• Home
  • Line#
  • Scopes#
  • Navigate#
  • Raw
  • Download
1 /*
2  * Copyright (C) 2017 The Android Open Source Project
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  *      http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16 
17 #ifndef FRAMEWORKS_ML_NN_RNN_H
18 #define FRAMEWORKS_ML_NN_RNN_H
19 
20 #include "ActivationFunctor.h"
21 #include "HalOperation.h"
22 
23 namespace android {
24 namespace nn {
25 
26 struct RunTimeOperandInfo;
27 struct Shape;
28 
29 class RNN {
30    public:
31     RNN(const Operation& operation, std::vector<RunTimeOperandInfo>& operands);
32 
33     static bool Prepare(const Operation& operation, std::vector<RunTimeOperandInfo>& operands,
34                         Shape* hiddenStateShape, Shape* outputShape);
35     bool Eval();
36 
37     static constexpr int kInputTensor = 0;
38     static constexpr int kWeightsTensor = 1;  // Optional
39     static constexpr int kRecurrentWeightsTensor = 2;
40     static constexpr int kBiasTensor = 3;
41     static constexpr int kHiddenStateInTensor = 4;
42     static constexpr int kActivationParam = 5;
43 
44     static constexpr int kHiddenStateOutTensor = 0;
45     static constexpr int kOutputTensor = 1;
46 
47     template <typename T>
48     static bool RNNStep(const T* inputData, const Shape& inputShape, const T* hiddenStateInputData,
49                         const T* biasData, const T* weightsData, const Shape& weightsShape,
50                         const T* recurrentWeightsData, const Shape& recurrentWeightsShape,
51                         int32_t activation, T* outputData);
52 
53     template <typename T>
54     static bool RNNStep(const T* inputData, const Shape& inputShape, const T* auxInputData,
55                         const Shape& auxInputShape, const T* hiddenStateInputData,
56                         const T* biasData, const T* weightsData, const Shape& weightsShape,
57                         const T* auxWeightsData, const Shape& auxWeightsShape,
58                         const T* recurrentWeightsData, const Shape& recurrentWeightsShape,
59                         int32_t activation, uint32_t outputBatchStride, uint32_t outputBatchStep,
60                         T* outputData, T* hiddenStateOutput = nullptr);
61 
62    private:
63     ActivationFn activation_;
64 
65     const RunTimeOperandInfo* input_;
66     const RunTimeOperandInfo* weights_;
67     const RunTimeOperandInfo* recurrent_weights_;
68     const RunTimeOperandInfo* bias_;
69     const RunTimeOperandInfo* hidden_state_in_;
70 
71     RunTimeOperandInfo* hidden_state_out_;
72     RunTimeOperandInfo* output_;
73 };
74 
75 }  // namespace nn
76 }  // namespace android
77 
78 #endif  // FRAMEWORKS_ML_NN_RNN_H
79