| /packages/modules/NeuralNetworks/shim_and_sl/ |
| D | ShimConverter.cpp | 62 const auto& subgraph = subgraphIndex == 0 ? model.main : model.referenced[subgraphIndex - 1]; in convertSubgraphFromHAL() local
76 for (int i = 0; i < subgraph.operands.size(); ++i) { in convertSubgraphFromHAL()
77 const auto& operand = subgraph.operands[i]; in convertSubgraphFromHAL()
168 auto subgraph = convertSubgraphFromHAL(nnapi, memoryPools, model, allModels, in convertSubgraphFromHAL() local
171 if (subgraph) { in convertSubgraphFromHAL()
172 resultModel.setOperandValueFromModel(i, subgraph); in convertSubgraphFromHAL()
202 for (int i = 0; i < subgraph.operations.size(); ++i) { in convertSubgraphFromHAL()
203 const auto& operation = subgraph.operations[i]; in convertSubgraphFromHAL()
238 std::vector<uint32_t> inputIndexes(subgraph.inputIndexes.begin(), subgraph.inputIndexes.end()); in convertSubgraphFromHAL()
239 std::vector<uint32_t> outputIndexes(subgraph.outputIndexes.begin(), in convertSubgraphFromHAL()
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| /packages/modules/NeuralNetworks/runtime/ |
| D | ModelArchHasher.cpp | 33 bool updateSubgraph(SHA256_CTX* hasher, const Model::Subgraph& subgraph) { in updateSubgraph() argument
35 for (auto& operand : subgraph.operands) { in updateSubgraph()
49 for (auto& operation : subgraph.operations) { in updateSubgraph()
60 hasher, static_cast<const void*>(subgraph.inputIndexes.data()), in updateSubgraph()
61 sizeof(decltype(subgraph.inputIndexes)::value_type) * subgraph.inputIndexes.size()); in updateSubgraph()
63 hasher, static_cast<const void*>(subgraph.outputIndexes.data()), in updateSubgraph()
64 sizeof(decltype(subgraph.outputIndexes)::value_type) * subgraph.outputIndexes.size()); in updateSubgraph()
78 for (auto& subgraph : model.referenced) { in calcModelArchHash() local
79 success &= updateSubgraph(&mHasher, subgraph); in calcModelArchHash()
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| D | FlatbufferModelBuilder.cpp | 84 const Model::Subgraph& subgraph) { in createSubGraphFlatbuffer() argument
86 NN_TRY(checkAllTensorOperandsHaveSpecifiedRank(subgraph.operands)); in createSubGraphFlatbuffer()
88 NN_TRY(checkNoSubgraphOutputOperandsHaveDynamicShape(subgraph.operands)); in createSubGraphFlatbuffer()
90 SubGraphContext context(&mModel, &subgraph, &mBuilder, &mOpCodesVector, in createSubGraphFlatbuffer()
92 for (const Operation& operation : subgraph.operations) { in createSubGraphFlatbuffer()
101 for (uint32_t idx : subgraph.inputIndexes) { in createSubGraphFlatbuffer()
104 for (uint32_t idx : subgraph.outputIndexes) { in createSubGraphFlatbuffer()
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| D | ModelBuilder.cpp | 906 void updateOperandLocations(const ModelBuilder* refModel, Model::Subgraph* subgraph);
951 Model::Subgraph subgraph; in makeSubgraph() local
952 subgraph.operands = model->mOperands; in makeSubgraph()
953 subgraph.operations = model->mOperations; in makeSubgraph()
954 subgraph.inputIndexes = model->mInputIndexes; in makeSubgraph()
955 subgraph.outputIndexes = model->mOutputIndexes; in makeSubgraph()
956 return subgraph; in makeSubgraph()
960 Model::Subgraph* subgraph) { in updateOperandLocations() argument
961 for (Operand& operand : subgraph->operands) { in updateOperandLocations()
973 for (Operand& operand : subgraph->operands) { in updateOperandLocations()
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| /packages/modules/NeuralNetworks/driver/sample_hidl/ |
| D | SampleDriverFloatXNNPACK.cpp | 109 const V1_3::Subgraph& subgraph, const std::vector<RunTimePoolInfo>& modelPoolInfos, in initializeRunTimeInfo() argument
111 const size_t count = subgraph.operands.size(); in initializeRunTimeInfo()
114 const V1_3::Operand& from = subgraph.operands[i]; in initializeRunTimeInfo()
175 std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> subgraph( in Create() local
245 subgraph.get(), xnn_datatype_fp32, dims.size(), dims.data(), data, in Create()
255 if (VisitNode(subgraph.get(), operation, operands.data(), xnnpackTensors) != in Create()
