/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. 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. */ #pragma once #include #include #include "paddle/phi/kernels/funcs/math_function.h" namespace phi { #define CUDA_NUM_THREADS 1024 inline static int PADDLE_GET_BLOCKS(const int N) { return (N + CUDA_NUM_THREADS - 1) / CUDA_NUM_THREADS; } template __global__ void PReluChannelFirstWiseKernel(const T *input, const T *alpha, T *output, size_t channel_num, size_t plane_size, size_t numel) { CUDA_KERNEL_LOOP(index, numel) { size_t temp = index / plane_size; size_t channel_index = temp % channel_num; T scale = alpha[channel_index]; T x = input[index]; T zero = static_cast(0); output[index] = (x > zero) ? x : scale * x; } } template __global__ void PReluChannelLastWiseKernel(const T *input, const T *alpha, T *output, size_t channel_num, size_t numel) { CUDA_KERNEL_LOOP(index, numel) { size_t channel_index = index % channel_num; T scale = alpha[channel_index]; T x = input[index]; T zero = static_cast(0); output[index] = (x > zero) ? x : scale * x; } } template __global__ void PReluElementWiseKernel(const T *input, const T *alpha, T *output, size_t spatial_size, size_t numel) { CUDA_KERNEL_LOOP(index, numel) { size_t element_index = index % spatial_size; T scale = alpha[element_index]; T x = input[index]; T zero = static_cast(0); output[index] = (x > zero) ? x : scale * x; } } template __global__ void PReluScalarKernel(const T *input, const T *alpha, T *output, size_t numel) { T scale = alpha[0]; CUDA_KERNEL_LOOP(index, numel) { T x = input[index]; T zero = static_cast(0); output[index] = (x > zero) ? x : scale * x; } } template class PreluChannelWiseDirectCUDAFunctor { public: void operator()(gpuStream_t stream, const T *input, const T *alpha, T *output, size_t batch_size, size_t channel, bool channel_last, size_t numel); }; template class PreluElementWiseDirectCUDAFunctor { public: void operator()(gpuStream_t stream, const T *input, const T *alpha, T *output, size_t batch_size, size_t numel); }; template class PreluScalarDirectCUDAFunctor { public: void operator()(gpuStream_t stream, const T *input, const T *alpha, T *output, size_t numel); }; template void PreluChannelWiseDirectCUDAFunctor::operator()(gpuStream_t stream, const T *input, const T *alpha, T *output, size_t batch_size, size_t channel, bool channel_last, size_t numel) { if (channel_last) { PReluChannelLastWiseKernel<<>>( input, alpha, output, channel, numel); } else { PReluChannelFirstWiseKernel<<>>( input, alpha, output, channel, numel / batch_size / channel, numel); } } template void PreluElementWiseDirectCUDAFunctor::operator()(gpuStream_t stream, const T *input, const T *alpha, T *output, size_t batch_size, size_t numel) { PReluElementWiseKernel<<>>( input, alpha, output, numel / batch_size, numel); } template void PreluScalarDirectCUDAFunctor::operator()(gpuStream_t stream, const T *input, const T *alpha, T *output, size_t numel) { PReluScalarKernel<<>>( input, alpha, output, numel); } template class PreluChannelWiseDirectCUDAFunctor; template class PreluChannelWiseDirectCUDAFunctor; template class PreluChannelWiseDirectCUDAFunctor; template class PreluElementWiseDirectCUDAFunctor; template class PreluElementWiseDirectCUDAFunctor; template class PreluElementWiseDirectCUDAFunctor; template class PreluScalarDirectCUDAFunctor; template class PreluScalarDirectCUDAFunctor; template class PreluScalarDirectCUDAFunctor; } // namespace phi