72 lines
2.2 KiB
C++
72 lines
2.2 KiB
C++
// 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.
|
|
|
|
#pragma once
|
|
|
|
#include "paddle/phi/backends/all_context.h"
|
|
#include "paddle/phi/common/transform.h"
|
|
#include "paddle/phi/core/kernel_registry.h"
|
|
#include "paddle/phi/kernels/clip_kernel.h"
|
|
#if defined(__NVCC__) || defined(__HIPCC__)
|
|
#include "paddle/phi/kernels/funcs/broadcast_function.h"
|
|
#endif
|
|
|
|
namespace phi {
|
|
|
|
template <typename T>
|
|
class ClipGradFunctor {
|
|
public:
|
|
explicit ClipGradFunctor(const T min, const T max) : min_(min), max_(max) {}
|
|
HOSTDEVICE T operator()(const T x, const T y) const {
|
|
return (y >= min_ && y <= max_) ? x : static_cast<T>(0);
|
|
}
|
|
|
|
private:
|
|
T min_;
|
|
T max_;
|
|
};
|
|
|
|
template <typename T, typename Context>
|
|
void ClipGradKernel(const Context& dev_ctx,
|
|
const DenseTensor& x,
|
|
const DenseTensor& out_grad,
|
|
const Scalar& min,
|
|
const Scalar& max,
|
|
DenseTensor* x_grad) {
|
|
auto max_ = max.to<T>();
|
|
auto min_ = min.to<T>();
|
|
|
|
#if defined(__NVCC__) || defined(__HIPCC__)
|
|
std::vector<const DenseTensor*> ins = {&out_grad, &x};
|
|
std::vector<DenseTensor*> outs = {x_grad};
|
|
auto functor = ClipGradFunctor<T>(min_, max_);
|
|
dev_ctx.template Alloc<T>(x_grad);
|
|
funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
|
|
#else
|
|
int64_t numel = out_grad.numel();
|
|
auto* d_x_data = dev_ctx.template Alloc<T>(x_grad);
|
|
const T* d_out_data = out_grad.data<T>();
|
|
const T* x_data = x.data<T>();
|
|
Transform<Context> trans;
|
|
trans(dev_ctx,
|
|
d_out_data,
|
|
d_out_data + numel,
|
|
x_data,
|
|
d_x_data,
|
|
ClipGradFunctor<T>(min_, max_));
|
|
#endif
|
|
}
|
|
|
|
} // namespace phi
|