Searched defs:tensors (Results 1 - 25 of 36) sorted by relevance

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/external/tensorflow/tensorflow/core/framework/
H A Dunique_tensor_references_test.cc32 TensorReferenceVector tensors; local
33 refs.FreezeAndReturnReferences(&tensors);
34 EXPECT_EQ(2, tensors.size());
35 if (tensors[0].SharesBufferWith(a)) {
36 EXPECT_TRUE(tensors[1].SharesBufferWith(b));
38 EXPECT_TRUE(tensors[1].SharesBufferWith(a));
39 EXPECT_TRUE(tensors[0].SharesBufferWith(b));
41 for (auto& t : tensors) {
55 TensorReferenceVector tensors; local
56 refs.FreezeAndReturnReferences(&tensors);
91 TensorReferenceVector tensors; local
116 TensorReferenceVector tensors; local
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H A Dtensor_util.cc48 Status Concat(const gtl::ArraySlice<Tensor>& tensors, Tensor* result) { argument
49 if (tensors.empty()) {
50 return errors::InvalidArgument("Cannot concatenate zero tensors");
53 for (const Tensor& tensor : tensors) {
60 TensorShape shape = tensors[0].shape();
63 const DataType dtype = tensors[0].dtype();
64 for (int i = 1; i < tensors.size(); ++i) {
65 if (tensors[i].dtype() != dtype) {
67 "Cannot concatenate tensors that have different data types");
79 for (const Tensor& tensor : tensors) {
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H A Dvariant_tensor_data.cc33 const Tensor& VariantTensorData::tensors(int index) const { function in class:tensorflow::VariantTensorData
37 const std::vector<Tensor>& VariantTensorData::tensors() const { function in class:tensorflow::VariantTensorData
58 for (const auto& tensor : proto.tensors()) {
89 strings::StrCat(repeated_field, " tensors: ", t.DebugString());
/external/tensorflow/tensorflow/cc/framework/
H A Dtestutil.cc27 void GetTensors(const Scope& scope, OutputList tensors, argument
30 TF_CHECK_OK(session.Run(tensors, out));
40 const OutputList& tensors, std::vector<Tensor>* out) {
43 TF_CHECK_OK(session.Run(tensors, out));
39 GetTensors(const Scope& scope, const std::vector<Output>& assign_vars, const OutputList& tensors, std::vector<Tensor>* out) argument
/external/tensorflow/tensorflow/contrib/lite/toco/tflite/
H A Dexport_test.cc58 details::TensorsMap tensors; local
59 details::LoadTensorsMap(input_model_, &tensors);
60 EXPECT_EQ(0, tensors["tensor_one"]);
61 EXPECT_EQ(1, tensors["tensor_two"]);
107 // TODO(ahentz): tests for tensors, inputs, outpus, opcodes and operators.
H A Dimport_test.cc43 // The tensors
65 auto tensors = builder_.CreateVector( local
77 auto subgraph = ::tflite::CreateSubGraph(builder_, tensors, 0, 0, 0);
99 details::TensorsTable tensors; local
100 details::LoadTensorsTable(*input_model_, &tensors);
101 EXPECT_THAT(tensors, ElementsAre("tensor_one", "tensor_two"));
H A Dimport.cc31 auto tensors = (*input_model.subgraphs())[0]->tensors(); local
32 if (!tensors) return;
33 for (const auto* tensor : *tensors) {
54 auto tensors = (*input_model.subgraphs())[0]->tensors(); local
56 // auto tensors = input_model.tensors();
57 if (!tensors) return;
58 for (const auto* input_tensor : *tensors) {
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/external/tensorflow/tensorflow/core/kernels/data/
H A Dtensor_dataset_op.cc35 // TODO(mrry): Validate that the shapes of the "components" tensors match
48 Dataset(OpKernelContext* ctx, std::vector<Tensor> tensors) argument
49 : GraphDatasetBase(ctx), tensors_(std::move(tensors)) {
H A Dtensor_slice_dataset_op.cc59 explicit Dataset(OpKernelContext* ctx, std::vector<Tensor> tensors) argument
60 : GraphDatasetBase(ctx), tensors_(std::move(tensors)) {
/external/tensorflow/tensorflow/core/kernels/
H A Dmerge_v2_checkpoints_op_test.cc37 gtl::ArraySlice<Tensor> tensors) {
39 ASSERT_TRUE(names.size() == tensors.size());
41 TF_ASSERT_OK(writer.Add(names[i], tensors[i]));
94 // We expect to find all saved tensors.
