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