/* 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/api/lib/tensor_copy.h"

#include "glog/logging.h"

#include "paddle/phi/api/include/context_pool.h"
#include "paddle/phi/api/lib/api_gen_utils.h"
#include "paddle/phi/api/lib/kernel_dispatch.h"
#include "paddle/phi/core/compat/convert_utils.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/meta_tensor.h"
#include "paddle/phi/core/tensor_utils.h"
#include "paddle/phi/infermeta/unary.h"
#ifdef PADDLE_WITH_DISTRIBUTE
#include "paddle/phi/api/lib/data_transform.h"
#include "paddle/phi/core/distributed/auto_parallel/reshard/reshard_utils.h"
#include "paddle/phi/infermeta/spmd_rules/rules.h"
#endif
namespace paddle {
namespace experimental {

void copy(const Tensor& src, const Place& place, bool blocking, Tensor* dst) {
  auto kernel_key_set = ParseKernelKeyByInputArgs(src);
  kernel_key_set.backend_set =
      kernel_key_set.backend_set | BackendSet(phi::TransToPhiBackend(place));
  auto kernel_key = kernel_key_set.GetHighestPriorityKernelKey();

  VLOG(6) << "start copy. ";

  auto target_place = phi::TransToPhiPlace(kernel_key.backend());
  auto& pool = paddle::experimental::DeviceContextPool::Instance();
  auto* dev_ctx = pool.GetMutable(
      target_place.GetType() == place.GetType() ? place : target_place);
#ifdef PADDLE_WITH_DISTRIBUTE
  bool run_auto_parallel = AllInputsAreDistTensor(src);
  bool rank_is_in_current_mesh = false;
  if (run_auto_parallel) {
    auto mesh =
        std::static_pointer_cast<phi::distributed::DistTensor>(src.impl())
            ->dist_attr()
            .process_mesh();
    rank_is_in_current_mesh = phi::distributed::IsCurRankInMesh(mesh);

    auto meta_dist_input_x = MakeDistMetaTensor(*src.impl());

    auto dist_out = SetKernelDistOutput(dst, meta_dist_input_x.dist_attr());
    auto dense_out = dist_out->unsafe_mutable_value();
    if (!rank_is_in_current_mesh) {
      *dense_out =
          phi::DenseTensor(std::make_shared<phi::Allocation>(
                               nullptr, 0, phi::distributed::GetDefaultPlace()),
                           phi::DenseTensorMeta());
    }

    phi::MetaTensor meta_dist_out(dist_out);
    phi::UnchangedInferMeta(MakeMetaTensor(*(src.impl())), &meta_dist_out);

    if (rank_is_in_current_mesh) {
      auto dist_input_x =
          static_cast<phi::distributed::DistTensor*>(src.impl().get());

      auto input_x = &dist_input_x->value();

      phi::MetaTensor meta_dense_out(dense_out);
      phi::UnchangedInferMeta(MakeMetaTensor(*input_x), &meta_dense_out);

      phi::Copy(*dev_ctx, *input_x, place, blocking, dense_out);
    }
    VLOG(6) << "copy finished. ";
    return;
  }
#endif
  auto dense_x = TensorToDenseTensor(src);

  auto kernel_out = SetKernelOutput(dst);
  phi::MetaTensor meta_out(kernel_out);
  phi::UnchangedInferMeta(*dense_x, &meta_out);

  phi::Copy(*dev_ctx, *dense_x, place, blocking, kernel_out);

  VLOG(6) << "copy finished. ";
}

}  // namespace experimental
}  // namespace paddle