263 status = xnn_create_runtime_v2(subgraph.get(), threadpool, /*flags=*/0, &runtimePtr); in Create()
496 static V1_3::ErrorStatus VisitNode(xnn_subgraph_t subgraph, const V1_3::Operation& operation, in VisitNode() argument
501 return VisitAbsNode(subgraph, operation, operands, xnnpackTensors); in VisitNode()
503 return VisitAddNode(subgraph, operation, operands, xnnpackTensors); in VisitNode()
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| /packages/modules/NeuralNetworks/runtime/operation_converters/ |
| D | DepthwiseConv2DOperationConverter.cpp | 29 const Model::Subgraph* subgraph = context->getSubgraph(); in convert() local
38 subgraph->operands[operation.inputs[8]].type == OperandType::BOOL); in convert()
53 const Operand& paddingTypeOperand = subgraph->operands[operation.inputs[3]]; in convert()
65 subgraph->operands[operation.inputs[baseOptionsIdx + kStrideWOffset]]; in convert()
67 subgraph->operands[operation.inputs[baseOptionsIdx + kStrideHOffset]]; in convert()
69 subgraph->operands[operation.inputs[baseOptionsIdx + kActivationOffset]]; in convert()
71 subgraph->operands[operation.inputs[baseOptionsIdx + kDepthwiseMultiplier]]; in convert()
87 const Operand& isNchwOperand = subgraph->operands[operation.inputs[isNchwIdx]]; in convert()
101 const Operand& dilationWOperand = subgraph->operands[operation.inputs[dilationWIdx]]; in convert()
107 const Operand& dilationHOperand = subgraph->operands[operation.inputs[dilationHIdx]]; in convert()
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| D | Conv2DOperationConverter.cpp | 54 const Model::Subgraph* subgraph = context->getSubgraph(); in decomposeExplicitPadding() local
55 const Operand& inputOperand = subgraph->operands[operation.inputs[0]]; in decomposeExplicitPadding()
64 const Operand& frontWidthPaddingOperand = subgraph->operands[operation.inputs[3]]; in decomposeExplicitPadding()
65 const Operand& backWidthPaddingOperand = subgraph->operands[operation.inputs[4]]; in decomposeExplicitPadding()
66 const Operand& frontHeightPaddingOperand = subgraph->operands[operation.inputs[5]]; in decomposeExplicitPadding()
67 const Operand& backHeightPaddingOperand = subgraph->operands[operation.inputs[6]]; in decomposeExplicitPadding()
145 const Model::Subgraph* subgraph = context->getSubgraph(); in convert() local
154 subgraph->operands[operation.inputs[7]].type == OperandType::BOOL) { in convert()
171 const Operand& paddingTypeOperand = subgraph->operands[operation.inputs[3]]; in convert()
183 subgraph->operands[operation.inputs[baseOptionsIdx + kStrideWOffset]]; in convert()
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| D | SubGraphContext.cpp | 28 SubGraphContext::SubGraphContext(const Model* model, const Model::Subgraph* subgraph, in SubGraphContext() argument
34 mSubgraph(subgraph), in SubGraphContext()
40 CHECK(subgraph != nullptr); in SubGraphContext()
45 mOperandToTensorIdx.resize(subgraph->operands.size(), -1); in SubGraphContext()
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| D | AddOperationConverter.cpp | 29 const Model::Subgraph* subgraph = context->getSubgraph(); in convert() local
41 subgraph->operands[operation.inputs[baseOptionsIdx + kActivationOffset]]; in convert()
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| /packages/modules/NeuralNetworks/common/ |
| D | ModelUtils.cpp | 144 void identifyUsedPools(const Model::Subgraph& subgraph, std::vector<bool>* used) { in identifyUsedPools() argument
146 for (const auto& operand : subgraph.operands) { in identifyUsedPools()
158 for (const auto& subgraph : model.referenced) { in identifyUsedPools() local
159 identifyUsedPools(subgraph, &used); in identifyUsedPools()
220 for (auto& subgraph : model->referenced) { in fixOperandDataLocations() local
221 fixOperandDataLocations(&subgraph.operands, &model->operandValues, operandValues, in fixOperandDataLocations()
237 const auto collectPrefixes = [collectPrefix](const Model::Subgraph& subgraph) { in identifyUsedExtensions() argument
