// 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/dropout_grad_kernel.h"
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/eigen/common.h"

namespace phi {

template <typename T, typename Context>
void DropoutGradRawKernel(const Context& dev_ctx,
                          const DenseTensor& mask,
                          const DenseTensor& out_grad,
                          float p,
                          bool is_test,
                          const std::string& mode,
                          DenseTensor* x_grad) {
  auto* grad_x = x_grad;
  auto* grad_y = &out_grad;
  grad_x->mutable_data<T>(dev_ctx.GetPlace());

  auto dX = EigenVector<T>::Flatten(*grad_x);
  auto dY = EigenVector<T>::Flatten(*grad_y);

  auto& place = *dev_ctx.eigen_device();
  auto& dropout_implementation = mode;
  if (is_test == true) {
    if (dropout_implementation == "upscale_in_train") {
      dX.device(place) = static_cast<T>(1) * dY;
    } else {
      dX.device(place) = dY * static_cast<T>(1.0f - p);
    }
  } else {
    auto M = EigenVector<uint8_t>::Flatten(mask);
    if (dropout_implementation == "upscale_in_train") {
      if (p == 1.0f) {
        dX.device(place) = static_cast<T>(0) * dY;
      } else {
        dX.device(place) = dY * M.cast<T>() / static_cast<T>(1.0f - p);
      }
    } else {
      dX.device(place) = dY * M.cast<T>();
    }
  }
}

}  // namespace phi

PD_REGISTER_KERNEL(dropout_grad,
                   CPU,
                   ALL_LAYOUT,
                   phi::DropoutGradRawKernel,
                   float,
                   double,
                   phi::dtype::bfloat16) {}