/* 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 <vector>

#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/tensor.h"

namespace paddle {
namespace framework {

class SelectedRows {
 public:
  SelectedRows(const std::vector<int64_t>& rows, const int64_t& height)
      : rows_(rows), height_(height) {
    value_.reset(new Tensor());
  }

  SelectedRows() {
    height_ = 0;
    value_.reset(new Tensor());
  }

  platform::Place place() const { return value_->place(); }

  const Tensor& value() const { return *value_; }

  Tensor* mutable_value() { return value_.get(); }

  int64_t height() const { return height_; }

  void set_height(int64_t height) { height_ = height; }

  const Vector<int64_t>& rows() const { return rows_; }

  Vector<int64_t>* mutable_rows() { return &rows_; }

  void set_rows(const Vector<int64_t>& rows) { rows_ = rows; }

  /**
   * get the index of id in rows
   */
  int64_t index(int64_t id) const {
    auto it = std::find(rows_.begin(), rows_.end(), id);
    PADDLE_ENFORCE(it != rows_.end(), "id should be in rows");
    return static_cast<int64_t>(std::distance(rows_.begin(), it));
  }

  DDim GetCompleteDims() const {
    std::vector<int64_t> dims = vectorize(value_->dims());
    dims[0] = height_;
    return make_ddim(dims);
  }

 private:
  // Notice: rows can be duplicate. We can have {0, 4, 7, 0, 5, 7, 9} here.
  // SelectedRows are simply concated when adding together. Until a
  // SelectedRows add a Tensor, will the duplicate rows be handled.
  Vector<int64_t> rows_;
  std::unique_ptr<Tensor> value_{nullptr};
  int64_t height_;
};

/*
 * Serialize/Desiralize SelectedRows to std::ostream
 * You can pass ofstream or ostringstream to serilize to file
 * or to a in memory string. GPU tensor will be copied to CPU.
 */
void SerializeToStream(std::ostream& os, const SelectedRows& selected_rows,
                       const platform::DeviceContext& dev_ctx);
void DeserializeFromStream(std::istream& is, SelectedRows* selected_rows,
                           const platform::DeviceContext& dev_ctx);

}  // namespace framework
}  // namespace paddle
