/*
 * 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