// 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/backends/gpu/gpu_context.h"
#ifndef PADDLE_WITH_XPU_KP
#include "paddle/phi/common/complex.h"
#include "paddle/phi/common/float16.h"
#endif
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/elementwise_kernel_impl.h"
#include "paddle/phi/kernels/legacy/elementwise_kernel.h"

namespace phi {

template <typename T, typename Context>
void MaximumKernel(const Context& dev_ctx,
                   const DenseTensor& x,
                   const DenseTensor& y,
                   DenseTensor* out) {
  int axis = -1;
  MaximumRawKernel<T>(dev_ctx, x, y, axis, out);
}

template <typename T, typename Context>
void MinimumKernel(const Context& dev_ctx,
                   const DenseTensor& x,
                   const DenseTensor& y,
                   DenseTensor* out) {
  int axis = -1;
  MinimumRawKernel<T>(dev_ctx, x, y, axis, out);
}

template <typename T, typename Context>
void RemainderKernel(const Context& dev_ctx,
                     const DenseTensor& x,
                     const DenseTensor& y,
                     DenseTensor* out) {
  int axis = -1;
  RemainderRawKernel<T>(dev_ctx, x, y, axis, out);
}

template <typename T, typename Context>
void FloorDivideKernel(const Context& dev_ctx,
                       const DenseTensor& x,
                       const DenseTensor& y,
                       DenseTensor* out) {
  int axis = -1;
  FloorDivideRawKernel<T>(dev_ctx, x, y, axis, out);
}
// Create the definition of Heaviside
template <typename T, typename Context>
void HeavisideKernel(const Context& dev_ctx,
                     const DenseTensor& x,
                     const DenseTensor& y,
                     DenseTensor* out) {
  std::vector<const DenseTensor*> inputs;
  inputs.reserve(2);
  std::vector<DenseTensor*> outputs;
  outputs.reserve(1);
  inputs.emplace_back(&x);
  inputs.emplace_back(&y);
  outputs.emplace_back(out);
  dev_ctx.template Alloc<T>(out);
  funcs::BroadcastKernel<T>(
      dev_ctx, inputs, &outputs, funcs::ElementwiseHeavisideFunctor<T>());
}

template <typename T, typename Context>
void ElementwisePowKernel(const Context& dev_ctx,
                          const DenseTensor& x,
                          const DenseTensor& y,
                          DenseTensor* out) {
  int axis = -1;
  ElementwisePowRawKernel<T>(dev_ctx, x, y, axis, out);
}

}  // namespace phi

#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)

PD_REGISTER_KERNEL(maximum,
                   KPS,
                   ALL_LAYOUT,
                   phi::MaximumKernel,
                   float,
                   double,
                   int,
                   int64_t,
                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(minimum,
                   KPS,
                   ALL_LAYOUT,
                   phi::MinimumKernel,
                   float,
                   double,
                   int,
                   int64_t,
                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(remainder,
                   GPU,
                   ALL_LAYOUT,
                   phi::RemainderKernel,
                   float,
                   double,
                   int,
                   int64_t,
                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(floor_divide,
                   KPS,
                   ALL_LAYOUT,
                   phi::FloorDivideKernel,
                   uint8_t,
                   int8_t,
                   int16_t,
                   int,
                   int64_t,
                   float,
                   double,
                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(elementwise_pow,
                   KPS,
                   ALL_LAYOUT,
                   phi::ElementwisePowKernel,
                   float,
                   double,
                   int,
                   int64_t,
                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}

#endif

#ifdef PADDLE_WITH_XPU_KP
PD_REGISTER_KERNEL(maximum, KPS, ALL_LAYOUT, phi::MaximumKernel, float) {}
PD_REGISTER_KERNEL(minimum, KPS, ALL_LAYOUT, phi::MinimumKernel, float) {}
PD_REGISTER_KERNEL(floor_divide, KPS, ALL_LAYOUT, phi::FloorDivideKernel, int) {
}
PD_REGISTER_KERNEL(
    elementwise_pow, KPS, ALL_LAYOUT, phi::ElementwisePowKernel, float) {}

#else
using float16 = phi::dtype::float16;
using bfloat16 = phi::dtype::bfloat16;
using complex64 = ::phi::dtype::complex<float>;
using complex128 = ::phi::dtype::complex<double>;

PD_REGISTER_KERNEL(fmax,
                   KPS,
                   ALL_LAYOUT,
                   phi::FMaxKernel,
                   float,
                   double,
                   int,
                   float16,
                   bfloat16,
                   int64_t) {}

PD_REGISTER_KERNEL(fmin,
                   KPS,
                   ALL_LAYOUT,
                   phi::FMinKernel,
                   float,
                   double,
                   int,
                   float16,
                   bfloat16,
                   int64_t) {}

PD_REGISTER_KERNEL(heaviside,
                   KPS,
                   ALL_LAYOUT,
                   phi::HeavisideKernel,
                   float,
                   double,
                   int,
                   float16,
                   bfloat16,
                   int64_t) {}
#endif