36 WriteCheckpoint(const string& prefix, gtl::ArraySlice<string> names, gtl::ArraySlice<Tensor> tensors) argument
H A Dlist_kernels.h37 // Variant compatible type for a list of tensors. This is mutable but instances
54 std::vector<Tensor> tensors; member in struct:tensorflow::TensorList
88 OP_REQUIRES(c, l->tensors.size() == num_elements_,
92 l->tensors.size(), " elements."));
95 resulting_shape.AddDim(l->tensors.size());
106 inputs_flat.reserve(l->tensors.size());
107 for (const auto& t : l->tensors) {
155 output_list.tensors.reserve(t.shape().dim_size(0));
163 output_list.tensors.push_back(tmp);
169 output_list.tensors
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H A Dserialize_sparse_op.cc413 std::vector<SparseTensor> tensors; variable
414 tensors.reserve(num_sparse_tensors);
416 tensors.emplace_back(indices[i], values[i], shape, std_order);
422 maybe_output = SparseTensor::Concat<T>(tensors); \
/external/tensorflow/tensorflow/core/common_runtime/gpu/
H A Dgpu_event_mgr.cc96 const TensorReferenceVector& tensors) {
105 for (const auto& t : tensors) {
95 ThenDeleteTensors(perftools::gputools::Stream* stream, const TensorReferenceVector& tensors) argument
H A Dgpu_event_mgr_test.cc51 TensorReferenceVector* tensors) {
53 em_->QueueTensors(stream, tensors);
182 th.PollEvents(false); // Harvest the tensors ready to be freed.
224 // Some of the tensors at least should be flushed
50 QueueTensors(perftools::gputools::Stream* stream, TensorReferenceVector* tensors) argument
/external/tensorflow/tensorflow/core/grappler/costs/
H A Dgraph_memory_test.cc58 std::set<string> tensors; local
60 tensors.insert(strings::StrCat(t.node, ":", t.output_id));
64 // the order in which this takes place, in the worst case the 3 tensors are in
70 EXPECT_EQ(expected, tensors);
88 std::set<string> tensors; local
90 tensors.insert(strings::StrCat(t.node, ":", t.output_id));
96 EXPECT_EQ(expected, tensors);
215 std::set<string> tensors; local
217 tensors.insert(strings::StrCat(t.node, ":", t.output_id));
223 EXPECT_EQ(expected, tensors);
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/external/tensorflow/tensorflow/contrib/lite/tools/
H A Dverifier_test.cc190 auto tensors = builder.CreateVector(std::vector<Offset<Tensor>>{ local
194 {CreateSubGraph(builder, tensors, /*inputs=*/0, /*outputs=*/0,
/external/tensorflow/tensorflow/core/common_runtime/
H A Ddevice.h92 // Takes ownership of the references in tensors. If necessary, a
94 // accessed tensors until the async computation has completed.
96 DeviceContext* context, const TensorReferenceVector& tensors) {
97 for (const auto& ref : tensors) {
95 ConsumeListOfAccessedTensors( DeviceContext* context, const TensorReferenceVector& tensors) argument
/external/tensorflow/tensorflow/contrib/lite/
H A Darena_planner_test.cc100 std::vector<TfLiteTensor>* tensors() { return &tensors_; } function in class:tflite::__anon25861::TestGraph
116 size_t num_tensors() const override { return graph_->tensors()->size(); }
118 return &graph_->tensors()->at(index);
161 const TfLiteTensor& tensor = (*graph_->tensors())[tensor_index];
168 const TfLiteTensor& tensor = (*graph_->tensors())[tensor_index];
196 EXPECT_TRUE((*graph.tensors())[5].data.raw == nullptr);
197 EXPECT_TRUE((*graph.tensors())[11].data.raw == nullptr);
210 (*graph.tensors())[1].bytes = 0;
293 (*graph.tensors())[1].bytes = 40;
318 (*graph.tensors())[
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H A Dcontext.h23 // TfLiteContext - allows an op to access the tensors
64 // Check if two tensors are equal. Returns 1 if they are equal, 0 otherwise.