238 std::for_each(subgraph.operands.begin(), subgraph.operands.end(), collectPrefix); in identifyUsedExtensions()
239 std::for_each(subgraph.operations.begin(), subgraph.operations.end(), collectPrefix); in identifyUsedExtensions()
243 for (const auto& subgraph : model.referenced) { in identifyUsedExtensions() local
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| D | ValidateHal.cpp | 476 const Model::Subgraph& subgraph = *getSubgraph(modelOperand); in validateOperations() local
477 CHECK_LT(subgraph.inputIndexes[index], subgraph.operands.size()); in validateOperations()
478 return &subgraph.operands[subgraph.inputIndexes[index]]; in validateOperations()
482 const Model::Subgraph& subgraph = *getSubgraph(modelOperand); in validateOperations() local
483 CHECK_LT(subgraph.outputIndexes[index], subgraph.operands.size()); in validateOperations()
484 return &subgraph.operands[subgraph.outputIndexes[index]]; in validateOperations()
675 static bool checkNoReferenceCycles(const V1_3::Model& model, const V1_3::Subgraph& subgraph, in checkNoReferenceCycles() argument
677 auto [_, isNew] = path->insert(&subgraph); in checkNoReferenceCycles()
682 for (const V1_3::Operand& operand : subgraph.operands) { in checkNoReferenceCycles()
690 path->erase(&subgraph); in checkNoReferenceCycles()
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| /packages/modules/NeuralNetworks/tools/test_generator/test_harness/include/ |
| D | TestHarness.h | 346 for (const TestSubgraph& subgraph : referenced) { in forEachSubgraph() local
347 handler(subgraph); in forEachSubgraph()
353 for (TestSubgraph& subgraph : referenced) { in forEachSubgraph()
354 handler(subgraph); in forEachSubgraph()
361 newTestModel.forEachSubgraph([](TestSubgraph& subgraph) { in copy()
362 for (TestOperand& operand : subgraph.operands) { in copy()
373 forEachSubgraph([&result](const TestSubgraph& subgraph) { in hasQuant8CoupledOperands()
377 for (const TestOperation& operation : subgraph.operations) { in hasQuant8CoupledOperands()
402 if (subgraph.operands[operandIndex].type == in hasQuant8CoupledOperands()
409 if (subgraph.operands[operandIndex].type == in hasQuant8CoupledOperands()
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| /packages/modules/NeuralNetworks/tools/test_generator/ |
| D | example_generator.py | 131 def GetSubgraphStruct(subgraph): argument
134 COMMENT_KEY: subgraph.name,
135 "operands": [GetOperandStruct(op) for op in subgraph.operands],
136 "operations": [GetOperationStruct(op) for op in subgraph.operations],
137 "inputIndexes": [op.model_index for op in subgraph.GetInputs()],
138 "outputIndexes": [op.model_index for op in subgraph.GetOutputs()],
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| /packages/modules/NeuralNetworks/common/types/src/ |
| D | SharedMemory.cpp | 36 bool hasNoPointerData(const Model::Subgraph& subgraph);
53 bool hasNoPointerData(const Model::Subgraph& subgraph) { in hasNoPointerData() argument
54 return hasNoPointerData(subgraph.operands); in hasNoPointerData()
76 void copyPointersToSharedMemory(Model::Subgraph* subgraph, ConstantMemoryBuilder* memoryBuilder) { in copyPointersToSharedMemory() argument
77 CHECK(subgraph != nullptr); in copyPointersToSharedMemory()
78 std::for_each(subgraph->operands.begin(), subgraph->operands.end(), in copyPointersToSharedMemory()
165 [&memoryBuilder](auto& subgraph) { in flushDataFromPointerToShared() argument
166 copyPointersToSharedMemory(&subgraph, &memoryBuilder); in flushDataFromPointerToShared()
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| D | Validation.cpp | 348 Result<Version> validateModelSubgraph(const Model::Subgraph& subgraph,
782 Result<void> validateExecutionOrder(const Model::Subgraph& subgraph) { in validateExecutionOrder() argument
786 operandValueKnown.reserve(subgraph.operands.size()); in validateExecutionOrder()
787 std::transform(subgraph.operands.begin(), subgraph.operands.end(), in validateExecutionOrder()
798 for (size_t i = 0; i < subgraph.operations.size(); ++i) { in validateExecutionOrder()
