/* Copyright (c) 2016 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. */ #include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h" #include "paddle/fluid/operators/elementwise/elementwise_op_function.h" #include "paddle/fluid/operators/elementwise/elementwise_sub_op.h" #include "paddle/fluid/platform/complex128.h" #include "paddle/fluid/platform/complex64.h" #include "paddle/fluid/platform/float16.h" namespace ops = paddle::operators; namespace plat = paddle::platform; namespace paddle { namespace operators { template struct SameDimsElemwiseSub { void operator()(const framework::ExecutionContext& ctx, const framework::Tensor* x, const framework::Tensor* y, framework::Tensor* z) { SubRangeFunctor functor(x->data(), y->data(), z->data()); auto& dev_ctx = ctx.template device_context(); platform::ForRange for_range(dev_ctx, x->numel()); for_range(functor); } }; template <> struct SameDimsElemwiseSub { void operator()(const framework::ExecutionContext& ctx, const framework::Tensor* x, const framework::Tensor* y, framework::Tensor* z) { auto size = x->numel(); dim3 grid_size = dim3(((size + 1) / 2 + PADDLE_CUDA_THREAD_SIZE - 1) / PADDLE_CUDA_THREAD_SIZE, 1); dim3 block_size = dim3(PADDLE_CUDA_THREAD_SIZE, 1); const half* x2 = reinterpret_cast(x->data()); const half* y2 = reinterpret_cast(y->data()); half* z2 = reinterpret_cast(z->data()); SameDimsElemwiseSubCUDAKernel<<< grid_size, block_size, 0, ctx.template device_context().stream()>>>( x2, y2, z2, size); } }; template static __global__ void SimpleElemwiseSubGradCUDAKernel(const T* dout, int64_t size, T* dx, T* dy) { int col = blockIdx.x * blockDim.x + threadIdx.x; while (col < size) { dx[col] = dout[col]; dy[col] = -dout[col]; col += blockDim.x * gridDim.x; } } template typename std::enable_if< std::is_same::value>::type elementwise_sub_grad(const framework::ExecutionContext& ctx, const framework::Tensor* x, const framework::Tensor* y, const framework::Tensor* out, const framework::Tensor* dout, framework::Tensor* dx, framework::Tensor* dy) { dim3 block_size = dim3(PADDLE_CUDA_THREAD_SIZE, 1); auto size = x->numel(); dim3 grid_size = dim3((size + PADDLE_CUDA_THREAD_SIZE - 1) / PADDLE_CUDA_THREAD_SIZE, 1); SimpleElemwiseSubGradCUDAKernel< T><<().stream()>>>( dout->data(), size, dx->mutable_data(ctx.GetPlace()), dy->mutable_data(ctx.GetPlace())); } } // namespace operators } // namespace paddle REGISTER_OP_CUDA_KERNEL( elementwise_sub, ops::ElementwiseSubKernel, ops::ElementwiseSubKernel, ops::ElementwiseSubKernel, ops::ElementwiseSubKernel, ops::ElementwiseSubKernel, ops::ElementwiseSubKernel, ops::ElementwiseSubKernel); REGISTER_OP_CUDA_KERNEL( elementwise_sub_grad, ops::ElementwiseSubGradKernel, ops::ElementwiseSubGradKernel, ops::ElementwiseSubGradKernel, ops::ElementwiseSubGradKernel, ops::ElementwiseSubGradKernel, ops::ElementwiseSubGradKernel, ops::ElementwiseSubGradKernel); REGISTER_OP_CUDA_KERNEL( elementwise_sub_grad_grad, ops::ElementwiseSubDoubleGradKernel, ops::ElementwiseSubDoubleGradKernel, ops::ElementwiseSubDoubleGradKernel, ops::ElementwiseSubDoubleGradKernel, ops::ElementwiseSubDoubleGradKernel, ops::ElementwiseSubDoubleGradKernel);