wehub-resource-sync
77 lines
2.5 KiB
C++
77 lines
2.5 KiB
C++
// Copyright (c) 2024 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 <glog/logging.h>
|
|
|
|
#include <algorithm>
|
|
#include <cmath>
|
|
#include <memory>
|
|
#include <string>
|
|
#include <unordered_set>
|
|
#include <utility>
|
|
#include <vector>
|
|
#ifndef _USE_MATH_DEFINES
|
|
#define _USE_MATH_DEFINES
|
|
#endif
|
|
|
|
#include <type_traits>
|
|
|
|
#include "paddle/phi/core/kernel_registry.h"
|
|
#include "paddle/phi/core/tensor_utils.h"
|
|
#include "paddle/phi/kernels/funcs/activation_functor.h"
|
|
#include "paddle/phi/kernels/funcs/blas/blas.h"
|
|
#include "paddle/phi/kernels/funcs/eigen/common.h"
|
|
#include "paddle/phi/kernels/soft_relu_grad_kernel.h"
|
|
|
|
namespace phi {
|
|
|
|
template <typename T>
|
|
struct SoftReluGradFunctor {
|
|
float threshold;
|
|
void SetAttrs(float threshold_) { threshold = threshold_; }
|
|
|
|
template <typename Device,
|
|
typename X,
|
|
typename Out,
|
|
typename dOut,
|
|
typename dX>
|
|
void operator()(Device d, X x UNUSED, Out out, dOut dout, dX dx) {
|
|
auto tmp = static_cast<T>(threshold);
|
|
auto temp = ((out > -tmp) * (out < tmp)).template cast<T>();
|
|
dx.device(d) = dout * (static_cast<T>(1) - (-out).exp()) * temp;
|
|
}
|
|
};
|
|
|
|
template <typename T, typename Context>
|
|
void SoftmaxGradKernel(const Context& dev_ctx,
|
|
const DenseTensor& x_in,
|
|
const DenseTensor& out_in,
|
|
const DenseTensor& out_grad,
|
|
float threshold,
|
|
DenseTensor* x_grad) {
|
|
dev_ctx.template Alloc<T>(x_grad);
|
|
auto dout = EigenVector<T>::Flatten(out_grad);
|
|
auto out = EigenVector<T>::Flatten(out_in);
|
|
auto dx = EigenVector<T>::Flatten(*x_grad);
|
|
auto x = EigenVector<T>::Flatten(x_in);
|
|
auto* eigen_dev = dev_ctx.eigen_device();
|
|
SoftReluGradFunctor<T> functor;
|
|
functor.SetAttrs(threshold);
|
|
functor(*eigen_dev, x, out, dout, dx);
|
|
}
|
|
} // namespace phi
|
|
|
|
PD_REGISTER_KERNEL(
|
|
soft_relu_grad, CPU, ALL_LAYOUT, phi::SoftmaxGradKernel, float, double) {}
|