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move clip XPU kernel to PHI,test=kunlun (#45568)
* move clip XPU kernel to PHI,test=kunlun * delete clip_op_xpu.cc,test=kunlun
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paddle/fluid/operators/clip_op_xpu.cc

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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/clip_kernel.h"
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#include "paddle/phi/backends/xpu/xpu_context.h"
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#include "paddle/phi/backends/xpu/xpu_header.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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template <typename T, typename Context>
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void ClipKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const Scalar& min,
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const Scalar& max,
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DenseTensor* out) {
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dev_ctx.template Alloc<T>(out);
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using XPUDataType = typename XPUTypeTrait<T>::Type;
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auto x_data = reinterpret_cast<const XPUDataType*>(x.data<T>());
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auto out_data = reinterpret_cast<XPUDataType*>(out->data<T>());
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int r = xpu::clip_v2(dev_ctx.x_context(),
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x_data,
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out_data,
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x.numel(),
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min.to<float>(),
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max.to<float>());
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PADDLE_ENFORCE_EQ(r,
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XPU_SUCCESS,
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phi::errors::External("XPU API(clip_v2) return wrong "
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"value[%d %s]",
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r,
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XPUAPIErrorMsg[r]));
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}
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} // namespace phi
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PD_REGISTER_KERNEL(clip, XPU, ALL_LAYOUT, phi::ClipKernel, float) {}

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