| /external/tensorflow/tensorflow/core/kernels/hexagon/ |
| graph_transferer_test.cc | 309 const std::vector<string> output_node_names = {NAME_A_PLUS_B}; local
311 inputs, output_node_names, false);
320 const std::vector<string> output_node_names = {"softmax"}; local
322 input_node_info_list, output_node_names,
346 const std::vector<string> output_node_names = {"softmax"}; local
348 input_node_info_list, output_node_names,
382 std::vector<string> output_node_names = {}; local
389 // output_node_names.emplace_back("softmax");
396 *ops_definitions, filename, input_node_info_list, output_node_names,
445 std::vector<string> output_node_names = {} local
[all...] |
| hexagon_graph_execution_test.cc | 304 std::vector<string> output_node_names; local
305 output_node_names.emplace_back(REMOTE_FUSED_GRAPH_EXECUTE_NODE_NAME);
309 TF_ASSERT_OK(session->Run(run_options, input_tensors, output_node_names, {},
411 std::vector<string> output_node_names = {"softmax"}; local
419 *ops_definitions, MODEL_FILENAME, inputs, output_node_names,
444 std::vector<string> output_node_names = {"softmax"}; local
453 output_node_names,
478 std::vector<string> output_node_names = {"softmax"}; local
486 *ops_definitions, MODEL_FILENAME, inputs, output_node_names,
547 std::vector<string> output_node_names = {"softmax"} local
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| remote_fused_graph_execute_utils.cc | 202 const std::vector<string>& output_node_names, const bool initialize_by_zero,
256 status = session->Run(run_options, input_tensors, output_node_names, {},
273 std::vector<string> output_node_names; local
286 output_node_names.emplace_back(strings::StrCat(node->name(), ":", i));
290 status = DryRunInference(graph_def, input_node_info_list, output_node_names,
297 CHECK_EQ(output_node_names.size(), output_tensors.size())
298 << output_node_names.size() << ", " << output_tensors.size();
307 for (int i = 0; static_cast<size_t>(i) < output_node_names.size(); ++i) {
308 const string& name = output_node_names.at(i);
314 const Tensor& tensor = output_tensors.at(output_node_names.size() + i)
[all...] |