156 // data. kTfLiteDynamic is for tensors that are allocated during evaluation.
215 // Inputs to this node expressed as indices into the simulator's tensors.
218 // Outputs to this node expressed as indices into the simulator's tensors.
221 // Temporary tensors uses during the computations. This usually contains no
222 // tensors, but ops are allowed to change that if they need scratch space of
240 // Number of tensors in the context.
261 // An tensor of tensors in the interpreter context (of length `tensors_size`)
262 TfLiteTensor* tensors; member in struct:TfLiteContext
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H A Dmodel.cc622 const flatbuffers::Vector<flatbuffers::Offset<Tensor>>* tensors,
634 for (int i = 0; i < tensors->Length(); ++i) {
635 const auto* tensor = tensors->Get(i);
762 // Construct interpreter with correct number of tensors and operators.
771 auto tensors = subgraph->tensors(); local
772 if (!operators || !tensors || !buffers) {
774 "Did not get operators, tensors, or buffers in input flat buffer.\n");
778 if ((**interpreter).AddTensors(tensors->Length()) != kTfLiteOk) {
786 // Finally setup nodes and tensors
620 ParseTensors( const flatbuffers::Vector<flatbuffers::Offset<Buffer>>* buffers, const flatbuffers::Vector<flatbuffers::Offset<Tensor>>* tensors, Interpreter* interpreter) argument
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/external/tensorflow/tensorflow/contrib/lite/kernels/
H A Dtest_util.cc83 // Initialize buffers list with empty buffer to allow for non-const tensors.
159 auto tensors = builder_.CreateVector(tensors_); local
164 auto subgraph = CreateSubGraph(builder_, tensors, inputs, outputs, operators);
194 << "Cannot allocate tensors";
/external/tensorflow/tensorflow/core/debug/
H A Ddebug_grpc_io_utils_test.cc182 // Prepare the tensors to sent.
183 std::vector<Tensor> tensors; local
187 tensors.push_back(tensor);
202 auto fn = [this, &mu, &tensor_count, &tensors, &statuses, &all_done,
210 // Different concurrent tasks will send different tensors.
216 tensors[this_count], wall_time, urls);
245 // One prep tensor plus kSends concurrent tensors are expected.
H A Dgrpc_session_debug_test.cc120 void LoadTensorDumps(const string& subdir, std::vector<Tensor>* tensors) { argument
135 tensors->push_back(tensor);
/external/tensorflow/tensorflow/core/grappler/optimizers/
H A Dmemory_optimizer_test.cc390 auto tensors = EvaluateNodes(output, fetch); local
391 EXPECT_EQ(4, tensors.size());
393 for (int i = 0; i < tensors[0].NumElements(); ++i) {
394 float actual = tensors[3].flat<float>()(i);
397 expected += tensors[j].flat<float>()(i);
/external/tensorflow/tensorflow/c/eager/
H A Dtape.h63 // Operations the tape needs to perform on tensors to do backpropagation. Named
90 // Consumes references to the tensors in the gradient_tensors list and returns
123 // functions (and hence the tensors they keep alive). Instead, everything
146 // once) and produces the gradient of the target tensors with respect to the
147 // source tensors. The output gradients are used if not empty and not
203 std::vector<TapeTensor> tensors; local
204 tensors.reserve(output_tensors.size());
210 tensors.push_back(o);
213 op_type, tensors, ids, backward_function, backward_function_deleter};
233 // Do not delete watched tensors
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