| /external/tensorflow/tensorflow/core/grappler/utils/ |
| grappler_test.cc | 31 std::vector<Tensor> output_tensors; local
33 &output_tensors, nullptr));
35 return output_tensors;
|
| /external/tensorflow/tensorflow/contrib/lite/ |
| graph_info_test.cc | 95 EXPECT_EQ(generated_subgraphs[subgraph_index].output_tensors,
96 expected_subgraphs[subgraph_index].output_tensors);
125 expected_subgraph.output_tensors = {1};
145 expected_subgraph.output_tensors = {0};
165 expected_subgraph.output_tensors = {1};
188 expected_subgraph0.output_tensors = {1};
193 expected_subgraph1.output_tensors = {2};
216 expected_subgraph0.output_tensors = {2};
247 expected_subgraph0.output_tensors = {1};
252 expected_subgraph1.output_tensors = {2}
[all...] |
| graph_info.h | 67 std::vector<int> output_tensors; member in struct:tflite::Subgraph
|
| graph_info.cc | 98 output_subgraph.output_tensors.push_back(output_index);
111 uniquefy(&subgraph.output_tensors);
174 input_subgraph.output_tensors.push_back(input_tensor_index);
|
| /external/tensorflow/tensorflow/contrib/tpu/python/tpu/ |
| training_loop.py | 133 output_tensors = [o for o in outputs
136 if outputs != output_tensors + output_operations:
141 output_types = [op.dtype for op in output_tensors]
152 if not output_tensors:
153 output_tensors = array_ops.constant(0)
159 return control_flow_ops.tuple(output_tensors,
162 return output_tensors
|
| tpu.py | 344 output_tensors = [o for o in outputs
347 if outputs != output_tensors + output_operations:
351 output_arity = len(output_tensors)
359 for t in output_tensors:
362 output_tensors = new_output_tensors
368 outputs = [tpu_ops.tpu_replicated_output(output_tensors[i], num_replicas,
|
| /external/tensorflow/tensorflow/python/eager/ |
| tape.py | 79 def record_operation(op_type, output_tensors, input_tensors, backward_function):
82 op_type, output_tensors, input_tensors, backward_function)
|
| pywrap_tfe.h | 121 // operation type, used in the backprop code. output_tensors should be a list of
127 void TFE_Py_TapeSetRecordOperation(PyObject* op_type, PyObject* output_tensors,
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/utils/ |
| saved_model_export_utils.py | 80 def build_standardized_signature_def(input_tensors, output_tensors,
91 output_tensors: a dict of string key to `Tensor`
99 ValueError: if input_tensors or output_tensors is None or empty.
104 if not output_tensors:
105 raise ValueError('output_tensors must be provided.')
108 if _is_classification_problem(problem_type, input_tensors, output_tensors):
110 classes = _get_classification_classes(output_tensors)
111 scores = _get_classification_scores(output_tensors)
113 items = list(output_tensors.items())
120 elif _is_regression_problem(problem_type, input_tensors, output_tensors)
[all...] |
| 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...] |
| /external/tensorflow/tensorflow/contrib/all_reduce/python/ |
| 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
[all...] |
| all_reduce_test.py | 100 output_tensors = ar._build_ring_gather(input_tensors, device_names, 1,
103 self.assertEqual(output_tensors, input_tensors)
107 output_tensors, pad_len = ar._build_ring_gather(
111 self.assertEqual(len(output_tensors), len(input_tensors))
114 for otl in output_tensors:
152 output_tensors = build_f(input_tensors, un_op)
153 sum_reduced = math_ops.add_n(output_tensors)
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| model_fn.py | 216 def _scores(output_tensors):
217 scores = output_tensors.get(prediction_key.PredictionKey.SCORES)
219 scores = output_tensors.get(prediction_key.PredictionKey.PROBABILITIES)
222 def _classes(output_tensors): # pylint: disable=missing-docstring
223 classes = output_tensors.get(prediction_key.PredictionKey.CLASSES)
|
| /external/tensorflow/tensorflow/python/layers/ |
| network.py | 110 # and set output_tensors' _keras_history.
