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buffer_pool_mem_assigner.h 2.7 kB

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  1. /**
  2. * Copyright 2020 Huawei Technologies Co., Ltd
  3. *
  4. * Licensed under the Apache License, Version 2.0 (the "License");
  5. * you may not use this file except in compliance with the License.
  6. * You may obtain a copy of the License at
  7. *
  8. * http://www.apache.org/licenses/LICENSE-2.0
  9. *
  10. * Unless required by applicable law or agreed to in writing, software
  11. * distributed under the License is distributed on an "AS IS" BASIS,
  12. * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13. * See the License for the specific language governing permissions and
  14. * limitations under the License.
  15. */
  16. #ifndef GE_GRAPH_BUILD_MEMORY_BUFFER_POOL_MEM_ASSIGNER_H_
  17. #define GE_GRAPH_BUILD_MEMORY_BUFFER_POOL_MEM_ASSIGNER_H_
  18. #include <vector>
  19. #include <map>
  20. #include <unordered_map>
  21. #include "graph/build/memory/mem_assigner.h"
  22. #include "runtime/mem.h"
  23. namespace ge {
  24. class BufferPoolMemAssigner : public MemAssigner {
  25. public:
  26. BufferPoolMemAssigner(ComputeGraphPtr compute_graph, const std::map<int64_t, size_t> &mem_type_to_offset)
  27. : MemAssigner(), compute_graph_(compute_graph),
  28. mem_type_(0),
  29. mem_offset_(0),
  30. mem_offset_base_(0),
  31. init_offset_base_(false),
  32. mem_type_to_offset_(mem_type_to_offset) {}
  33. BufferPoolMemAssigner(const BufferPoolMemAssigner &) = delete;
  34. BufferPoolMemAssigner &operator=(const BufferPoolMemAssigner &) = delete;
  35. ~BufferPoolMemAssigner() override = default;
  36. Status Assign() override;
  37. size_t GetMemOffset() const { return mem_offset_; }
  38. int64_t GetMemType() const { return mem_type_; }
  39. private:
  40. static Status GetOutputMemoryType(const NodePtr &node, size_t idx, int64_t &memory_type);
  41. Status InitAssigner(const ComputeGraphPtr &graph);
  42. Status InitMemOffsetBase(const NodePtr &node);
  43. Status AssignOutput();
  44. Status AssignOutputInOneBufferPool(const std::string &batch_label,
  45. int64_t output_offset_base,
  46. const std::vector<NodePtr> &buffer_pool_nodes);
  47. ComputeGraphPtr compute_graph_;
  48. int64_t mem_type_;
  49. size_t mem_offset_;
  50. int64_t mem_offset_base_;
  51. bool init_offset_base_;
  52. std::map<int64_t, size_t> mem_type_to_offset_;
  53. // Use map to ensure that each visit is in the order of pool id
  54. std::unordered_map<std::string, std::map<int64_t, std::vector<NodePtr>>> buffer_pool_nodes_;
  55. // Use map to ensure that each visit is in the order of pool id
  56. std::unordered_map<std::string, std::map<int64_t, int64_t>> buffer_pool_size_;
  57. std::unordered_map<std::string, std::unordered_map<int64_t, int64_t>> buffer_pool_offset_base_;
  58. };
  59. } // namespace ge
  60. #endif // GE_GRAPH_BUILD_MEMORY_BUFFER_POOL_MEM_ASSIGNER_H_

图引擎模块(GE)是MindSpore的一个子模块,其代码由C++实现,位于前端模块ME和底层硬件之间,起到承接作用。图引擎模块以ME下发的图作为输入,然后进行一系列的深度图优化操作,最后输出一张可以在底层硬件上高效运行的图。GE针对昇腾AI处理器的硬件结构特点,做了特定的优化工作,以此来充分发挥出昇腾AI处理器的强大算力。在进行模型训练/推理时,GE会被自动调用而用户并不感知。GE主要由GE API和GE Core两部分组成,详细的架构图如下所示