lstm_kernel.h

/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

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. */

#include "hl_activation_functions.h"

#ifdef __CUDA_ARCH__
#define INLINE __device__ inline
#else
#define INLINE inline
#endif

namespace paddle {
namespace operators {
namespace math {
namespace detail {

namespace forward {

template <class T>
class lstm {
 public:
  INLINE void operator()(T &valueIn, T &valueIg, T &valueFg, T &valueOg,
                         T &prevState, T &state, T &stateAtv, T &output,
                         T &checkI, T &checkF, T &checkO,
                         Active<T>::forward actInput,
                         Active<T>::forward actGate,
                         Active<T>::forward actState) {
    valueIn = actInput(valueIn);
    valueIg = actGate(valueIg + prevState * checkI);
    valueFg = actGate(valueFg + prevState * checkF);
    state = valueIn * valueIg + prevState * valueFg;
    valueOg = actGate(valueOg + state * checkO);
    stateAtv = actState(state);
    output = valueOg * stateAtv;
  }
#ifndef __NVCC__
#ifndef __AVX__
  static const bool avx = false;
#else
  static const bool avx = true;
  INLINE void operator()(__m256 &valueIn, __m256 &valueIg, __m256 &valueFg,
                         __m256 &valueOg, __m256 &prevState, __m256 &state,
                         __m256 &stateAtv, __m256 &output, __m256 &checkI,
                         __m256 &checkF, __m256 &checkO,
                         Active<__m256>::forward actInput,
                         Active<__m256>::forward actGate,
                         Active<__m256>::forward actState) {
    valueIn = actInput(valueIn);
    valueIg = actGate(_mm256_add_ps(valueIg, _mm256_mul_ps(prevState, checkI)));
    valueFg = actGate(_mm256_add_ps(valueFg, _mm256_mul_ps(prevState, checkF)));
    state = _mm256_add_ps(_mm256_mul_ps(valueIn, valueIg),
                          _mm256_mul_ps(prevState, valueFg));
    valueOg = actGate(_mm256_add_ps(valueOg, _mm256_mul_ps(state, checkO)));
    stateAtv = actState(state);
    output = _mm256_mul_ps(valueOg, stateAtv);
  }
#endif
#endif
};

}  // namespace forward

namespace backward {

template <class T>
class lstm {
 public:
  INLINE void operator()(T &valueIn, T &valueIg, T &valueFg, T &valueOg,
                         T &gradIn, T &gradIg, T &gradFg, T &gradOg,
                         T &prevState, T &prevStateGrad, T &state, T &stateGrad,
                         T &stateAtv, T &outputGrad, T &checkI, T &checkF,
                         T &checkO, T &checkIGrad, T &checkFGrad, T &checkOGrad,
                         Active<T>::backward actInput,
                         Active<T>::backward actGate,
                         Active<T>::backward actState) {
    gradOg = actGate(outputGrad * stateAtv, valueOg);
    stateGrad += actState(outputGrad * valueOg, stateAtv) + gradOg * checkO;
    gradIn = actInput(stateGrad * valueIg, valueIn);
    gradIg = actGate(stateGrad * valueIn, valueIg);
    gradFg = actGate(stateGrad * prevState, valueFg);
    prevStateGrad = gradIg * checkI + gradFg * checkF + stateGrad * valueFg;
    checkIGrad = gradIg * prevState;
    checkFGrad = gradFg * prevState;
    checkOGrad = gradOg * state;
  }
#ifndef __NVCC__
#ifndef __AVX__
  static const bool avx = false;
#else
  static const bool avx = true;
  INLINE void operator()(__m256 &valueIn, __m256 &valueIg, __m256 &valueFg,
                         __m256 &valueOg, __m256 &gradIn, __m256 &gradIg,
                         __m256 &gradFg, __m256 &gradOg, __m256 &prevState,
                         __m256 &prevStateGrad, __m256 &state,
                         __m256 &stateGrad, __m256 &stateAtv,
                         __m256 &outputGrad, __m256 &checkI, __m256 &checkF,
                         __m256 &checkO, __m256 &checkIGrad, __m256 &checkFGrad,
                         __m256 &checkOGrad, Active<__m256>::backward actInput,
                         Active<__m256>::backward actGate,
                         Active<__m256>::backward actState) {
    gradOg = actGate(_mm256_mul_ps(outputGrad, stateAtv), valueOg);
    stateGrad = _mm256_add_ps(
        actState(_mm256_mul_ps(outputGrad, valueOg), stateAtv), stateGrad);
    stateGrad = _mm256_add_ps(_mm256_mul_ps(gradOg, checkO), stateGrad);
    gradIn = actInput(_mm256_mul_ps(stateGrad, valueIg), valueIn);
    gradIg = actGate(_mm256_mul_ps(stateGrad, valueIn), valueIg);
    gradFg = actGate(_mm256_mul_ps(stateGrad, prevState), valueFg);
    prevStateGrad = _mm256_add_ps(_mm256_mul_ps(gradIg, checkI),
                                  _mm256_mul_ps(gradFg, checkF));
    prevStateGrad =
        _mm256_add_ps(_mm256_mul_ps(stateGrad, valueFg), prevStateGrad);
    checkIGrad = _mm256_mul_ps(gradIg, prevState);
    checkFGrad = _mm256_mul_ps(gradFg, prevState);
    checkOGrad = _mm256_mul_ps(gradOg, state);
  }
#endif
#endif
};

}  // namespace backward

}  // namespace detail
}  // namespace math
}  // namespace operators
}  // namespace paddle

#endif /* HL_LSTM_OPS_CUH_ */