// 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/core/dense_tensor.h"
#include "paddle/phi/core/device_context.h"
#include "paddle/phi/kernels/cast_kernel.h"
#include "paddle/phi/kernels/complex_kernel.h"
#include "paddle/phi/kernels/full_kernel.h"
#include "paddle/phi/kernels/funcs/complex_functors.h"
#include "paddle/phi/kernels/funcs/diag_functor.h"
#include "paddle/phi/kernels/funcs/math_function.h"
#include "paddle/phi/kernels/funcs/unsqueeze.h"
#include "paddle/phi/kernels/math_kernel.h"
#include "paddle/phi/kernels/matmul_kernel.h"
#include "paddle/phi/kernels/transpose_kernel.h"

#include "paddle/phi/kernels/funcs/eigen/common.h"
#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"

namespace phi {

template <typename T, typename Context>
void EighGradKernel(const Context& dev_ctx,
                    const DenseTensor& out_w,
                    const DenseTensor& out_v,
                    const DenseTensor& dout_w,
                    const DenseTensor& dout_v,
                    DenseTensor* dx) {
  dev_ctx.template Alloc<T>(dx);
  auto& dims = out_v.dims();
  const int m = dims[dims.size() - 1];
  DenseTensor tV =
      phi::TransposeLast2Dim<T>(dev_ctx, phi::Conj<T>(dev_ctx, out_v));
  DenseTensor W =
      phi::Subtract<phi::dtype::Real<T>>(dev_ctx,
                                         phi::funcs::Unsqueeze(out_w, -2),
                                         phi::funcs::Unsqueeze(out_w, -1));
  DenseTensor result = phi::Matmul<T>(dev_ctx, tV, dout_v);
  result.Resize(dims);
  dev_ctx.template Alloc<T>(&result);

  std::vector<int> out_shape = phi::vectorize<int>(dims);
  DenseTensor constant;
  constant.Resize(phi::make_ddim(out_shape));
  dev_ctx.template Alloc<T>(&constant);
  phi::funcs::SetConstant<Context, T>()(dev_ctx, &constant, T(0.5));
  result = phi::Subtract<T>(
      dev_ctx,
      result,
      phi::Conj<T>(dev_ctx, phi::TransposeLast2Dim<T>(dev_ctx, result)));
  result = phi::Multiply<T>(dev_ctx, result, constant);
  if (result.type() != W.type()) {
    auto x_vector = EigenVector<T>::Flatten(result);
    auto y_vector = EigenVector<phi::dtype::Real<T>>::Flatten(W);
    auto out_vector = EigenVector<T>::Flatten(result);
    auto& place = *dev_ctx.eigen_device();
    out_vector.device(place) = x_vector / y_vector;
  } else {
    result = phi::Divide<T>(dev_ctx, result, W);
  }
  result = phi::funcs::DiagFill<T, phi::dtype::Real<T>>(
      dev_ctx, m, m, m, 0, dout_w, result);
  *dx = phi::Matmul<T>(dev_ctx, out_v, phi::Matmul<T>(dev_ctx, result, tV));
}

}  // namespace phi