/**
 * Copyright (c) 2017-present, Facebook, Inc.
 *
 * 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 "caffe2/contrib/gloo/common.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/types.h"

#include <gloo/algorithm.h>
#include <gloo/common/error.h>
#include <gloo/context.h>

namespace caffe2 {
namespace gloo {

template <class Context>
class AllgatherOp final : public Operator<Context> {
 public:
  USE_OPERATOR_CONTEXT_FUNCTIONS;

  AllgatherOp(const OperatorDef& operator_def, Workspace* ws)
      : Operator<Context>(operator_def, ws),
        ws_(ws),
        status_blob_(
            OperatorBase::GetSingleArgument<std::string>("status_blob", "")) {
    if (status_blob_ != "") {
      ws_->CreateBlob(status_blob_);
    }
  }

  virtual ~AllgatherOp() {}

  bool RunOnDevice() override {
    std::call_once(once_, [&] { initialize(); });

    // If any parameter has changed in between runs, the initialized
    // algorithm is invalid and cannot be used.
    update(current_);
    CAFFE_ENFORCE(current_ == init_, "Inputs/outputs have changed");

    try {
      algorithm_->run();
    } catch (::gloo::IoException& ioe) {
      LOG(ERROR) << "Caught gloo IO exception: " << ioe.what();
      if (status_blob_ != "") {
        signalFailure(ws_->GetBlob(status_blob_), ioe);
        return false;
      } else {
        throw;
      }
    }
    return true;
  }

 protected:
  void initialize() {
    // Allocate output tensor
    CAFFE_ENFORCE_EQ(OutputSize(), 1);
    auto comm_size =
        OperatorBase::Input<std::shared_ptr<::gloo::Context>>(0)->size;
    const auto dims = std::vector<int64_t>(
        1, (InputSize() - 1) * Input(1).numel() * comm_size);
    Output(0)->Resize(dims);

    // Store which inputs/outputs this instance initialized with
    update(init_);

    CAFFE_ENFORCE_EQ(init_.outputs.size(), 1);

    // Verify tensors all have same size
    size_t size = Input(1).numel();
    for (auto i = 2; i < InputSize(); i++) {
      CAFFE_ENFORCE_EQ(Input(i).numel(), size);
    }

    // Verify tensors all have same type
    TypeMeta meta = Input(1).dtype();
    for (auto i = 2; i < InputSize(); i++) {
      CAFFE_ENFORCE(Input(i).dtype() == meta);
    }

    // Finally initialize the algorithm
    initializeAlgorithm();
  }

  void initializeAlgorithm();

  std::once_flag once_;
  std::unique_ptr<::gloo::Algorithm> algorithm_;

  // Captures the parameters passed to Gloo when first initialized.
  // An instance is updated every time this op runs and is compared
  // to the reference instance for equality. If any parameter has
  // changed from run to run, the initialized algorithm is invalid.
  void update(GlooParameters& params) {
    params.context = OperatorBase::Input<std::shared_ptr<::gloo::Context>>(0);
    params.inputs.resize(InputSize() - 1);
    params.size = Input(1).numel();
    params.meta = Input(1).dtype();
    for (auto i = 0; i < params.inputs.size(); i++) {
      params.inputs[i] = Input(i + 1).raw_data();
    }
    params.outputs.resize(OutputSize());
    params.outputs[0] = Output(0)->raw_mutable_data(params.meta);
  }

  GlooParameters init_;
  GlooParameters current_;
  Workspace* ws_;
  std::string status_blob_;
};

} // namespace gloo
} // namespace caffe2
