chore: import upstream snapshot with attribution
This commit is contained in:
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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#include "paddle/phi/kernels/sparse/unary_kernel.h"
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/eigen/common.h"
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#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
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#include "paddle/phi/kernels/sparse/impl/unary_grad_kernel_impl.h"
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#include "paddle/phi/kernels/sparse/impl/unary_kernel_impl.h"
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namespace phi::sparse {
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template <typename T, typename Context>
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void DivScalarCooKernel(const Context& dev_ctx,
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const SparseCooTensor& x,
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float scalar,
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SparseCooTensor* out) {
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EmptyLikeCooKernel<T, Context>(dev_ctx, x, out);
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auto eigen_out = EigenVector<T>::Flatten(*(out->mutable_non_zero_elements()));
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auto eigen_x = EigenVector<T>::Flatten(x.non_zero_elements());
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auto& dev = *dev_ctx.eigen_device();
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funcs::EigenDiv<std::decay_t<decltype(dev)>, T>::Eval(
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dev, eigen_out, eigen_x, static_cast<T>(scalar));
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}
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template <typename T, typename Context>
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void DivScalarCsrKernel(const Context& dev_ctx,
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const SparseCsrTensor& x,
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float scalar,
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SparseCsrTensor* out) {
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EmptyLikeCsrKernel<T, Context>(dev_ctx, x, out);
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auto eigen_out = EigenVector<T>::Flatten(*(out->mutable_non_zero_elements()));
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auto eigen_x = EigenVector<T>::Flatten(x.non_zero_elements());
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auto& dev = *dev_ctx.eigen_device();
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funcs::EigenDiv<std::decay_t<decltype(dev)>, T>::Eval(
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dev, eigen_out, eigen_x, static_cast<T>(scalar));
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}
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} // namespace phi::sparse
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#define PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(name, prefix) \
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PD_REGISTER_KERNEL(name##_coo, \
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CPU, \
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ALL_LAYOUT, \
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phi::sparse::prefix##CooKernel, \
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float, \
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double) { \
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO); \
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} \
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\
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PD_REGISTER_KERNEL(name##_csr, \
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CPU, \
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ALL_LAYOUT, \
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phi::sparse::prefix##CsrKernel, \
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float, \
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double) { \
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_CSR); \
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}
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#define PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(name, prefix) \
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PD_REGISTER_KERNEL(name##_coo, \
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CPU, \
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ALL_LAYOUT, \
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phi::sparse::prefix##CooKernel, \
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float, \
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double, \
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phi::complex64, \
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phi::complex128) { \
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO); \
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} \
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\
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PD_REGISTER_KERNEL(name##_csr, \
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CPU, \
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ALL_LAYOUT, \
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phi::sparse::prefix##CsrKernel, \
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float, \
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double, \
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phi::complex64, \
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phi::complex128) { \
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_CSR); \
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}
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(sqrt, Sqrt)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(relu, Relu)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(pow, Pow)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(scale, Scale)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(relu6, Relu6)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(leaky_relu, LeakyRelu)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(asin, Asin)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(asinh, Asinh)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(atanh, Atanh)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(expm1, Expm1)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(log1p, Log1p)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(square, Square)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(tanh, Tanh)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(sinh, Sinh)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(tan, Tan)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(sin, Sin)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(abs, Abs)
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PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(atan, Atan)
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PD_REGISTER_KERNEL(divide_scalar_coo,
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CPU,
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ALL_LAYOUT,
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phi::sparse::DivScalarCooKernel,
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float,
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double) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
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}
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PD_REGISTER_KERNEL(divide_scalar_csr,
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CPU,
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ALL_LAYOUT,
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phi::sparse::DivScalarCsrKernel,
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float,
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double) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_CSR);
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}
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PD_REGISTER_KERNEL(cast_coo,
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CPU,
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ALL_LAYOUT,
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phi::sparse::CastCooKernel,
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float,
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double,
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int8_t,
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uint8_t,
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int16_t,
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int,
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int64_t,
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bool) {}
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PD_REGISTER_KERNEL(cast_csr,
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CPU,
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ALL_LAYOUT,
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phi::sparse::CastCsrKernel,
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float,
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double,
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int8_t,
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uint8_t,
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int16_t,
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int,
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int64_t,
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bool) {}
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PD_REGISTER_KERNEL(isnan_coo,
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CPU,
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ALL_LAYOUT,
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phi::sparse::IsnanCooKernel,
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float,
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double,
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phi::float16,
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int,
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int64_t) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
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}
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PD_REGISTER_KERNEL(isnan_csr,
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CPU,
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ALL_LAYOUT,
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phi::sparse::IsnanCsrKernel,
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float,
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double,
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phi::float16,
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int,
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int64_t) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_CSR);
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}
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