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paddlepaddle--paddle/paddle/phi/kernels/xpu/elementwise_divide_kernel.cc
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2026-07-13 12:40:42 +08:00

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// Copyright (c) 2022 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/elementwise_divide_kernel.h"
#include <memory>
#include <string>
#include "paddle/phi/backends/xpu/xpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/elementwise_base.h"
#include "paddle/phi/kernels/xpu/elementwise.h"
namespace phi {
template <typename T, typename Context>
void DivideKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
using XPUType = typename XPUTypeTrait<T>::Type;
auto f = [](xpu::Context* xpu_ctx,
const XPUType* x,
const XPUType* y,
XPUType* z,
const std::vector<int64_t>& xshape,
const std::vector<int64_t>& yshape) {
return xpu::broadcast_div<XPUType>(xpu_ctx, x, y, z, xshape, yshape);
};
XPUElementwise<T, XPUType>(dev_ctx, x, y, -1, out, f);
}
} // namespace phi
PD_REGISTER_KERNEL(divide,
XPU,
ALL_LAYOUT,
phi::DivideKernel,
float,
phi::float16,
phi::bfloat16,
int,
int64_t) {}