You can not select more than 25 topics Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.

dnnengines.cc 3.3 kB

5 years ago
4 years ago
5 years ago
4 years ago
5 years ago
4 years ago
5 years ago
4 years ago
5 years ago
5 years ago
4 years ago
5 years ago
12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576777879808182838485
  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 "plugin/engine/dnnengines.h"
  17. #include <string>
  18. namespace ge {
  19. AICoreDNNEngine::AICoreDNNEngine(const std::string &engine_name) {
  20. engine_attribute_.engine_name = engine_name;
  21. engine_attribute_.compute_cost = COST_0;
  22. engine_attribute_.runtime_type = DEVICE;
  23. engine_attribute_.engine_input_format = FORMAT_RESERVED;
  24. engine_attribute_.engine_output_format = FORMAT_RESERVED;
  25. }
  26. VectorCoreDNNEngine::VectorCoreDNNEngine(const std::string &engine_name) {
  27. engine_attribute_.engine_name = engine_name;
  28. engine_attribute_.compute_cost = COST_1;
  29. engine_attribute_.runtime_type = DEVICE;
  30. engine_attribute_.engine_input_format = FORMAT_RESERVED;
  31. engine_attribute_.engine_output_format = FORMAT_RESERVED;
  32. }
  33. AICpuDNNEngine::AICpuDNNEngine(const std::string &engine_name) {
  34. engine_attribute_.engine_name = engine_name;
  35. engine_attribute_.compute_cost = COST_2;
  36. engine_attribute_.runtime_type = DEVICE;
  37. engine_attribute_.engine_input_format = FORMAT_RESERVED;
  38. engine_attribute_.engine_output_format = FORMAT_RESERVED;
  39. }
  40. AICpuTFDNNEngine::AICpuTFDNNEngine(const std::string &engine_name) {
  41. engine_attribute_.engine_name = engine_name;
  42. engine_attribute_.compute_cost = COST_3;
  43. engine_attribute_.runtime_type = DEVICE;
  44. engine_attribute_.engine_input_format = FORMAT_RESERVED;
  45. engine_attribute_.engine_output_format = FORMAT_RESERVED;
  46. }
  47. GeLocalDNNEngine::GeLocalDNNEngine(const std::string &engine_name) {
  48. engine_attribute_.engine_name = engine_name;
  49. engine_attribute_.engine_input_format = FORMAT_RESERVED;
  50. engine_attribute_.engine_output_format = FORMAT_RESERVED;
  51. }
  52. HostCpuDNNEngine::HostCpuDNNEngine(const std::string &engine_name) {
  53. engine_attribute_.engine_name = engine_name;
  54. engine_attribute_.compute_cost = COST_10;
  55. engine_attribute_.runtime_type = HOST;
  56. engine_attribute_.engine_input_format = FORMAT_RESERVED;
  57. engine_attribute_.engine_output_format = FORMAT_RESERVED;
  58. }
  59. RtsDNNEngine::RtsDNNEngine(const std::string &engine_name) {
  60. engine_attribute_.engine_name = engine_name;
  61. engine_attribute_.engine_input_format = FORMAT_RESERVED;
  62. engine_attribute_.engine_output_format = FORMAT_RESERVED;
  63. }
  64. HcclDNNEngine::HcclDNNEngine(const std::string &engine_name) {
  65. engine_attribute_.engine_name = engine_name;
  66. engine_attribute_.engine_input_format = FORMAT_RESERVED;
  67. engine_attribute_.engine_output_format = FORMAT_RESERVED;
  68. }
  69. FftsPlusDNNEngine::FftsPlusDNNEngine(const std::string &engine_name) {
  70. engine_attribute_.engine_name = engine_name;
  71. engine_attribute_.engine_input_format = FORMAT_RESERVED;
  72. engine_attribute_.engine_output_format = FORMAT_RESERVED;
  73. }
  74. } // 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