/* * Copyright (C) 2017 The Android Open Source Project * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #ifndef FRAMEWORKS_ML_NN_RNN_H #define FRAMEWORKS_ML_NN_RNN_H #include "ActivationFunctor.h" #include "HalOperation.h" namespace android { namespace nn { struct RunTimeOperandInfo; struct Shape; class RNN { public: RNN(const Operation& operation, std::vector<RunTimeOperandInfo>& operands); static bool Prepare(const Operation& operation, std::vector<RunTimeOperandInfo>& operands, Shape* hiddenStateShape, Shape* outputShape); bool Eval(); static constexpr int kInputTensor = 0; static constexpr int kWeightsTensor = 1; // Optional static constexpr int kRecurrentWeightsTensor = 2; static constexpr int kBiasTensor = 3; static constexpr int kHiddenStateInTensor = 4; static constexpr int kActivationParam = 5; static constexpr int kHiddenStateOutTensor = 0; static constexpr int kOutputTensor = 1; template <typename T> static bool RNNStep(const T* inputData, const Shape& inputShape, const T* hiddenStateInputData, const T* biasData, const T* weightsData, const Shape& weightsShape, const T* recurrentWeightsData, const Shape& recurrentWeightsShape, int32_t activation, T* outputData); template <typename T> static bool RNNStep(const T* inputData, const Shape& inputShape, const T* auxInputData, const Shape& auxInputShape, const T* hiddenStateInputData, const T* biasData, const T* weightsData, const Shape& weightsShape, const T* auxWeightsData, const Shape& auxWeightsShape, const T* recurrentWeightsData, const Shape& recurrentWeightsShape, int32_t activation, uint32_t outputBatchStride, uint32_t outputBatchStep, T* outputData, T* hiddenStateOutput = nullptr); private: ActivationFn activation_; const RunTimeOperandInfo* input_; const RunTimeOperandInfo* weights_; const RunTimeOperandInfo* recurrent_weights_; const RunTimeOperandInfo* bias_; const RunTimeOperandInfo* hidden_state_in_; RunTimeOperandInfo* hidden_state_out_; RunTimeOperandInfo* output_; }; } // namespace nn } // namespace android #endif // FRAMEWORKS_ML_NN_RNN_H