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							102 lines
						
					
					
						
							3.7 KiB
						
					
					
				| /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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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| #include "paddle/fluid/operators/math/prelu.h"
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| 
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| namespace paddle {
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| namespace operators {
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| namespace math {
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| 
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| #define CUDA_NUM_THREADS 1024
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| 
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| inline static int PADDLE_GET_BLOCKS(const int N) {
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|   return (N + CUDA_NUM_THREADS - 1) / CUDA_NUM_THREADS;
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| }
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| 
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| template <typename T>
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| __global__ void PReluChannelWiseKernel(const T *input, const T *alpha,
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|                                        T *output, size_t channel_num,
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|                                        size_t plane_size, size_t numel) {
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|   CUDA_KERNEL_LOOP(index, numel) {
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|     size_t temp = index / plane_size;
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|     size_t channel_index = temp % channel_num;
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|     T scale = alpha[channel_index];
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|     T x = input[index];
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|     output[index] = (x > 0) ? x : scale * x;
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|   }
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| }
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| 
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| template <typename T>
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| __global__ void PReluElementWiseKernel(const T *input, const T *alpha,
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|                                        T *output, size_t spatial_size,
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|                                        size_t numel) {
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|   CUDA_KERNEL_LOOP(index, numel) {
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|     size_t element_index = index % spatial_size;
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|     T scale = alpha[element_index];
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|     T x = input[index];
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|     output[index] = (x > 0) ? x : scale * x;
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|   }
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| }
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| 
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| template <typename T>
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| __global__ void PReluScalarKernel(const T *input, const T *alpha, T *output,
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|                                   size_t numel) {
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|   T scale = alpha[0];
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|   CUDA_KERNEL_LOOP(index, numel) {
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|     T x = input[index];
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|     output[index] = (x > 0) ? x : scale * x;
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|   }
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| }
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| 
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| template <typename T>
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| void PreluChannelWiseDirectCUDAFunctor<T>::operator()(
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|     cudaStream_t stream, const T *input, const T *alpha, T *output,
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|     size_t batch_size, size_t channel, size_t numel) {
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|   PReluChannelWiseKernel<<<PADDLE_GET_BLOCKS(numel), CUDA_NUM_THREADS, 0,
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|                            stream>>>(input, alpha, output, channel,
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|                                      numel / batch_size / channel, numel);
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| }
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| 
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| template <typename T>
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| void PreluElementWiseDirectCUDAFunctor<T>::operator()(cudaStream_t stream,
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|                                                       const T *input,
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|                                                       const T *alpha, T *output,
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|                                                       size_t batch_size,
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|                                                       size_t numel) {
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|   PReluElementWiseKernel<<<PADDLE_GET_BLOCKS(numel), CUDA_NUM_THREADS, 0,
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|                            stream>>>(input, alpha, output, numel / batch_size,
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|                                      numel);
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| }
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| 
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| template <typename T>
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| void PreluScalarDirectCUDAFunctor<T>::operator()(cudaStream_t stream,
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|                                                  const T *input, const T *alpha,
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|                                                  T *output, size_t numel) {
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|   PReluScalarKernel<<<PADDLE_GET_BLOCKS(numel), CUDA_NUM_THREADS, 0, stream>>>(
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|       input, alpha, output, numel);
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| }
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| 
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| template class PreluChannelWiseDirectCUDAFunctor<float>;
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| template class PreluChannelWiseDirectCUDAFunctor<double>;
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| 
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| template class PreluElementWiseDirectCUDAFunctor<float>;
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| template class PreluElementWiseDirectCUDAFunctor<double>;
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| 
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| template class PreluScalarDirectCUDAFunctor<float>;
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| template class PreluScalarDirectCUDAFunctor<double>;
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| 
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| }  // namespace math
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| }  // namespace operators
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| }  // namespace paddle
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