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/hardware/qcom/neuralnetworks/hvxservice/1.0/
DHexagonModel.cpp261 static bool verifyOperationInputs(const std::vector<hexagon_nn_input>& inputs) { in verifyOperationInputs() argument
262 for (const hexagon_nn_input& input : inputs) { in verifyOperationInputs()
280 const std::vector<hexagon_nn_input>& inputs, in addOperationInternal() argument
282 HEXAGON_SOFT_ASSERT(verifyOperationInputs(inputs), in addOperationInternal()
287 return hexagon::Controller::getInstance().append_node(mGraphId, node, op, pad, inputs.data(), in addOperationInternal()
288 inputs.size(), outputs.data(), in addOperationInternal()
323 const std::vector<hexagon_nn_input>& inputs, in addBasicOperation() argument
326 uint32_t node = addOperationInternal(op, pad, inputs, outs); in addBasicOperation()
354 const std::vector<hexagon_nn_input>& inputs, in addFloatOperationWithActivation() argument
359 uint32_t node = addOperationInternal(op, pad, inputs, outs); in addFloatOperationWithActivation()
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DHexagonModel.h114 const std::vector<hexagon_nn_input>& inputs,
118 const std::vector<hexagon_nn_input>& inputs,
122 const std::vector<hexagon_nn_input>& inputs,
126 const std::vector<hexagon_nn_input>& inputs,
130 const std::vector<hexagon_nn_input>& inputs,
140 const std::vector<hexagon_nn_input>& inputs,
DHexagonController.cpp127 hexagon_nn_padding_type padding, const hexagon_nn_input* inputs, in append_node() argument
130 CONTROLLER_CHECK(append_node, id, node_id, operation, padding, inputs, num_inputs, outputs, in append_node()
140 int Controller::execute_new(hexagon_nn_nn_id id, const hexagon_nn_tensordef* inputs, in execute_new() argument
142 CONTROLLER_CHECK(execute_new, id, inputs, n_inputs, outputs, n_outputs); in execute_new()
DHexagonController.h70 hexagon_nn_padding_type padding, const hexagon_nn_input* inputs,
76 int execute_new(hexagon_nn_nn_id id, const hexagon_nn_tensordef* inputs, uint32_t n_inputs,
/hardware/interfaces/neuralnetworks/1.3/vts/functional/
DValidateModel.cpp243 size += sizeForBinder(operation.inputs); in sizeForBinder()
338 for (uint32_t input : operationObj.inputs) { in mutateExecutionOrderTest()
734 for (uint32_t input : newOperation.inputs) { in mutateOperandAddWriterTest()
854 if (operand == operation.inputs[1]) { in mutateOperationOperandTypeSkip()
868 if (operand == operation.inputs[0] && in mutateOperationOperandTypeSkip()
879 if (operand == operation.inputs[0] && in mutateOperationOperandTypeSkip()
885 if (operand == operation.inputs[0] && in mutateOperationOperandTypeSkip()
901 if (operand == operation.inputs[1] && in mutateOperationOperandTypeSkip()
908 if (operand == operation.inputs[1] && in mutateOperationOperandTypeSkip()
915 if (operand == operation.inputs[0] && in mutateOperationOperandTypeSkip()
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DMemoryDomainTests.cpp138 std::vector<uint32_t> inputs(operands.size() - 1); in createConvModel() local
139 std::iota(inputs.begin(), inputs.end(), inputIndex); in createConvModel()
141 .inputs = std::move(inputs), in createConvModel()
181 .inputs = {0, 1, 2}, in createSingleAddModel()
966 {.inputs = {deviceMemoryArg}, in TEST_P()
971 {.inputs = {deviceMemoryArg}, in TEST_P()
976 {.inputs = {sharedMemoryArg}, in TEST_P()
981 {.inputs = {sharedMemoryArg}, in TEST_P()
1003 {.inputs = {deviceMemoryArg}, in TEST_P()
1008 {.inputs = {sharedMemoryArg}, in TEST_P()
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DBasicTests.cpp163 {.type = OperationType::ADD, .inputs = {0, 4, 2}, .outputs = {3}}, in TEST_P()
164 {.type = OperationType::ADD, .inputs = {1, 3, 2}, .outputs = {4}}, in TEST_P()
165 {.type = OperationType::ADD, .inputs = {4, 0, 2}, .outputs = {5}}, in TEST_P()
DGeneratedTestHarness.cpp247 .inputs = op.inputs, in createSubgraph()
372 hidl_vec<RequestArgument> inputs(testModel.main.inputIndexes.size()); in createRequest() local
378 inputs[i] = {.hasNoValue = true}; in createRequest()
388 inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}}; in createRequest()
