| /frameworks/ml/nn/runtime/ |
| D | ModelBuilder.cpp | 349 int ModelBuilder::addOperation(ANeuralNetworksOperationType type, uint32_t inputCount, in addOperation() argument
380 return getReferencedModel(modelOperand)->inputCount(); in addOperation()
392 type, inputCount, inputs, outputCount, outputs, mOperands, HalVersion::LATEST, in addOperation()
408 .inputs = hidl_vec<uint32_t>(inputs, inputs + inputCount), in addOperation()
420 int ModelBuilder::identifyInputsAndOutputs(uint32_t inputCount, const uint32_t* inputs, in identifyInputsAndOutputs() argument
426 int n = validateOperandList(inputCount, inputs, operandCount(), in identifyInputsAndOutputs()
466 if (!setArguments(&mInputIndexes, inputCount, inputs, OperandLifeTime::SUBGRAPH_INPUT) || in identifyInputsAndOutputs()
566 const uint32_t inputCount = operation.inputs.size(); in removeTrailingArgumentsWithDefaultValues() local
567 CHECK_LT(count, inputCount); in removeTrailingArgumentsWithDefaultValues()
568 const uint32_t newInputCount = inputCount - count; in removeTrailingArgumentsWithDefaultValues()
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| D | ModelBuilder.h | 54 int addOperation(ANeuralNetworksOperationType type, uint32_t inputCount, const uint32_t* inputs,
56 int identifyInputsAndOutputs(uint32_t inputCount, const uint32_t* inputs, uint32_t outputCount,
85 uint32_t inputCount() const { return static_cast<uint32_t>(mInputIndexes.size()); } in inputCount() function
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| D | ExecutionPlan.cpp | 328 const uint32_t inputCount = static_cast<uint32_t>(operation.inputs.size()); in addOperation() local
330 std::vector<uint32_t> inputs(inputCount); in addOperation()
334 return mStepModel.addOperation(static_cast<uint32_t>(operation.type), inputCount, inputs.data(), in addOperation()
506 for (uint32_t i = 0, n = mainModel->inputCount(); i < n; ++i) { in finishStepModel()
666 for (uint32_t i = 0, n = mainModel->inputCount(); i < n; ++i) { in finish()
1764 for (uint32_t i = 0, n = thenModel->inputCount(); i < n; ++i) { in partitionTheWorkInternal()
1773 for (uint32_t i = 0, n = elseModel->inputCount(); i < n; ++i) { in partitionTheWorkInternal()
1825 for (uint32_t i = 0, n = condModel->inputCount(); i < n; ++i) { in partitionTheWorkInternal()
1832 for (uint32_t i = 0, n = bodyModel->inputCount(); i < n; ++i) { in partitionTheWorkInternal()
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| D | CompilationBuilder.cpp | 222 if (index >= mModel->inputCount()) { in forEachStepRoleOfInput()
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| D | NeuralNetworks.cpp | 1112 ANeuralNetworksOperationType type, uint32_t inputCount, in ANeuralNetworksModel_addOperation() argument
1121 return m->addOperation(type, inputCount, inputs, outputCount, outputs); in ANeuralNetworksModel_addOperation()
1137 int ANeuralNetworksModel_identifyInputsAndOutputs(ANeuralNetworksModel* model, uint32_t inputCount, in ANeuralNetworksModel_identifyInputsAndOutputs() argument
1146 return m->identifyInputsAndOutputs(inputCount, inputs, outputCount, outputs); in ANeuralNetworksModel_identifyInputsAndOutputs()
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| D | ExecutionBuilder.cpp | 95 mInputs(mModel->inputCount()), in ExecutionBuilder()
986 mInputs(model->inputCount()), in StepExecutor()
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| D | Memory.cpp | 354 if (index >= model->inputCount()) { in addRole()
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| /frameworks/ml/nn/common/operations/ |
| D | Concatenation.cpp | 95 uint32_t inputCount = context->getNumInputs() - 1; in concatenation() local
98 for (uint32_t i = 0; i < inputCount; ++i) { in concatenation()
104 return concatenation(inputDatas, inputShapes, context->getInputValue<int32_t>(inputCount), in concatenation()
111 uint32_t inputCount = context->getNumInputs() - 1; in concatenation() local
112 std::vector<std::vector<uint8_t>> inputs_uint8(inputCount); in concatenation()
113 for (int i = 0; i < inputCount; ++i) { in concatenation()
122 for (uint32_t i = 0; i < inputCount; ++i) { in concatenation()
131 NN_RET_CHECK(concatenation(inputDatas, inputShapes, context->getInputValue<int32_t>(inputCount), in concatenation()
142 uint32_t inputCount = context->getNumInputs(); in validate() local
143 NN_RET_CHECK_GE(inputCount, 2); in validate()
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| D | Pooling.cpp | 295 auto inputCount = context->getNumInputs(); in validate() local
