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/*
* 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 ANDROID_FRAMEWORKS_ML_NN_COMMON_OPERATIONS_RNN_H
#define ANDROID_FRAMEWORKS_ML_NN_COMMON_OPERATIONS_RNN_H
#include <vector>
#include "ActivationFunctor.h"
#include "nnapi/Types.h"
namespace android {
namespace nn {
struct RunTimeOperandInfo;
struct Shape;
class RNN {
public:
RNN(const Operation& operation, RunTimeOperandInfo* operands);
static bool Prepare(const Operation& operation, RunTimeOperandInfo* operands,
Shape* hiddenStateShape, Shape* outputShape);
bool Eval();
static constexpr int kInputTensor = 0;
static constexpr int kWeightsTensor = 1;
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 // ANDROID_FRAMEWORKS_ML_NN_COMMON_OPERATIONS_RNN_H
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