/* Copyright (c) 2018 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. */

#pragma once
#include <algorithm>
#include <utility>
#include <vector>

#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/op_registry.h"

#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/nccl_helper.h"
#endif

namespace paddle {
namespace operators {

template <typename DeviceContext, typename T>
class AllReduceOpKernel : public framework::OpKernel<T> {
 public:
  void Compute(const framework::ExecutionContext& ctx) const override {
    auto place = ctx.GetPlace();
    PADDLE_ENFORCE_EQ(is_gpu_place(place), true,
                      platform::errors::PreconditionNotMet(
                          "AllReduce op can run on gpu place only for now."));
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
    auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
    auto in = ctx.Input<framework::Tensor>("X");
    auto out = ctx.Output<framework::Tensor>("Out");

    int dtype = platform::ToNCCLDataType(in->type());
    int64_t numel = in->numel();
    auto* sendbuff = in->data<void>();
    out->Resize(in->dims());
    void* recvbuff = out->mutable_data<T>(place);

    auto* comm = dev_ctx.nccl_comm();
    // FIXME(typhoonzero): should use nccl stream here.
    auto stream = dev_ctx.stream();
    PADDLE_ENFORCE_NOT_NULL(
        stream, platform::errors::NotFound("Should initialize NCCL firstly."));

    int reduce_type = ctx.Attr<int>("reduce_type");
    ncclRedOp_t red_type = ncclSum;
    switch (reduce_type) {
      case 0:
        red_type = ncclSum;
        break;
      case 1:
        red_type = ncclProd;
        break;
      case 2:
        red_type = ncclMax;
        break;
      case 3:
        red_type = ncclMin;
        break;
    }
    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
        sendbuff, recvbuff, numel, static_cast<ncclDataType_t>(dtype), red_type,
        comm, stream));
    if (ctx.Attr<bool>("sync_mode")) {
#ifdef PADDLE_WITH_RCCL
      PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
#else
      PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
#endif
    }
#else
    PADDLE_THROW(platform::errors::PreconditionNotMet(
        "PaddlePaddle should compile with GPU."));
#endif
  }
};

}  // namespace operators
}  // namespace paddle