296 NN_RET_CHECK(inputCount == 11 || inputCount == 10 || inputCount == 8 || inputCount == 7); in validate()
341 if (inputCount >= 10) { in validate()
346 if (inputCount == 11 || inputCount == 8) { in validate()
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| D | Conv2D.cpp | 545 auto inputCount = context->getNumInputs(); in validate() local
594 if (inputCount >= 8) { in validate()
595 if (context->getInputType(7) == OperandType::INT32 && inputCount >= 10) { in validate()
602 if (inputCount >= 8 + inputOffset) { in validate()
606 NN_RET_CHECK_NE(inputCount, 9 + inputOffset) in validate()
609 if (inputCount == 10 + inputOffset) { in validate()
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| D | TransposeConv2D.cpp | 440 const uint32_t inputCount = context->getNumInputs(); in validate() local
441 NN_RET_CHECK(inputCount == kNumInputs1 || inputCount == kNumInputs2); in validate()
469 if (inputCount == 11) { in validate()
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| /frameworks/ml/nn/common/ |
| D | Utils.cpp | 196 OperationValidationContext(const char* operationName, uint32_t inputCount, in OperationValidationContext() argument
201 inputCount(inputCount), in OperationValidationContext()
225 uint32_t inputCount; member in android::nn::__anon8d54713c0111::OperationValidationContext
242 CHECK(index < static_cast<uint32_t>(inputCount)); in getInputOperand()
252 return inputCount; in getNumInputs()
730 static bool validateIfOperation(uint32_t inputCount, const uint32_t* inputs, uint32_t outputCount, in validateIfOperation() argument
735 NN_RET_CHECK_GE(inputCount, 3u) << "ANEURALNETWORKS_IF must have at least 3 inputs"; in validateIfOperation()
742 NN_RET_CHECK_EQ(inputCount, op::kFirstInput + branchModelInputCount); in validateIfOperation()
774 static bool validateWhileOperation(uint32_t inputCount, const uint32_t* inputs, in validateWhileOperation() argument
788 NN_RET_CHECK_GE(inputCount, 3u) << "ANEURALNETWORKS_WHILE must have at least 3 inputs"; in validateWhileOperation()
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| /frameworks/ml/nn/runtime/test/ |
| D | TestPartitioningRandom.cpp | 158 uint32_t inputCount() const { return builder()->inputCount(); } in inputCount() function in android::__anonbe695bce0111::TestModel
434 const uint32_t inputCount = stats.mBuilder->inputCount(); in operator <<() local
437 << ", operandCount = " << operandCount << ", inputCount = " << inputCount << " (" in operator <<()
438 << (double(inputCount) / operandCount) << ")" in operator <<()
1246 std::vector<float> goldenInputs(problemSize * problemSize * model.inputCount()); in TEST_P()
1271 std::vector<InputOutputDescriptor> ioDescriptors(model.inputCount() + model.outputCount()); in TEST_P()
1273 ioDescriptors[i].mKind = (i < model.inputCount() ? InputOutputDescriptor::INPUT in TEST_P()
1341 CHECK(inputIndex == model.inputCount()); in TEST_P()
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| D | TestPartitioning.cpp | 1131 ASSERT_LT(model->inputCount(), kPseudoDefiningOperationRange); in buildDefinitionMap()
1132 for (uint32_t i = 0, e = model->inputCount(); i < e; i++) { in buildDefinitionMap()
1247 modelA->inputCount() != modelB->inputCount() || in compare()
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| /frameworks/ml/nn/runtime/include/ |
| D | NeuralNetworks.h | 7375 ANeuralNetworksOperationType type, uint32_t inputCount,
7403 int ANeuralNetworksModel_identifyInputsAndOutputs(ANeuralNetworksModel* model, uint32_t inputCount,
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| /frameworks/ml/nn/extensions/ |
| D | README.md | 153 CHECK_EQ(ANeuralNetworksModel_addOperation(model, type, inputCount, inputs, outputCount, outputs),
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| /frameworks/ml/nn/common/include/ |
| D | Utils.h | 406 int validateOperation(ANeuralNetworksOperationType opType, uint32_t inputCount,
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| /frameworks/ml/nn/tools/api/ |
| D | NeuralNetworks.t | 1783 * @param inputCount The number of entries in the inputs array.
1801 ANeuralNetworksOperationType type, uint32_t inputCount,
1813 * @param inputCount The number of entries in the inputs array.
1829 int ANeuralNetworksModel_identifyInputsAndOutputs(ANeuralNetworksModel* model, uint32_t inputCount,
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