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193 lines
7.6 KiB
193 lines
7.6 KiB
/* Copyright (c) 2016 Baidu, Inc. All Rights Reserve.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#ifndef HL_RECURRENT_APPLY_CUH_
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#define HL_RECURRENT_APPLY_CUH_
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#include "hl_base.h"
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#include "hl_activation_functions.h"
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#include "hl_lstm_ops.cuh"
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#include "hl_gpu_lstm.cuh"
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#include "hl_cpu_lstm.cuh"
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#include "hl_gru_ops.cuh"
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#include "hl_gpu_gru.cuh"
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#include "hl_cpu_gru.cuh"
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/**
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* @brief Cpu lstm forward one sequence.
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*
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* @param[in] op hl_lstm_ops.cuh
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* @param[out] value hl_lstm_value type.
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* @param[in] frameSize frame size.
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* @param[in] active_node active input type.
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* @param[in] active_gate active state type.
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* @param[in] active_state actvie gate type.
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*/
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template<class Op>
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extern void hl_cpu_lstm_forward(Op op,
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hl_lstm_value value,
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int frameSize,
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hl_activation_mode_t active_node,
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hl_activation_mode_t active_gate,
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hl_activation_mode_t active_state);
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/**
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* @brief Cpu lstm backward one sequence.
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*
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* @param[in] op hl_lstm_ops.cuh
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* @param[in] value lstm value.
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* @param[out] grad output gradient.
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* @param[in] frameSize frame size.
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* @param[in] active_node active input type.
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* @param[in] active_gate active state type.
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* @param[in] active_state actvie gate type.
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*/
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template<class Op>
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extern void hl_cpu_lstm_backward(Op op,
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hl_lstm_value value,
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hl_lstm_grad grad,
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int frameSize,
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hl_activation_mode_t active_node,
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hl_activation_mode_t active_gate,
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hl_activation_mode_t active_state);
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/**
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* @brief Gpu lstm batch forward.
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*
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* @param[in] op hl_lstm_ops.cuh
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* @param[out] value lstm value.
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* @param[in] frameSize frame size.
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* @param[in] batchSize size of current batch.
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* @param[in] active_node active input type.
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* @param[in] active_gate active state type.
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* @param[in] active_state actvie gate type.
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*/
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template<class Op>
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extern void hl_gpu_lstm_forward(Op op,
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hl_lstm_value value,
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int frameSize,
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int batchSize,
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hl_activation_mode_t active_node,
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hl_activation_mode_t active_gate,
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hl_activation_mode_t active_state);
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/**
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* @brief Gpu lstm batch backward.
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*
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* @param[in] op hl_lstm_ops.cuh
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* @param[out] value lstm value.
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* @param[out] grad lstm gradient.
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* @param[in] frameSize frame size.
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* @param[in] batchSize size of current batch.
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* @param[in] active_node active input type.
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* @param[in] active_gate active state type.
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* @param[in] active_state actvie gate type.
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*/
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template<class Op>
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extern void hl_gpu_lstm_backward(Op op,
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hl_lstm_value value,
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hl_lstm_grad grad,
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int frameSize,
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int batchSize,
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hl_activation_mode_t active_node,
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hl_activation_mode_t active_gate,
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hl_activation_mode_t active_state);
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/**
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* @brief Cpu gru forward.
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*
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* @param[in] opResetOutput hl_gru_ops.cuh
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* @param[in] opFinalOutput hl_gru_ops.cuh
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* @param[in,out] value gru value.
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* @param[in] frameSize frame length/size.
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* @param[in] batchSize size of current batch.
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* @param[in] active_node active input type.
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* @param[in] active_gate active state type.
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*/
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template<class OpResetOutput, class OpFinalOutput>
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extern void hl_cpu_gru_forward(OpResetOutput opResetOutput,
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OpFinalOutput opFinalOutput,
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hl_gru_value value,
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int frameSize,
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int batchSize,
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hl_activation_mode_t active_node,
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hl_activation_mode_t active_gate);
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/**
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* @brief Cpu gru forward.
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*
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* @param[in] opStateGrad hl_gru_ops.cuh
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* @param[in] opResetGrad hl_gru_ops.cuh
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* @param[in] value gru value.
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* @param[in,out] grad gru gradient.
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* @param[in] frameSize frame length/size.
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* @param[in] batchSize size of current batch.
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* @param[in] active_node active input type.
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* @param[in] active_gate active state type.
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*/
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template<class OpStateGrad, class OpResetGrad>
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extern void hl_cpu_gru_backward(OpStateGrad opStateGrad,
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OpResetGrad opResetGrad,
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hl_gru_value value,
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hl_gru_grad grad,
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int frameSize,
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int batchSize,
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hl_activation_mode_t active_node,
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hl_activation_mode_t active_gate);
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/**
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* @brief Gpu gru forward.
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*
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* @param[in] opResetOutput hl_gru_ops.cuh
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* @param[in] opFinalOutput hl_gru_ops.cuh
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* @param[in,out] value gru value.
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* @param[in] frameSize frame length/size.
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* @param[in] batchSize size of current batch.
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* @param[in] active_node active input type.
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* @param[in] active_gate active state type.
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*/
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template<class OpResetOutput, class OpFinalOutput>
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extern void hl_gpu_gru_forward(OpResetOutput opResetOutput,
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OpFinalOutput opFinalOutput,
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hl_gru_value value,
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int frameSize,
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int batchSize,
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hl_activation_mode_t active_node,
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hl_activation_mode_t active_gate);
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/**
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* @brief Gpu gru forward.
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*
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* @param[in] opStateGrad hl_gru_ops.cuh
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* @param[in] opResetGrad hl_gru_ops.cuh
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* @param[in] value gru value.
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* @param[in,out] grad gru gradient.
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* @param[in] frameSize frame length/size.
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* @param[in] batchSize size of current batch.
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* @param[in] active_node active input type.
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* @param[in] active_gate active state type.
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*/
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template<class OpStateGrad, class OpResetGrad>
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extern void hl_gpu_gru_backward(OpStateGrad opStateGrad,
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OpResetGrad opResetGrad,
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hl_gru_value value,
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hl_gru_grad grad,
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int frameSize,
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int batchSize,
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hl_activation_mode_t active_node,
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hl_activation_mode_t active_gate);
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#endif /* HL_RECURRENT_APPLY_CUH_ */
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