wehub-resource-sync
124 lines
4.0 KiB
C++
124 lines
4.0 KiB
C++
// Copyright (c) 2022 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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#pragma once
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#include "paddle/phi/kernels/full_kernel.h"
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#include "paddle/phi/kernels/funcs/complex_functors.h"
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#include "paddle/phi/kernels/funcs/elementwise_grad_base.h"
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#include "paddle/phi/kernels/funcs/for_range.h"
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namespace phi {
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template <typename T, typename Context>
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void RealGradKernel(const Context& dev_ctx,
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const DenseTensor& dout,
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DenseTensor* dx) {
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if (dx && dx->numel() == 0) {
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dev_ctx.template Alloc<T>(dx);
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return;
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}
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auto numel = dout.numel();
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auto* dout_data = dout.data<dtype::Real<T>>();
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auto* dx_data =
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dev_ctx.template Alloc<T>(dx, static_cast<size_t>(numel * sizeof(T)));
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funcs::ForRange<Context> for_range(dev_ctx, numel);
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funcs::RealToComplexFunctor<T> functor(dout_data, dx_data, numel);
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for_range(functor);
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}
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template <typename T, typename Context>
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void ImagGradKernel(const Context& dev_ctx,
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const DenseTensor& dout,
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DenseTensor* dx) {
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if (dx && dx->numel() == 0) {
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dev_ctx.template Alloc<T>(dx);
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return;
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}
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auto numel = dout.numel();
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auto* dout_data = dout.data<dtype::Real<T>>();
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auto* dx_data =
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dev_ctx.template Alloc<T>(dx, static_cast<size_t>(numel * sizeof(T)));
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funcs::ForRange<Context> for_range(dev_ctx, numel);
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funcs::ImagToComplexFunctor<T> functor(dout_data, dx_data, numel);
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for_range(functor);
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}
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template <typename T>
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struct ComplexGradForRealFunctor {
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inline HOSTDEVICE T operator()(const T x UNUSED,
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const T y UNUSED,
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const dtype::complex<T> out UNUSED,
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const dtype::complex<T> dout) {
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return dout.real;
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}
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};
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template <typename T>
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struct ComplexGradForImagFunctor {
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inline HOSTDEVICE T operator()(const T x UNUSED,
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const T y UNUSED,
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const dtype::complex<T> out UNUSED,
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const dtype::complex<T> dout) {
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return dout.imag;
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}
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};
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template <typename T, typename Context>
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void ComplexGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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const DenseTensor& dout,
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DenseTensor* dx,
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DenseTensor* dy) {
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using C = dtype::complex<T>;
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if (dout.numel() == 0) {
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if (dx) {
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if (dx->numel() == 0) {
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dev_ctx.template Alloc<T>(dx);
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} else {
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Full<T, Context>(dev_ctx, dx->dims(), 0, dx);
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}
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}
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if (dy) {
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if (dy->numel() == 0) {
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dev_ctx.template Alloc<T>(dy);
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} else {
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Full<T, Context>(dev_ctx, dy->dims(), 0, dy);
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}
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}
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return;
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}
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// skip out in a hacky way
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auto out = dout;
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funcs::ElemwiseGradCompute<Context,
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T,
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ComplexGradForRealFunctor<T>,
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ComplexGradForImagFunctor<T>,
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C>(dev_ctx,
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x,
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y,
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out,
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dout,
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/*axis*/ -1,
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dx,
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dy,
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ComplexGradForRealFunctor<T>(),
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ComplexGradForImagFunctor<T>());
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}
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} // namespace phi
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