/* 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/sparse/full_kernel.h"

#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/tensor_utils.h"
#include "paddle/phi/kernels/funcs/elementwise_base.h"

namespace phi {

template <typename InT, typename OutT = InT>
struct FullFunctor {
  OutT value;

  template <typename VType>
  explicit inline FullFunctor(VType val) {
    value = static_cast<OutT>(val);
  }

  __device__ __forceinline__ OutT operator()() const {
    return static_cast<OutT>(value);
  }
};

template <typename T, typename Context>
void FullLikeCooKernel(const Context& dev_ctx,
                       const SparseCooTensor& x,
                       const Scalar& val,
                       DataType dtype,
                       SparseCooTensor* out) {
  phi::Copy<Context>(
      dev_ctx, x.indices(), dev_ctx.GetPlace(), false, out->mutable_indices());

  DenseTensor* values = out->mutable_values();
  values->Resize(x.values().dims());
  dev_ctx.template Alloc<T>(values);

  std::vector<const DenseTensor*> inputs = {};
  std::vector<DenseTensor*> outputs = {values};
  int numel = values->numel();
  if (numel > 0) {
    phi::funcs::ElementwiseKernel<T>(
        dev_ctx, inputs, &outputs, FullFunctor<T>(val.to<T>()));
  }
  out->set_dims(x.dims());
}

template <typename T, typename Context>
void FullLikeCsrKernel(const Context& dev_ctx,
                       const SparseCsrTensor& x,
                       const Scalar& val,
                       DataType dtype,
                       SparseCsrTensor* out) {
  phi::Copy<Context>(
      dev_ctx, x.crows(), dev_ctx.GetPlace(), false, out->mutable_crows());

  phi::Copy<Context>(
      dev_ctx, x.cols(), dev_ctx.GetPlace(), false, out->mutable_cols());

  DenseTensor* values = out->mutable_values();
  values->Resize(x.values().dims());
  dev_ctx.template Alloc<T>(values);

  std::vector<const DenseTensor*> inputs = {};
  std::vector<DenseTensor*> outputs = {values};
  int numel = values->numel();
  if (numel > 0) {
    phi::funcs::ElementwiseKernel<T>(
        dev_ctx, inputs, &outputs, FullFunctor<T>(val.to<T>()));
  }
  out->set_dims(x.dims());
}

}  // namespace phi

PD_REGISTER_KERNEL(full_like_coo,
                   GPU,
                   ALL_LAYOUT,
                   phi::FullLikeCooKernel,
                   float,
                   double,
                   uint8_t,
                   int16_t,
                   int,
                   int64_t,
                   bool,
                   phi::dtype::bfloat16,
                   phi::dtype::float16,
                   phi::dtype::complex<float>,
                   phi::dtype::complex<double>) {
  kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
}

PD_REGISTER_KERNEL(full_like_csr,
                   GPU,
                   ALL_LAYOUT,
                   phi::FullLikeCsrKernel,
                   float,
                   double,
                   uint8_t,
                   int16_t,
                   int,
                   int64_t,
                   bool,
                   phi::dtype::bfloat16,
                   phi::dtype::float16,
                   phi::dtype::complex<float>,
                   phi::dtype::complex<double>) {
  kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_CSR);
}