output_tensors) 360 if not output_tensors: 363 output_tensors = [ 365 for i, o in enumerate(output_tensors) 371 output_tensors = [ 373 for i, o in enumerate(output_tensors) 379 output_tensors = nest.pack_sequence_as( 380 structure=outputs, flat_sequence=output_tensors) [all …]
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/external/tensorflow/tensorflow/python/keras/ |
D | models.py | 157 output_tensors = layer(computed_tensors, **kwargs) 160 nest.flatten(node.output_tensors), nest.flatten(output_tensors)): 165 output_tensors = [] 168 output_tensors.append(tensor_map[x]) 171 output_tensors = nest.pack_sequence_as(model._nested_outputs, output_tensors) 172 return Model(input_tensors, output_tensors, name=model.name)
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/external/tensorflow/tensorflow/core/grappler/utils/ |
D | grappler_test.cc | 101 std::vector<Tensor> output_tensors; in EvaluateNodes() local 103 &output_tensors, nullptr)); in EvaluateNodes() 105 return output_tensors; in EvaluateNodes() 118 std::vector<Tensor> output_tensors; in EvaluateFetchNodes() local 120 &output_tensors, nullptr)); in EvaluateFetchNodes() 122 return output_tensors; in EvaluateFetchNodes()
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D | functions.cc | 610 std::vector<string> output_tensors; in MakeGrapplerFunctionItem() local 615 ? connectivity.ExpandFunctionDefInput(ret->second, &output_tensors) in MakeGrapplerFunctionItem() 617 : connectivity.ExpandFunctionDefInput(out.name(), &output_tensors)); in MakeGrapplerFunctionItem() 620 for (int i = 0; i < output_tensors.size(); ++i) { in MakeGrapplerFunctionItem() 621 const string& output_tensor = output_tensors[i]; in MakeGrapplerFunctionItem() 802 absl::flat_hash_map<absl::string_view, string> output_tensors; in MakeFunctionDef() local 814 output_tensors.emplace(node_name, func_body_node.input(0)); in MakeFunctionDef() 824 [&output_tensors](const OutputArgExpansion& output_arg) -> const string& { in MakeFunctionDef() 826 const auto is_output_tensor = output_tensors.find(output_node); in MakeFunctionDef() 827 return is_output_tensor == output_tensors.end() ? output_node in MakeFunctionDef() [all …]
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/external/tensorflow/tensorflow/python/keras/engine/ |
D | network.py | 302 output_tensors=self._nested_outputs) 483 output_tensors = self._run_internal_graph(inputs, mask=mask) 484 return nest.map_structure(lambda t: t._keras_mask, output_tensors) 1010 output_tensors = layer(computed_tensors, **kwargs) 1014 nest.flatten(node.output_tensors), nest.flatten(output_tensors)): 1017 output_tensors = [] 1023 output_tensors.append(tensor) 1031 output_tensors = nest.pack_sequence_as(self._nested_outputs, output_tensors) 1032 return output_tensors 1194 nest.flatten(inbound_node.output_tensors)[inbound_tensor_index]) [all …]
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/external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
D | model_fn.py | 232 def _scores(output_tensors): argument 233 scores = output_tensors.get(prediction_key.PredictionKey.SCORES) 235 scores = output_tensors.get(prediction_key.PredictionKey.PROBABILITIES) 238 def _classes(output_tensors): # pylint: disable=missing-docstring argument 239 classes = output_tensors.get(prediction_key.PredictionKey.CLASSES)
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/external/tensorflow/tensorflow/lite/tools/ |
D | verifier.cc | 198 variable_tensors, output_tensors; in VerifySubGraphConsistency() local 221 output_tensors.find(input_idx) == output_tensors.end()) { in VerifySubGraphConsistency() 248 } else if (output_tensors.find(output_idx) != output_tensors.end()) { in VerifySubGraphConsistency() 257 output_tensors.insert(output_idx); in VerifySubGraphConsistency()
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/external/tensorflow/tensorflow/core/kernels/ |
D | remote_fused_graph_execute_utils_test.cc | 235 std::vector<tensorflow::Tensor> output_tensors; in TEST() local 237 def, inputs, outputs, false /* initialize_by_zero */, &output_tensors); in TEST() 239 EXPECT_EQ(outputs.size(), output_tensors.size()); in TEST() 240 EXPECT_NEAR(NODE_B_VAL, output_tensors.at(0).scalar<float>()(), in TEST() 242 EXPECT_NEAR(1.0f + NODE_B_VAL, output_tensors.at(1).scalar<float>()(), in TEST() 255 std::vector<tensorflow::Tensor> output_tensors; in TEST() local 257 def, inputs, outputs, true /* initialize_by_zero */, &output_tensors); in TEST() 259 EXPECT_EQ(outputs.size(), output_tensors.size()); in TEST() 260 EXPECT_NEAR(NODE_B_VAL, output_tensors.at(0).scalar<float>()(), in TEST() 262 EXPECT_NEAR(NODE_B_VAL, output_tensors.at(1).scalar<float>()(), in TEST() [all …]
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D | remote_fused_graph_execute_op_test.cc | 291 std::vector<Tensor> output_tensors; in TEST() local 312 status = session->Run(run_options, inputs, outputs, {}, &output_tensors, in TEST() 317 ASSERT_EQ(1, output_tensors.size()); in TEST() 319 output_tensors.at(0).flat<float>().data()[0], in TEST()
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/external/tensorflow/tensorflow/contrib/layers/python/layers/ |
D | feature_column_ops.py | 110 output_tensors = [] 131 output_tensors.append( 142 output_tensors.append(column._to_dnn_input_layer( 151 cols_to_outs[column] = output_tensors[-1] 152 return array_ops.concat(output_tensors, output_rank - 1) 490 output_tensors = [] 526 output_tensors.append(array_ops.reshape( 532 predictions_no_bias = math_ops.add_n(output_tensors)
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/external/tensorflow/tensorflow/contrib/feature_column/python/feature_column/ |
D | sequence_feature_column.py | 110 output_tensors = [] 126 output_tensors.append( 130 fc._verify_static_batch_size_equality(output_tensors, ordered_columns) 134 return array_ops.concat(output_tensors, -1), sequence_length
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/external/tensorflow/tensorflow/contrib/kernel_methods/python/ |
D | kernel_estimators.py | 100 output_tensors = [] 102 output_tensors.append(kernel_mapper.map(features[column_name])) 103 tensor = array_ops.concat(output_tensors, 1)
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/external/tensorflow/tensorflow/cc/framework/ |
D | while_gradients.cc | 36 const std::vector<OutputTensor>& output_tensors) { in ToOutputVector() argument 37 size_t n = output_tensors.size(); in ToOutputVector() 40 for (int i = 0; i < n; ++i) result.push_back(ToOutput(output_tensors[i])); in ToOutputVector()
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/external/tensorflow/tensorflow/tools/api/golden/v1/ |
D | tensorflow.lite.-t-f-lite-converter.pbtxt | 7 …argspec: "args=[\'self\', \'graph_def\', \'input_tensors\', \'output_tensors\', \'input_arrays_wit… 27 …argspec: "args=[\'cls\', \'sess\', \'input_tensors\', \'output_tensors\'], varargs=None, keywords=…
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