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gen_node.h 1.8 kB

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 UT_GE_Gen_Node_H_
  17. #define UT_GE_Gen_Node_H_
  18. #include <gtest/gtest.h>
  19. #include "common/debug/log.h"
  20. #include "common/debug/memory_dumper.h"
  21. #include "common/op/ge_op_utils.h"
  22. #include "common/types.h"
  23. #include "graph/compute_graph.h"
  24. #include "graph/op_desc.h"
  25. #include "graph/optimize/common/params.h"
  26. #include "graph/types.h"
  27. #include "graph/utils/attr_utils.h"
  28. #include "graph/utils/graph_utils.h"
  29. #include "graph/utils/op_desc_utils.h"
  30. #include "graph/utils/tensor_utils.h"
  31. #include "register/op_registry.h"
  32. static ge::NodePtr GenNodeFromOpDesc(ge::OpDescPtr op_desc);
  33. static ge::NodePtr GenNodeFromOpDesc(ge::OpDescPtr op_desc) {
  34. if (!op_desc) {
  35. return nullptr;
  36. }
  37. static auto g = std::make_shared<ge::ComputeGraph>("g");
  38. return g->AddNode(std::move(op_desc));
  39. }
  40. static void AddInputDesc(ge::OpDescPtr op_desc, int num) {
  41. for (int i = 0; i < num; ++i) {
  42. ge::GeTensorDesc tensor;
  43. tensor.SetFormat(ge::FORMAT_NCHW);
  44. tensor.SetShape(ge::GeShape({1, 1, 1, 1}));
  45. tensor.SetDataType(ge::DT_FLOAT);
  46. ge::TensorUtils::SetRealDimCnt(tensor, 4);
  47. op_desc->AddInputDesc(tensor);
  48. }
  49. }
  50. #endif // UT_GE_Gen_Node_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