// 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"

namespace phi {

template <typename T>
struct SoftReluFunctor {
  float threshold;
  void SetAttrs(float threshold_) { threshold = threshold_; }

  template <typename Device, typename X, typename Out>
  void operator()(Device d, X x, Out out) {
    auto tmp = static_cast<T>(threshold);
    auto temp = x.cwiseMax(-tmp).cwiseMin(tmp);
    out.device(d) = (static_cast<T>(1) + temp.exp()).log();
  }
};

template <typename T, typename Context>
void SoftmaxKernel(const Context& dev_ctx,
                   const DenseTensor& x,
                   float threshold,
                   DenseTensor* out) {
  dev_ctx.template Alloc<T>(out);

  auto x_flatten = EigenVector<T>::Flatten(x);
  auto out_flatten = EigenVector<T>::Flatten(*out);
  auto* eigen_dev = dev_ctx.eigen_device();
  SoftReluFunctor<T> functor;
  functor.SetAttrs(threshold);
  functor(*eigen_dev, x_flatten, out_flatten);
}

}  // namespace phi

PD_REGISTER_KERNEL(
    soft_relu, CPU, ALL_LAYOUT, phi::SoftmaxKernel, float, double) {}