118 output_tensors=[input_tensor])
176 outputs = input_layer._inbound_nodes[0].output_tensors # pylint: disable=protected-access
528 for x in node.output_tensors:
558 output_tensors=self.outputs)
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| remote_fused_graph_execute_utils_test.cc | 234 std::vector<tensorflow::Tensor> output_tensors; local
236 def, inputs, outputs, false /* initialize_by_zero */, &output_tensors);
238 EXPECT_EQ(outputs.size(), output_tensors.size());
239 EXPECT_NEAR(NODE_B_VAL, output_tensors.at(0).scalar<float>()(),
241 EXPECT_NEAR(1.0f + NODE_B_VAL, output_tensors.at(1).scalar<float>()(),
254 std::vector<tensorflow::Tensor> output_tensors; local
256 def, inputs, outputs, true /* initialize_by_zero */, &output_tensors);
258 EXPECT_EQ(outputs.size(), output_tensors.size());
259 EXPECT_NEAR(NODE_B_VAL, output_tensors.at(0).scalar<float>()(),
261 EXPECT_NEAR(NODE_B_VAL, output_tensors.at(1).scalar<float>()()
280 std::vector<tensorflow::Tensor> output_tensors; local
[all...] |
| remote_fused_graph_execute_op_test.cc | 291 std::vector<Tensor> output_tensors; local
312 status = session->Run(run_options, inputs, outputs, {}, &output_tensors,
317 ASSERT_EQ(1, output_tensors.size());
319 output_tensors.at(0).flat<float>().data()[0],
|
| remote_fused_graph_execute_utils.cc | 203 std::vector<tensorflow::Tensor>* output_tensors) {
240 CHECK(output_tensors != nullptr);
257 output_tensors, &run_metadata);
271 std::vector<Tensor> output_tensors; local
272 output_tensors.reserve(graph_def.node_size());
291 initialize_by_zero, &output_tensors);
297 CHECK_EQ(output_node_names.size(), output_tensors.size())
298 << output_node_names.size() << ", " << output_tensors.size();
304 output_tensors.push_back(input_node_info.second);
309 const Tensor& tensor = output_tensors.at(i)
[all...] |
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| 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)
[all...] |
| /external/tensorflow/tensorflow/cc/framework/ |
| while_gradients.cc | 36 const std::vector<OutputTensor>& output_tensors) {
37 size_t n = output_tensors.size();
40 for (int i = 0; i < n; ++i) result.push_back(ToOutput(output_tensors[i]));
|
| /external/tensorflow/tensorflow/contrib/kernel_methods/python/ |
| kernel_estimators.py | 100 output_tensors = []
102 output_tensors.append(kernel_mapper.map(features[column_name]))
103 tensor = array_ops.concat(output_tensors, 1)
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/ |
| models.py | 502 if len(layer._inbound_nodes[-1].output_tensors) != 1:
508 self.outputs = [layer._inbound_nodes[-1].output_tensors[0]]
519 output_tensors=self.outputs)
529 self._inbound_nodes[0].output_tensors = self.outputs
553 self._inbound_nodes[0].output_tensors = self.outputs
[all...] |
| /external/tensorflow/tensorflow/c/ |
| c_api_function.cc | 426 std::vector<OutputTensor>* output_tensors)
428 output_tensors->reserve(noutputs);
439 output_tensors->emplace_back(&node, idx);
505 std::vector<tensorflow::OutputTensor> output_tensors;
507 outputs, &output_tensors);
530 input_tensors, output_tensors, output_names_vec, description,
|
| /external/tensorflow/tensorflow/tools/benchmark/ |
| benchmark_model.cc | 140 std::vector<tensorflow::Tensor> output_tensors; local
157 session->Run(input_tensors, output_tensor_names, {}, &output_tensors));
158 CHECK_EQ(output_tensors.size(), output_tensor_names.size());
161 const TensorShape& found_shape = output_tensors[i].shape();
256 std::vector<tensorflow::Tensor> output_tensors; local
267 s = session->Run(run_options, input_tensors, outputs, {}, &output_tensors,
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/engine/ |
| topology.py | 270 output_tensors = _to_list(output)
274 for i in range(len(output_tensors)):
275 output_tensors[i]._uses_learning_phase = getattr(
276 output_tensors[i], '_uses_learning_phase', False) or uses_lp
646 outputs = input_layer._inbound_nodes[0].output_tensors
[all...] |
| /external/tensorflow/tensorflow/contrib/lite/python/ |
| lite.py | 143 output_tensors,
158 output_tensors: List of output tensors (only .name is used from this).
207 for output_tensor in output_tensors:
|
