chore: import upstream snapshot with attribution
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wehub-resource-sync
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// 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/core/sparse_coo_tensor.h"
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#include "paddle/phi/core/sparse_csr_tensor.h"
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#include "paddle/phi/core/tensor_utils.h"
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#include "paddle/phi/kernels/abs_grad_kernel.h"
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#include "paddle/phi/kernels/activation_grad_kernel.h"
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#include "paddle/phi/kernels/cast_kernel.h"
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#include "paddle/phi/kernels/sparse/empty_kernel.h"
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#include "paddle/phi/kernels/sparse/impl/unary_kernel_impl.h"
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namespace phi {
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namespace sparse {
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#define DEFINE_SPARSE_UNARY_GRAD_KERNEL(prefix) \
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template <typename T, typename Context> \
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void prefix##CooGradKernel(const Context& dev_ctx, \
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const SparseCooTensor& x_or_out, \
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const SparseCooTensor& dout, \
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SparseCooTensor* dx) { \
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EmptyLikeCooKernel<T, Context>(dev_ctx, x_or_out, dx); \
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if (dx->mutable_non_zero_elements()->numel() == 0) { \
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return; \
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} \
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phi::prefix##GradKernel<T, Context>(dev_ctx, \
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x_or_out.non_zero_elements(), \
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dout.non_zero_elements(), \
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dx->mutable_non_zero_elements()); \
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} \
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\
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template <typename T, typename Context> \
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void prefix##CsrGradKernel(const Context& dev_ctx, \
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const SparseCsrTensor& x_or_out, \
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const SparseCsrTensor& dout, \
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SparseCsrTensor* dx) { \
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EmptyLikeCsrKernel<T, Context>(dev_ctx, x_or_out, dx); \
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if (dx->mutable_non_zero_elements()->numel() == 0) { \
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return; \
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} \
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phi::prefix##GradKernel<T, Context>(dev_ctx, \
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x_or_out.non_zero_elements(), \
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dout.non_zero_elements(), \
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dx->mutable_non_zero_elements()); \
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}
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#define DEFINE_SPARSE_UNARY_GRAD_KERNEL_WITH_ONE_ATTR(prefix, attr) \
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template <typename T, typename Context> \
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void prefix##CooGradKernel(const Context& dev_ctx, \
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const SparseCooTensor& x_or_out, \
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const SparseCooTensor& dout, \
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float attr, \
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SparseCooTensor* dx) { \
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EmptyLikeCooKernel<T, Context>(dev_ctx, x_or_out, dx); \
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if (dx->mutable_non_zero_elements()->numel() == 0) { \
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return; \
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} \
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phi::prefix##GradKernel<T, Context>(dev_ctx, \
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x_or_out.non_zero_elements(), \
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dout.non_zero_elements(), \
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attr, \
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dx->mutable_non_zero_elements()); \
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} \
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\
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template <typename T, typename Context> \
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void prefix##CsrGradKernel(const Context& dev_ctx, \
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const SparseCsrTensor& x_or_out, \
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const SparseCsrTensor& dout, \
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float attr, \
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SparseCsrTensor* dx) { \
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EmptyLikeCsrKernel<T, Context>(dev_ctx, x_or_out, dx); \
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if (dx->mutable_non_zero_elements()->numel() == 0) { \
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return; \
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} \
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phi::prefix##GradKernel<T, Context>(dev_ctx, \
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x_or_out.non_zero_elements(), \
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dout.non_zero_elements(), \
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attr, \
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dx->mutable_non_zero_elements()); \
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}
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Sin)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Tan)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Asin)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Atan)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Sinh)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Tanh)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Asinh)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Atanh)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Sqrt)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Square)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Log1p)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Abs)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Relu)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Expm1)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL(Relu6)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL_WITH_ONE_ATTR(Pow, factor)
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DEFINE_SPARSE_UNARY_GRAD_KERNEL_WITH_ONE_ATTR(LeakyRelu, alpha)
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template <typename T, typename Context>
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void CastCooGradKernel(const Context& dev_ctx,
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const SparseCooTensor& x,
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const SparseCooTensor& dout,
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DataType value_dtype,
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SparseCooTensor* dx) {
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EmptyLikeCooKernel<T, Context>(dev_ctx, x, dx);
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if (value_dtype == DataType::UNDEFINED) {
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phi::Copy(dev_ctx,
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dout.non_zero_elements(),
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dev_ctx.GetPlace(),
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false,
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dx->mutable_non_zero_elements());
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} else {
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CastKernel<T, Context>(dev_ctx,
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dout.non_zero_elements(),
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x.non_zero_elements().dtype(),
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dx->mutable_non_zero_elements());
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}
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}
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template <typename T, typename Context>
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void CastCsrGradKernel(const Context& dev_ctx,
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const SparseCsrTensor& x,
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const SparseCsrTensor& dout,
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DataType value_dtype,
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SparseCsrTensor* dx) {
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EmptyLikeCsrKernel<T, Context>(dev_ctx, x, dx);
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if (value_dtype == DataType::UNDEFINED) {
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phi::Copy(dev_ctx,
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dout.non_zero_elements(),
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dev_ctx.GetPlace(),
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false,
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dx->mutable_non_zero_elements());
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} else {
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CastKernel<T, Context>(dev_ctx,
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dout.non_zero_elements(),
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x.non_zero_elements().dtype(),
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dx->mutable_non_zero_elements());
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}
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}
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} // namespace sparse
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} // namespace phi
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