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.

mark_agnostic_pass.cc 2.8 kB

12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364
  1. /**
  2. * Copyright 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 "graph/passes/mark_agnostic_pass.h"
  17. #include "graph/utils/node_utils.h"
  18. namespace ge {
  19. Status MarkAgnosticPass::Run(ComputeGraphPtr graph) {
  20. for (const auto &node : graph->GetDirectNode()) {
  21. auto node_type = NodeUtils::GetNodeType(*node);
  22. if (node_type == SWITCH || node_type == SWITCHN) {
  23. GELOGD("Mark format agnostic and continuous for switch node %s", node->GetName().c_str());
  24. const OpDescPtr op_desc = node->GetOpDesc();
  25. const GeTensorDescPtr op_tensor = op_desc->MutableInputDesc(0);
  26. if (op_tensor == nullptr) {
  27. GELOGD("Op: %s, Index:0,has no input", node->GetName().c_str());
  28. continue;
  29. }
  30. AttrUtils::SetInt(op_tensor, "_format_continuous", 1);
  31. AttrUtils::SetInt(node->GetOpDesc(), "_format_agnostic", 1);
  32. AttrUtils::SetListInt(node->GetOpDesc(), "_format_agnostic_except_input", std::vector<int64_t>({1}));
  33. continue;
  34. }
  35. if (node_type == IDENTITY) {
  36. GELOGD("Mark format agnostic for identity node %s", node->GetName().c_str());
  37. AttrUtils::SetInt(node->GetOpDesc(), "_format_agnostic", 1);
  38. continue;
  39. }
  40. if (node_type == REFMERGE || node_type == REFSWITCH) {
  41. GELOGD("Mark format agnostic for regmerge and refswitch node %s", node->GetName().c_str());
  42. AttrUtils::SetInt(node->GetOpDesc(), "_format_agnostic", 1);
  43. AttrUtils::SetListInt(node->GetOpDesc(), "_format_agnostic_except_input", std::vector<int64_t>({1}));
  44. continue;
  45. }
  46. if (node_type == MERGE) {
  47. GELOGD("Mark format agnostic and continuous for merge node %s", node->GetName().c_str());
  48. const OpDescPtr op_desc = node->GetOpDesc();
  49. const GeTensorDescPtr op_tensor = op_desc->MutableOutputDesc(0);
  50. if (op_tensor == nullptr) {
  51. GELOGD("Op: %s, Index:0,has no output", node->GetName().c_str());
  52. continue;
  53. }
  54. AttrUtils::SetInt(op_tensor, "_format_continuous", 1);
  55. AttrUtils::SetInt(node->GetOpDesc(), "_format_agnostic", 1);
  56. AttrUtils::SetListInt(node->GetOpDesc(), "_format_agnostic_except_output", std::vector<int64_t>({1}));
  57. continue;
  58. }
  59. }
  60. return SUCCESS;
  61. }
  62. } // 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