799 const auto& operation = subgraph.operations[i]; in validateExecutionOrder()
821 for (size_t i = 0; i < subgraph.operands.size(); ++i) { in validateExecutionOrder()
837 Result<Version> validateModelSubgraph(const Model::Subgraph& subgraph, in validateModelSubgraph() argument
853 NN_RET_CHECK(!subgraph.operands.empty()); in validateModelSubgraph()
854 NN_RET_CHECK(!subgraph.operations.empty()); in validateModelSubgraph()
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| /packages/modules/NeuralNetworks/runtime/test/ |
| D | GeneratedTestUtils.cpp | 116 auto processSubgraph = [&size](const TestSubgraph& subgraph) { argument
117 for (const TestOperand& operand : subgraph.operands) {
125 for (const TestSubgraph& subgraph : testModel.referenced) { local
126 processSubgraph(subgraph);
135 static void createModelFromSubgraph(const TestSubgraph& subgraph, bool testDynamicOutputShape, argument
140 for (const auto& operand : subgraph.operands) {
180 for (const auto& operation : subgraph.operations) {
185 model->identifyInputsAndOutputs(subgraph.inputIndexes, subgraph.outputIndexes);
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| /packages/modules/NeuralNetworks/runtime/test/android_fuzzing/ |
| D | Converter.cpp | 155 TestSubgraph convert(const Subgraph& subgraph) { in convert() argument
156 std::vector<TestOperand> operands = convert(subgraph.operands()); in convert()
157 std::vector<TestOperation> operations = convert(subgraph.operations()); in convert()
158 std::vector<uint32_t> inputIndexes = convert(subgraph.input_indexes()); in convert()
159 std::vector<uint32_t> outputIndexes = convert(subgraph.output_indexes()); in convert()
173 const auto& repeatedSubgraph = subgraphs.subgraph(); in convert()
176 [](const auto& subgraph) { return convert(subgraph); }); in convert() argument
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| D | GenerateCorpus.cpp | 138 Subgraph convert(const TestSubgraph& subgraph) { in convert() argument
140 *protoSubgraph.mutable_operands() = convert(subgraph.operands); in convert()
141 *protoSubgraph.mutable_operations() = convert(subgraph.operations); in convert()
142 *protoSubgraph.mutable_input_indexes() = convertIndexes(subgraph.inputIndexes); in convert()
143 *protoSubgraph.mutable_output_indexes() = convertIndexes(subgraph.outputIndexes); in convert()
149 for (const auto& subgraph : subgraphs) { in convert() local
150 *protoSubgraphs.add_subgraph() = convert(subgraph); in convert()
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| D | FuzzHarness.cpp | 44 bool hasOperandThatOverflows(const TestSubgraph& subgraph) { in hasOperandThatOverflows() argument
45 return std::any_of(subgraph.operands.begin(), subgraph.operands.end(), operandOverflows); in hasOperandThatOverflows()
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| D | FuzzTest.cpp | 67 const auto& subgraph = index == 0 ? testModel.main : testModel.referenced[index - 1]; in areSubgraphsAcyclic() local
68 for (const auto& operand : subgraph.operands) { in areSubgraphsAcyclic()
149 auto subgraph = CreateSubgraph(testModel, index, subgraphs); in CreateModels() local
150 if (!subgraph.has_value()) return std::nullopt; in CreateModels()
151 subgraphs[index] = std::move(subgraph).value(); in CreateModels()
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| /packages/modules/NeuralNetworks/runtime/test/android_fuzzing/corpus/ |
| D | seed196 | 129 subgraph {
226 subgraph {
457 subgraph {
554 subgraph {
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| D | seed160 | 180 subgraph {
277 subgraph {
508 subgraph {
605 subgraph {
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| /packages/modules/NeuralNetworks/runtime/test/android_fuzzing/corpus_additional/ |
| D | seed321 | 135 subgraph {
236 subgraph {
531 subgraph {
632 subgraph {
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| D | seed452 | 135 subgraph {
236 subgraph {
531 subgraph {
632 subgraph {
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| D | seed471 | 98 subgraph {
177 subgraph {
|