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inner_session_unittest.cc 1.9 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. #include <gtest/gtest.h>
  17. #define private public
  18. #define protected public
  19. #include "session/inner_session.h"
  20. using namespace std;
  21. namespace ge {
  22. class UtestInnerSession : public testing::Test {
  23. protected:
  24. void SetUp() override {}
  25. void TearDown() override {}
  26. };
  27. TEST_F(UtestInnerSession, build_graph_success) {
  28. std::map <string, string> options;
  29. uint64_t session_id = 1;
  30. InnerSession inner_seesion(session_id, options);
  31. std::vector<ge::Tensor> inputs;
  32. ge::Tensor tensor;
  33. inputs.emplace_back(tensor);
  34. Status ret = inner_seesion.BuildGraph(1, inputs);
  35. EXPECT_NE(ret, ge::SUCCESS);
  36. }
  37. TEST_F(UtestInnerSession, initialize) {
  38. std::map<std::string, std::string> options = {};
  39. uint64_t session_id = 1;
  40. InnerSession inner_session(session_id, options);
  41. EXPECT_EQ(inner_session.Initialize(), SUCCESS);
  42. EXPECT_EQ(inner_session.Finalize(), SUCCESS);
  43. }
  44. TEST_F(UtestInnerSession, check_op_precision_mode) {
  45. std::map<std::string, std::string> options = {
  46. {ge::OP_PRECISION_MODE, "./op_precision_mode.ini"}
  47. };
  48. uint64_t session_id = 1;
  49. InnerSession inner_session(session_id, options);
  50. auto ret = inner_session.Initialize();
  51. EXPECT_NE(ret, ge::SUCCESS);
  52. }
  53. } // namespace ge

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