// Copyright 2018 The MACE 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.

#ifndef MACE_CORE_MEMORY_OPTIMIZER_H_
#define MACE_CORE_MEMORY_OPTIMIZER_H_

#include <set>
#include <string>
#include <unordered_map>
#include <utility>
#include <vector>

#include "mace/proto/mace.pb.h"
#include "mace/port/port.h"
#include "mace/core/types.h"

namespace mace {

class MemoryBlock {
 public:
  inline void set_mem_id(int mem_id) {
    mem_id_ = mem_id;
  }

  inline int mem_id() const {
    return mem_id_;
  }

  inline void set_data_type(DataType data_type) {
    data_type_ = data_type;
  }

  inline DataType data_type() const {
    return data_type_;
  }

  inline void set_mem_type(MemoryType mem_type) {
    mem_type_ = mem_type;
  }

  inline MemoryType mem_type() const {
    return mem_type_;
  }

  inline void set_x(int64_t x) {
    x_ = x;
  }

  inline int64_t x() const {
    return x_;
  }

  inline void set_y(int64_t y) {
    y_ = y;
  }

  inline int64_t y() const {
    return y_;
  }

 private:
  int mem_id_;
  DataType data_type_;
  MemoryType mem_type_;
  int64_t x_;
  int64_t y_;
};

class MemoryOptimizer {
 public:
  struct TensorMemInfo {
    int mem_id;
    DataType data_type;
    DataFormat data_format;

    TensorMemInfo(int mem_id, DataType data_type, DataFormat data_format) :
        mem_id(mem_id), data_type(data_type), data_format(data_format)
    {}
  };

 public:
  static bool IsMemoryReuseOp(const std::string &op_type,
                              const MemoryType mem_type);
  void UpdateTensorRef(const std::string &tensor_name);
  void UpdateTensorRef(const OperatorDef *op_def);
  virtual void Optimize(
      const OperatorDef *op_def,
      const std::unordered_map<std::string, MemoryType> *mem_types);

  const std::vector<MemoryBlock> &mem_blocks() const;

  const std::unordered_map<std::string, TensorMemInfo> &tensor_mem_map() const;

  std::string DebugInfo() const;

 private:
  MemoryBlock CreateMemoryBlock(
      const OperatorDef *op_def,
      int output_idx,
      DataType dt,
      MemoryType mem_type);

 private:
  std::unordered_map<std::string, int> tensor_ref_count_;
  std::vector<MemoryBlock> mem_blocks_;
  // tensor name : <mem_id, data_type>
  // Buffer Memory do not different data type, so store the data type.
  std::unordered_map<std::string, TensorMemInfo> tensor_mem_map_;
  std::unordered_map<int, int> mem_ref_count_;
  std::set<int> idle_blocks_;
};

}  // namespace mace
#endif  // MACE_CORE_MEMORY_OPTIMIZER_H_
