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2026-07-13 12:40:42 +08:00

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// Copyright (c) 2023 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/phi/kernels/i1_grad_kernel.h"
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/for_range.h"
#include "paddle/phi/kernels/impl/bessel_grad_kernel_impl.h"
namespace phi {
template <typename T, typename Context>
void I1GradKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& out,
const DenseTensor& out_grad,
DenseTensor* x_grad) {
if (x_grad && x_grad->numel() == 0) {
dev_ctx.template Alloc<T>(x_grad);
return;
}
const int64_t size = x.numel();
const T* x_data = x.data<T>();
const T* out_data = out.data<T>();
const T* out_grad_data = out_grad.data<T>();
T* x_grad_data = dev_ctx.template Alloc<T>(x_grad);
funcs::ForRange<Context> for_range(dev_ctx, size);
I1GradFunctor<T> functor(x_data, out_data, out_grad_data, x_grad_data, size);
for_range(functor);
}
} // namespace phi
PD_REGISTER_KERNEL(i1_grad, CPU, ALL_LAYOUT, phi::I1GradKernel, float, double) {
}