Loading neuralnetworks/1.0/IDevice.hal +6 −4 Original line number Original line Diff line number Diff line Loading @@ -22,11 +22,13 @@ import IEvent; import IPreparedModel; import IPreparedModel; interface IDevice { interface IDevice { initialize() generates(Capabilities capabilities); getCapabilities() generates (ErrorStatus status, Capabilities capabilities); getSupportedSubgraph(Model model) generates(vec<bool> supported); getSupportedOperations(Model model) generates (ErrorStatus status, vec<bool> supportedOperations); prepareModel(Model model, IEvent event) generates(IPreparedModel preparedModel); prepareModel(Model model, IEvent event) generates (ErrorStatus status, IPreparedModel preparedModel); getStatus() generates (DeviceStatus status); getStatus() generates (DeviceStatus status); }; }; neuralnetworks/1.0/IEvent.hal +1 −1 Original line number Original line Diff line number Diff line Loading @@ -44,6 +44,6 @@ interface IEvent { * @param status Status of the execution associated with the Event. * @param status Status of the execution associated with the Event. * Should be SUCCESS or ERROR. * Should be SUCCESS or ERROR. */ */ oneway notify(Status status); oneway notify(ErrorStatus status); }; }; neuralnetworks/1.0/IPreparedModel.hal +1 −1 Original line number Original line Diff line number Diff line Loading @@ -22,5 +22,5 @@ import IEvent; interface IPreparedModel { interface IPreparedModel { // Multiple threads can call this execute function concurrently. // Multiple threads can call this execute function concurrently. execute(Request request, IEvent event) generates(bool success); execute(Request request, IEvent event) generates (ErrorStatus status); }; }; neuralnetworks/1.0/types.hal +13 −14 Original line number Original line Diff line number Diff line Loading @@ -22,18 +22,14 @@ package android.hardware.neuralnetworks@1.0; // These values are the same as found in the NeuralNetworks.h file. // These values are the same as found in the NeuralNetworks.h file. // When modifying, be sure to update HAL_NUM_OPERAND_TYPES in HalIntefaces.h. // When modifying, be sure to update HAL_NUM_OPERAND_TYPES in HalIntefaces.h. enum OperandType : uint32_t { enum OperandType : uint32_t { FLOAT16 = 0, OEM = 0, FLOAT32 = 1, FLOAT32 = 1, INT8 = 2, INT32 = 2, // TODO: is this needed? UINT8 = 3, UINT32 = 3, INT16 = 4, TENSOR_OEM_BYTE = 4, UINT16 = 5, TENSOR_FLOAT32 = 5, INT32 = 6, TENSOR_INT32 = 6, UINT32 = 7, TENSOR_QUANT8_ASYMM = 7, TENSOR_FLOAT16 = 8, TENSOR_FLOAT32 = 9, TENSOR_INT32 = 10, TENSOR_QUANT8_ASYMM = 11, }; }; // The type of operations. Unlike the operation types found in // The type of operations. Unlike the operation types found in Loading Loading @@ -210,7 +206,10 @@ struct Request { vec<memory> pools; vec<memory> pools; }; }; enum Status : uint32_t { enum ErrorStatus : uint32_t { SUCCESS, NONE, ERROR, DEVICE_UNAVAILABLE, GENERAL_FAILURE, OUTPUT_INSUFFICIENT_SIZE, INVALID_ARGUMENT, }; }; neuralnetworks/1.0/vts/functional/Event.cpp +2 −2 Original line number Original line Diff line number Diff line Loading @@ -21,10 +21,10 @@ Event::~Event() { // thread::join failed: Resource deadlock would occur // thread::join failed: Resource deadlock would occur } } Return<void> Event::notify(ReturnedStatus status) { Return<void> Event::notify(ErrorStatus status) { { { std::lock_guard<std::mutex> lock(mMutex); std::lock_guard<std::mutex> lock(mMutex); mStatus = status == ReturnedStatus::SUCCESS ? Status::SUCCESS : Status::ERROR; mStatus = status == ErrorStatus::NONE ? Status::SUCCESS : Status::ERROR; if (mStatus == Status::SUCCESS && mCallback != nullptr) { if (mStatus == Status::SUCCESS && mCallback != nullptr) { bool success = mCallback(); bool success = mCallback(); if (!success) { if (!success) { Loading Loading
