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tensor_value.h 2.6 kB

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  1. /**
  2. * Copyright 2019-2020 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_HYBRID_COMMON_TENSOR_VALUE_H_
  17. #define GE_HYBRID_COMMON_TENSOR_VALUE_H_
  18. #include <atomic>
  19. #include <cstddef>
  20. #include <memory>
  21. #include "memory/memory_api.h"
  22. #include "framework/common/util.h"
  23. namespace ge {
  24. namespace hybrid {
  25. class NpuMemoryAllocator;
  26. class AllocationAttr;
  27. class TensorBuffer {
  28. public:
  29. static std::unique_ptr<TensorBuffer> Create(NpuMemoryAllocator *allocator,
  30. size_t size,
  31. AllocationAttr *attr = nullptr);
  32. static std::unique_ptr<TensorBuffer> Create(void *buffer, size_t size);
  33. TensorBuffer(const TensorBuffer &) = delete;
  34. TensorBuffer &operator = (const TensorBuffer &) = delete;
  35. ~TensorBuffer();
  36. void *GetData() {
  37. return buffer_;
  38. }
  39. size_t GetSize() const {
  40. return size_;
  41. }
  42. private:
  43. TensorBuffer(NpuMemoryAllocator *allocator, void *buffer, size_t size, MemStorageType mem_type = HBM);
  44. NpuMemoryAllocator *allocator_ = nullptr;
  45. void *buffer_ = nullptr;
  46. size_t size_ = 0;
  47. MemStorageType mem_type_;
  48. };
  49. class TensorValue {
  50. public:
  51. TensorValue() = default;
  52. explicit TensorValue(std::shared_ptr<TensorBuffer> buffer);
  53. TensorValue(void *buffer, size_t size);
  54. ~TensorValue();
  55. void Destroy();
  56. bool IsEmpty() {
  57. return ref_buffer_ == nullptr && buffer_ == nullptr;
  58. }
  59. const void *GetData() const;
  60. std::string DebugString() const;
  61. void SetName(const std::string &name) {
  62. name_ = name;
  63. }
  64. void *MutableData();
  65. size_t GetSize() const;
  66. template<typename T>
  67. Status CopyScalarValueToHost(T &value) const {
  68. GE_CHECK_GE(this->GetSize(), sizeof(value));
  69. return rtMemcpy(&value, sizeof(value), this->GetData(), sizeof(value), RT_MEMCPY_DEVICE_TO_HOST);
  70. }
  71. private:
  72. std::shared_ptr<TensorBuffer> buffer_;
  73. std::string name_;
  74. // for weights and variables
  75. void *ref_buffer_ = nullptr;
  76. size_t ref_size_ = 0;
  77. // shape
  78. };
  79. } // namespace hybrid
  80. } // namespace ge
  81. #endif // GE_HYBRID_COMMON_TENSOR_VALUE_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