398 inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}}; in createRequest()
459 if (!inputs[i].hasNoValue && inputs[i].location.poolIndex == kInputPoolIndex) { in createRequest()
463 std::copy(begin, end, inputPtr + inputs[i].location.offset); in createRequest()
467 .inputs = std::move(inputs), .outputs = std::move(outputs), .pools = std::move(pools)}; in createRequest()
/hardware/interfaces/neuralnetworks/1.2/vts/functional/
DValidateModel.cpp236 size += sizeForBinder(operation.inputs); in sizeForBinder()
321 for (uint32_t input : operationObj.inputs) { in mutateExecutionOrderTest()
706 for (uint32_t input : newOperation.inputs) { in mutateOperandAddWriterTest()
823 if (operand == operation.inputs[1]) { in mutateOperationOperandTypeSkip()
837 if (operand == operation.inputs[0] && in mutateOperationOperandTypeSkip()
843 if (operand == operation.inputs[0] && in mutateOperationOperandTypeSkip()
858 if (operand == operation.inputs[1] && in mutateOperationOperandTypeSkip()
916 for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) { in mutateOperationInputOperandIndexTest()
922 model->operations[operation].inputs[input] = invalidOperand; in mutateOperationInputOperandIndexTest()
993 removeValueAndDecrementGreaterValues(&operation.inputs, index); in removeOperand()
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DBasicTests.cpp222 {.type = OperationType::ADD, .inputs = {0, 4, 2}, .outputs = {3}}, in TEST_P()
223 {.type = OperationType::ADD, .inputs = {1, 3, 2}, .outputs = {4}}, in TEST_P()
224 {.type = OperationType::ADD, .inputs = {4, 0, 2}, .outputs = {5}}, in TEST_P()
DValidateRequest.cpp134 for (size_t input = 0; input < request.inputs.size(); ++input) { in removeInputTest()
137 [input](Request* request) { hidl_vec_removeAt(&request->inputs, input); }); in removeInputTest()
/hardware/libhardware_legacy/audio/
Daudio_policy.conf37 inputs {
55 inputs {
/hardware/interfaces/neuralnetworks/1.0/vts/functional/
DUtils.cpp106 hidl_vec<RequestArgument> inputs(testModel.main.inputIndexes.size()); in createRequest() local
112 inputs[i] = {.hasNoValue = true}; in createRequest()
118 inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}}; in createRequest()
162 std::copy(begin, end, inputPtr + inputs[i].location.offset); in createRequest()
166 return {.inputs = std::move(inputs), .outputs = std::move(outputs), .pools = std::move(pools)}; in createRequest()
DBasicTests.cpp141 {.type = OperationType::ADD, .inputs = {0, 4, 2}, .outputs = {3}}, in TEST_P()
142 {.type = OperationType::ADD, .inputs = {1, 3, 2}, .outputs = {4}}, in TEST_P()
143 {.type = OperationType::ADD, .inputs = {4, 0, 2}, .outputs = {5}}, in TEST_P()
DValidateModel.cpp189 size += sizeForBinder(operation.inputs); in sizeForBinder()
262 for (uint32_t input : operationObj.inputs) { in mutateExecutionOrderTest()
609 for (uint32_t input : newOperation.inputs) { in mutateOperandAddWriterTest()
684 if (operation.type == OperationType::LSH_PROJECTION && operand == operation.inputs[1]) { in mutateOperationOperandTypeSkip()
741 for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) { in mutateOperationInputOperandIndexTest()
746 model->operations[operation].inputs[input] = invalidOperand; in mutateOperationInputOperandIndexTest()
812 removeValueAndDecrementGreaterValues(&operation.inputs, index); in removeOperand()
830 for (uint32_t operand : model->operations[index].inputs) { in removeOperation()
848 for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) { in removeOperationInputTest()
853 if (op.type == OperationType::CONCATENATION && op.inputs.size() > 2 && in removeOperationInputTest()
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DValidateRequest.cpp73 for (size_t input = 0; input < request.inputs.size(); ++input) { in removeInputTest()
76 [input](Request* request) { hidl_vec_removeAt(&request->inputs, input); }); in removeInputTest()
/hardware/interfaces/neuralnetworks/1.1/vts/functional/
DBasicTests.cpp148 {.type = OperationType::ADD, .inputs = {0, 4, 2}, .outputs = {3}}, in TEST_P()
