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244 lines
11 KiB
244 lines
11 KiB
/*
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* Copyright (C) 2019 The Android Open Source Project
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef ANDROID_FRAMEWORKS_ML_NN_COMMON_OPERATIONS_BIDIRECTIONAL_SEQUENCE_LSTM_H
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#define ANDROID_FRAMEWORKS_ML_NN_COMMON_OPERATIONS_BIDIRECTIONAL_SEQUENCE_LSTM_H
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#include <algorithm>
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#include <cmath>
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#include <vector>
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#include "ActivationFunctor.h"
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#include "LSTM.h"
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#include "OperationsUtils.h"
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namespace android {
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namespace nn {
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struct RunTimeOperandInfo;
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class BidirectionalSequenceLSTM {
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public:
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BidirectionalSequenceLSTM(const Operation& operation, RunTimeOperandInfo* operands);
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bool Prepare(const Operation& operation, RunTimeOperandInfo* operands, Shape* fwOutputShape,
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Shape* bwOutputShape, Shape* fwOutputActivationState, Shape* fwOutputCellState,
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Shape* bwOutputActivationState, Shape* bwOutputCellState);
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bool Eval();
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// Input Tensors of size {max_time, n_batch, n_input}
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static constexpr int kInputTensor = 0;
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// Forward LSTM cell tensors.
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// Input weight tensors of size: {n_cell, n_input}
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static constexpr int kFwInputToInputWeightsTensor = 1; // Optional
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static constexpr int kFwInputToForgetWeightsTensor = 2;
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static constexpr int kFwInputToCellWeightsTensor = 3;
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static constexpr int kFwInputToOutputWeightsTensor = 4;
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// Recurrent weight tensors of size {n_cell, n_output}
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static constexpr int kFwRecurrentToInputWeightsTensor = 5; // Optional
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static constexpr int kFwRecurrentToForgetWeightsTensor = 6;
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static constexpr int kFwRecurrentToCellWeightsTensor = 7;
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static constexpr int kFwRecurrentToOutputWeightsTensor = 8;
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// Peephole weights tensors of size {n_cell}, representing a diagonal matrix.
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static constexpr int kFwCellToInputWeightsTensor = 9; // Optional
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static constexpr int kFwCellToForgetWeightsTensor = 10; // Optional
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static constexpr int kFwCellToOutputWeightsTensor = 11; // Optional
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// Gates bias tensors of size {n_cell}
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static constexpr int kFwInputGateBiasTensor = 12; // Optional
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static constexpr int kFwForgetGateBiasTensor = 13;
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static constexpr int kFwCellGateBiasTensor = 14;
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static constexpr int kFwOutputGateBiasTensor = 15;
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// Projection weight tensor of size {n_output, n_cell}
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static constexpr int kFwProjectionWeightsTensor = 16; // Optional
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// Projection bias tensor of size {n_output}
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static constexpr int kFwProjectionBiasTensor = 17; // Optional
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// Backward LSTM cell tensors.
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// Input weight tensors of size: {n_cell, n_input}
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static constexpr int kBwInputToInputWeightsTensor = 18; // Optional
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static constexpr int kBwInputToForgetWeightsTensor = 19;
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static constexpr int kBwInputToCellWeightsTensor = 20;
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static constexpr int kBwInputToOutputWeightsTensor = 21;
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// Recurrent weight tensors of size {n_cell, n_output}
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static constexpr int kBwRecurrentToInputWeightsTensor = 22; // Optional
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static constexpr int kBwRecurrentToForgetWeightsTensor = 23;
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static constexpr int kBwRecurrentToCellWeightsTensor = 24;
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static constexpr int kBwRecurrentToOutputWeightsTensor = 25;
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// Peephole weights tensors of size {n_cell}, representing a diagonal matrix.
