/* Copyright (c) 2020 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/fluid/operators/collective/send_v2_op.h"

namespace paddle {
namespace operators {

class SendOpV2 : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;

  void InferShape(framework::InferShapeContext* ctx) const override {
    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "SendV2");
    int peer = ctx->Attrs().Get<int>("peer");
    int ring_id = ctx->Attrs().Get<int>("ring_id");
    PADDLE_ENFORCE_GE(
        peer, 0,
        platform::errors::InvalidArgument(
            "The peer (%d) for send_v2 op must be non-negative.", peer));
    PADDLE_ENFORCE_GE(
        ring_id, 0,
        platform::errors::InvalidArgument(
            "The ring_id (%d) for send_v2 op must be non-negative.", ring_id));
  }

 protected:
  framework::OpKernelType GetExpectedKernelType(
      const framework::ExecutionContext& ctx) const override {
    const framework::Variable* var = ctx.InputVar("X");
    if (var->IsType<framework::LoDTensorArray>()) {
      auto t_arr = var->Get<framework::LoDTensorArray>();
      // NOTE(sandyhouse): Support an empty tensor array as Input.
      // And set the kernel type is float.
      if (t_arr.size() == 0) {
        return framework::OpKernelType(framework::proto::VarType::FP32,
                                       ctx.device_context());
      }
    }
    return framework::OpKernelType(
        OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
  }
};

class SendOpV2Maker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() {
    AddInput("X", "(Tensor) tensor to be sent.");
    AddAttr<int>("ring_id", "(int default 0) nccl communication ring id.")
        .SetDefault(0);
    AddAttr<int>("peer", "(int default 0) rank id for receiver.").SetDefault(0);
#if defined(PADDLE_WITH_ASCEND_CL)
    AddAttr<std::string>("tag", "(string default tag) tag for broadcasting.")
        .SetDefault("tag");
    AddAttr<int>("srTag", "(string default tag) tag for broadcasting.")
        .SetDefault(0);
#endif
    AddAttr<bool>(
        "use_calc_stream",
        "(bool default false) eject CUDA operations to calculation stream.")
        .SetDefault(false);
    AddComment(R"DOC(
Send Operator

Reference: https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/usage/p2p.html#sendrecv
)DOC");
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
namespace plat = paddle::platform;

REGISTER_OP_WITHOUT_GRADIENT(send_v2, ops::SendOpV2, ops::SendOpV2Maker);

REGISTER_OP_CPU_KERNEL(send_v2, ops::SendOpV2CPUKernel<float>,
                       ops::SendOpV2CPUKernel<double>,
                       ops::SendOpV2CPUKernel<int>,
                       ops::SendOpV2CPUKernel<int64_t>,
                       ops::SendOpV2CPUKernel<plat::float16>);