// 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/bce_loss_kernel.h"

#include <algorithm>
#include <vector>

#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/common/amp_type_traits.h"
#include "paddle/phi/common/float16.h"
#include "paddle/phi/core/hostdevice.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/elementwise_base.h"
#include "paddle/phi/kernels/primitive/functor_primitives.h"

namespace phi {

template <typename T>
struct BCELossFunctor {
  using MT = typename phi::dtype::MPTypeTrait<T>::Type;
  MT zero = static_cast<MT>(0);
  MT one = static_cast<MT>(1.0f);
  MT neg_100 = static_cast<MT>(-100.);

  HOSTDEVICE inline T operator()(const T x, const T label) const {
    MT x_mt = static_cast<MT>(x);
    MT label_mt = static_cast<MT>(label);

    PADDLE_ENFORCE(
        (x_mt >= zero) && (x_mt <= one),
        "Input is expected to be within the interval [0, 1], but received %f.",
        x_mt);

    MT term1 = max(phi::kps::details::Log(x_mt), neg_100);
    MT term2 = max(phi::kps::details::Log(one - x_mt), neg_100);
    return static_cast<T>((label_mt - one) * term2 - label_mt * term1);
  }
};

template <typename T, typename Context>
void BCELossKernel(const Context& dev_ctx,
                   const DenseTensor& input,
                   const DenseTensor& label,
                   DenseTensor* out) {
  dev_ctx.template Alloc<T>(out);
  std::vector<const DenseTensor*> ins = {&input, &label};
  std::vector<DenseTensor*> outs = {out};
  auto functor = BCELossFunctor<T>();
  phi::funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
}

}  // namespace phi

PD_REGISTER_KERNEL(bce_loss,
                   GPU,
                   ALL_LAYOUT,
                   phi::BCELossKernel,
                   float,
                   double,
                   phi::dtype::float16) {}