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static constexpr int kBwCellToInputWeightsTensor = 26; // Optional
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static constexpr int kBwCellToForgetWeightsTensor = 27; // Optional
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static constexpr int kBwCellToOutputWeightsTensor = 28; // Optional
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// Gates bias tensors of size {n_cell}
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static constexpr int kBwInputGateBiasTensor = 29; // Optional
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static constexpr int kBwForgetGateBiasTensor = 30;
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static constexpr int kBwCellGateBiasTensor = 31;
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static constexpr int kBwOutputGateBiasTensor = 32;
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// Projection weight tensor of size {n_output, n_cell}
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static constexpr int kBwProjectionWeightsTensor = 33; // Optional
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// Projection bias tensor of size {n_output}
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static constexpr int kBwProjectionBiasTensor = 34; // Optional
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// Stateful input tensors that are variables and will be modified by the Op.
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// Activation state tensors of size {n_batch, n_output}
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static constexpr int kFwInputActivationStateTensor = 35;
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// Cell state tensors of size {n_batch, n_cell}
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static constexpr int kFwInputCellStateTensor = 36;
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// Activation state tensors of size {n_batch, n_output}
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static constexpr int kBwInputActivationStateTensor = 37;
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// Cell state tensors of size {n_batch, n_cell}
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static constexpr int kBwInputCellStateTensor = 38;
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// Used as auxiliary input and weights when stacking for
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// tf.contrib.rnn.stack_bidirectional_rnn case (with cross links); Used as input
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// to the backward cell when stacking for tf.nn.static_bidirectional_rnn case
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// (without cross links).
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static constexpr int kAuxInputTensor = 39; // Optional
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// Forward weights.
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static constexpr int kFwAuxInputToInputWeightsTensor = 40; // Optional
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static constexpr int kFwAuxInputToForgetWeightsTensor = 41; // Optional
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static constexpr int kFwAuxInputToCellWeightsTensor = 42; // Optional
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static constexpr int kFwAuxInputToOutputWeightsTensor = 43; // Optional
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// Backward weights.
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static constexpr int kBwAuxInputToInputWeightsTensor = 44; // Optional
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static constexpr int kBwAuxInputToForgetWeightsTensor = 45; // Optional
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static constexpr int kBwAuxInputToCellWeightsTensor = 46; // Optional
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static constexpr int kBwAuxInputToOutputWeightsTensor = 47; // Optional
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static constexpr int kActivationParam = 48;
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static constexpr int kCellClipParam = 49;
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static constexpr int kProjClipParam = 50;
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static constexpr int kMergeOutputsParam = 51;
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static constexpr int kTimeMajorParam = 52;
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// Forward layer norm weights tensors of size {n_cell}, representing a diagonal matrix.
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static constexpr int kFwInputLayerNormWeightsTensor = 53; // Optional
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static constexpr int kFwForgetLayerNormWeightsTensor = 54; // Optional
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static constexpr int kFwCellLayerNormWeightsTensor = 55; // Optional
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static constexpr int kFwOutputLayerNormWeightsTensor = 56; // Optional
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// Backward layer norm weights tensors of size {n_cell}, representing a diagonal matrix.
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static constexpr int kBwInputLayerNormWeightsTensor = 57; // Optional
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static constexpr int kBwForgetLayerNormWeightsTensor = 58; // Optional
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static constexpr int kBwCellLayerNormWeightsTensor = 59; // Optional
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static constexpr int kBwOutputLayerNormWeightsTensor = 60; // Optional
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// Output tensors.
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static constexpr int kFwOutputTensor = 0;
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static constexpr int kBwOutputTensor = 1; // Ignored if merge_outputs is set.