neuralnetworks/1.0/IDevice.hal +6 −4 Original line number Original line Diff line number Diff line Loading @@ -22,11 +22,13 @@ import IEvent; import IPreparedModel; import IPreparedModel; interface IDevice { interface IDevice { initialize() generates(Capabilities capabilities); getCapabilities() generates (ErrorStatus status, Capabilities capabilities); getSupportedSubgraph(Model model) generates(vec<bool> supported); getSupportedOperations(Model model) generates (ErrorStatus status, vec<bool> supportedOperations); prepareModel(Model model, IEvent event) generates(IPreparedModel preparedModel); prepareModel(Model model, IEvent event) generates (ErrorStatus status, IPreparedModel preparedModel); getStatus() generates (DeviceStatus status); getStatus() generates (DeviceStatus status); }; };
neuralnetworks/1.0/IEvent.hal +1 −1 Original line number Original line Diff line number Diff line Loading @@ -44,6 +44,6 @@ interface IEvent { * @param status Status of the execution associated with the Event. * @param status Status of the execution associated with the Event. * Should be SUCCESS or ERROR. * Should be SUCCESS or ERROR. */ */ oneway notify(Status status); oneway notify(ErrorStatus status); }; };
neuralnetworks/1.0/IPreparedModel.hal +1 −1 Original line number Original line Diff line number Diff line Loading @@ -22,5 +22,5 @@ import IEvent; interface IPreparedModel { interface IPreparedModel { // Multiple threads can call this execute function concurrently. // Multiple threads can call this execute function concurrently. execute(Request request, IEvent event) generates(bool success); execute(Request request, IEvent event) generates (ErrorStatus status); }; };
neuralnetworks/1.0/types.hal +13 −14 Original line number Original line Diff line number Diff line Loading @@ -22,18 +22,14 @@ package android.hardware.neuralnetworks@1.0; // These values are the same as found in the NeuralNetworks.h file. // These values are the same as found in the NeuralNetworks.h file. // When modifying, be sure to update HAL_NUM_OPERAND_TYPES in HalIntefaces.h. // When modifying, be sure to update HAL_NUM_OPERAND_TYPES in HalIntefaces.h. enum OperandType : uint32_t { enum OperandType : uint32_t { FLOAT16 = 0, OEM = 0, FLOAT32 = 1, FLOAT32 = 1, INT8 = 2, INT32 = 2, // TODO: is this needed? UINT8 = 3, UINT32 = 3, INT16 = 4, TENSOR_OEM_BYTE = 4, UINT16 = 5, TENSOR_FLOAT32 = 5, INT32 = 6, TENSOR_INT32 = 6, UINT32 = 7, TENSOR_QUANT8_ASYMM = 7, TENSOR_FLOAT16 = 8, TENSOR_FLOAT32 = 9, TENSOR_INT32 = 10, TENSOR_QUANT8_ASYMM = 11, }; }; // The type of operations. Unlike the operation types found in // The type of operations. Unlike the operation types found in Loading Loading @@ -210,7 +206,10 @@ struct Request { vec<memory> pools; vec<memory> pools; }; }; enum Status : uint32_t { enum ErrorStatus : uint32_t { SUCCESS, NONE, ERROR, DEVICE_UNAVAILABLE, GENERAL_FAILURE, OUTPUT_INSUFFICIENT_SIZE, INVALID_ARGUMENT, }; };
neuralnetworks/1.0/vts/functional/Event.cpp +2 −2 Original line number Original line Diff line number Diff line Loading @@ -21,10 +21,10 @@ Event::~Event() { // thread::join failed: Resource deadlock would occur // thread::join failed: Resource deadlock would occur } } Return<void> Event::notify(ReturnedStatus status) { Return<void> Event::notify(ErrorStatus status) { { { std::lock_guard<std::mutex> lock(mMutex); std::lock_guard<std::mutex> lock(mMutex); mStatus = status == ReturnedStatus::SUCCESS ? Status::SUCCESS : Status::ERROR; mStatus = status == ErrorStatus::NONE ? Status::SUCCESS : Status::ERROR; if (mStatus == Status::SUCCESS && mCallback != nullptr) { if (mStatus == Status::SUCCESS && mCallback != nullptr) { bool success = mCallback(); bool success = mCallback(); if (!success) { if (!success) { Loading