149 {.type = OperationType::ADD, .inputs = {1, 3, 2}, .outputs = {4}}, in TEST_P()
150 {.type = OperationType::ADD, .inputs = {4, 0, 2}, .outputs = {5}}, in TEST_P()
DValidateRequest.cpp57 for (size_t input = 0; input < request.inputs.size(); ++input) { in removeInputTest()
60 [input](Request* request) { hidl_vec_removeAt(&request->inputs, input); }); in removeInputTest()
DValidateModel.cpp208 size += sizeForBinder(operation.inputs); in sizeForBinder()
282 for (uint32_t input : operationObj.inputs) { in mutateExecutionOrderTest()
638 for (uint32_t input : newOperation.inputs) { in mutateOperandAddWriterTest()
716 if (operation.type == OperationType::LSH_PROJECTION && operand == operation.inputs[1]) { in mutateOperationOperandTypeSkip()
775 for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) { in mutateOperationInputOperandIndexTest()
781 model->operations[operation].inputs[input] = invalidOperand; in mutateOperationInputOperandIndexTest()
852 removeValueAndDecrementGreaterValues(&operation.inputs, index); in removeOperand()
870 for (uint32_t operand : model->operations[index].inputs) { in removeOperation()
889 for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) { in removeOperationInputTest()
894 if (op.type == OperationType::CONCATENATION && op.inputs.size() > 2 && in removeOperationInputTest()
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/hardware/qcom/neuralnetworks/hvxservice/1.0/hexagon_nn_controller/
Dhexagon_nn_controller.h88 const hexagon_nn_input* inputs, unsigned int num_inputs, const hexagon_nn_output* outputs,
98 const hexagon_nn_tensordef* inputs,
/hardware/interfaces/neuralnetworks/1.2/
DIPreparedModel.hal35 * execute_1_2 must verify the inputs to the function are correct. If there is
38 * the inputs to the function are valid and there is no error, execute_1_2 must
55 * 'request' inputs.
58 * operands have fully specified dimensions, and the inputs to the function
96 * executeSynchronously must verify the inputs to the function are
98 * return with the appropriate ErrorStatus value. If the inputs to the
107 * data objects corresponding to 'request' inputs.
110 * operands have fully specified dimensions, and the inputs to the function
169 * corresponding to Request inputs. requestChannel
/hardware/interfaces/neuralnetworks/1.0/
DIPreparedModel.hal30 * execute must verify the inputs to the function are correct. If there is
33 * the inputs to the function are valid and there is no error, execute must
50 * 'request' inputs.
53 * operands have fully specified dimensions, and the inputs to the function
DIDevice.hal70 * prepareModel function must verify the inputs to the prepareModel function
73 * IPreparedModel, then return with the same ErrorStatus. If the inputs to
93 * inputs to the model. Note that the same prepared model object can be
94 * used with different shapes of inputs on different (possibly concurrent)
/hardware/interfaces/neuralnetworks/1.3/
DIPreparedModel.hal39 * execute_1_3 must verify the inputs to the function are correct, and the usages
43 * the inputs to the function are valid and there is no error, execute_1_3 must
60 * 'request' inputs.
63 * operands have fully specified dimensions, and the inputs to the function
126 * executeSynchronously_1_3 must verify the inputs to the function are
129 * return with the appropriate ErrorStatus value. If the inputs to the
138 * data objects corresponding to 'request' inputs.
141 * operands have fully specified dimensions, and the inputs to the function
209 * executeFenced must verify the inputs to the function are correct, and the usages
212 * handle for syncFence, and nullptr for callback. If the inputs to the function
/hardware/interfaces/neuralnetworks/1.1/
DIDevice.hal75 * prepareModel function must verify the inputs to the prepareModel function
78 * IPreparedModel, then return with the same ErrorStatus. If the inputs to
98 * inputs to the model. Note that the same prepared model object can be
99 * used with different shapes of inputs on different (possibly concurrent)

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