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static constexpr int kFwOutputActivationStateTensor = 2;
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static constexpr int kFwOutputCellStateTensor = 3;
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static constexpr int kBwOutputActivationStateTensor = 4;
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static constexpr int kBwOutputCellStateTensor = 5;
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private:
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LSTMParams params_;
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Shape fw_scratch_shape_;
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Shape bw_scratch_shape_;
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const RunTimeOperandInfo* input_;
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const RunTimeOperandInfo* aux_input_;
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const RunTimeOperandInfo* fw_aux_input_to_input_weights_;
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const RunTimeOperandInfo* fw_aux_input_to_forget_weights_;
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const RunTimeOperandInfo* fw_aux_input_to_cell_weights_;
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const RunTimeOperandInfo* fw_aux_input_to_output_weights_;
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const RunTimeOperandInfo* bw_aux_input_to_input_weights_;
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const RunTimeOperandInfo* bw_aux_input_to_forget_weights_;
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const RunTimeOperandInfo* bw_aux_input_to_cell_weights_;
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const RunTimeOperandInfo* bw_aux_input_to_output_weights_;
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const RunTimeOperandInfo* fw_input_to_input_weights_;
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const RunTimeOperandInfo* fw_input_to_forget_weights_;
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const RunTimeOperandInfo* fw_input_to_cell_weights_;
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const RunTimeOperandInfo* fw_input_to_output_weights_;
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const RunTimeOperandInfo* fw_recurrent_to_input_weights_;
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const RunTimeOperandInfo* fw_recurrent_to_forget_weights_;
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const RunTimeOperandInfo* fw_recurrent_to_cell_weights_;
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const RunTimeOperandInfo* fw_recurrent_to_output_weights_;
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const RunTimeOperandInfo* fw_cell_to_input_weights_;
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const RunTimeOperandInfo* fw_cell_to_forget_weights_;
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const RunTimeOperandInfo* fw_cell_to_output_weights_;
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const RunTimeOperandInfo* fw_input_gate_bias_;
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const RunTimeOperandInfo* fw_forget_gate_bias_;
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const RunTimeOperandInfo* fw_cell_bias_;
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const RunTimeOperandInfo* fw_output_gate_bias_;
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const RunTimeOperandInfo* fw_projection_weights_;
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const RunTimeOperandInfo* fw_projection_bias_;
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const RunTimeOperandInfo* fw_input_layer_norm_weights_;
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const RunTimeOperandInfo* fw_forget_layer_norm_weights_;
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const RunTimeOperandInfo* fw_cell_layer_norm_weights_;
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const RunTimeOperandInfo* fw_output_layer_norm_weights_;
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const RunTimeOperandInfo* fw_activation_state_;
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const RunTimeOperandInfo* fw_cell_state_;
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RunTimeOperandInfo* fw_output_;
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const RunTimeOperandInfo* bw_input_to_input_weights_;
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const RunTimeOperandInfo* bw_input_to_forget_weights_;
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const RunTimeOperandInfo* bw_input_to_cell_weights_;
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const RunTimeOperandInfo* bw_input_to_output_weights_;
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const RunTimeOperandInfo* bw_recurrent_to_input_weights_;
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const RunTimeOperandInfo* bw_recurrent_to_forget_weights_;
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const RunTimeOperandInfo* bw_recurrent_to_cell_weights_;
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const RunTimeOperandInfo* bw_recurrent_to_output_weights_;
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const RunTimeOperandInfo* bw_cell_to_input_weights_;
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const RunTimeOperandInfo* bw_cell_to_forget_weights_;
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const RunTimeOperandInfo* bw_cell_to_output_weights_;
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const RunTimeOperandInfo* bw_input_gate_bias_;
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const RunTimeOperandInfo* bw_forget_gate_bias_;
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const RunTimeOperandInfo* bw_cell_bias_;
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const RunTimeOperandInfo* bw_output_gate_bias_;
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const RunTimeOperandInfo* bw_projection_weights_;
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const RunTimeOperandInfo* bw_projection_bias_;
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const RunTimeOperandInfo* bw_input_layer_norm_weights_;
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const RunTimeOperandInfo* bw_forget_layer_norm_weights_;
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const RunTimeOperandInfo* bw_cell_layer_norm_weights_;
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const RunTimeOperandInfo* bw_output_layer_norm_weights_;
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const RunTimeOperandInfo* bw_activation_state_;
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const RunTimeOperandInfo* bw_cell_state_;
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RunTimeOperandInfo* bw_output_;
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RunTimeOperandInfo* fw_output_activation_state_;
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RunTimeOperandInfo* fw_output_cell_state_;
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RunTimeOperandInfo* bw_output_activation_state_;
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RunTimeOperandInfo* bw_output_cell_state_;
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};
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} // namespace nn
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} // namespace android
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#endif // ANDROID_FRAMEWORKS_ML_NN_COMMON_OPERATIONS_BIDIRECTIONAL_SEQUENCE_LSTM_H
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