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tensor_adapter.h 1.8 kB

5 years ago
5 years ago
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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 INC_GRAPH_UTILS_TENSOR_ADAPTER_H_
  17. #define INC_GRAPH_UTILS_TENSOR_ADAPTER_H_
  18. #include <memory>
  19. #include "graph/ge_tensor.h"
  20. #include "graph/tensor.h"
  21. namespace ge {
  22. using GeTensorPtr = std::shared_ptr<GeTensor>;
  23. using ConstGeTensorPtr = std::shared_ptr<const GeTensor>;
  24. class GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY TensorAdapter {
  25. public:
  26. static GeTensorDesc TensorDesc2GeTensorDesc(const TensorDesc &tensorDesc);
  27. static TensorDesc GeTensorDesc2TensorDesc(const GeTensorDesc &geTensorDesc);
  28. static GeTensorPtr Tensor2GeTensor(const Tensor &tensor);
  29. static Tensor GeTensor2Tensor(const ConstGeTensorPtr &geTensor);
  30. static ConstGeTensorPtr AsGeTensorPtr(const Tensor &tensor); // Share value
  31. static GeTensorPtr AsGeTensorPtr(Tensor &tensor); // Share value
  32. static const GeTensor AsGeTensor(const Tensor &tensor); // Share value
  33. static GeTensor AsGeTensor(Tensor &tensor); // Share value
  34. static const Tensor AsTensor(const GeTensor &tensor); // Share value
  35. static Tensor AsTensor(GeTensor &tensor); // Share value
  36. };
  37. } // namespace ge
  38. #endif // INC_GRAPH_UTILS_TENSOR_ADAPTER_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