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addn_pass.cc 1.4 kB

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  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/addn_pass.h"
  17. #include <vector>
  18. namespace ge {
  19. namespace {
  20. const size_t kInputSizeSingle = 1;
  21. } // namespace
  22. Status AddNPass::Run(NodePtr &node) {
  23. GELOGD("AddNPass running");
  24. if (node == nullptr) {
  25. GELOGE(PARAM_INVALID, "param [node] must not be null.");
  26. return PARAM_INVALID;
  27. }
  28. if (node->GetType() == ADDN) {
  29. if (node->GetOpDesc() == nullptr) {
  30. GELOGE(PARAM_INVALID, "Param [node] op desc is null.");
  31. return PARAM_INVALID;
  32. }
  33. // AddN with single input can be optimized
  34. if (node->GetOpDesc()->GetInputsSize() == kInputSizeSingle) {
  35. std::vector<int> io_map = {PassUtils::GetUniqueInDataAnchorIndex(node)};
  36. return IsolateAndDeleteNode(node, io_map);
  37. }
  38. }
  39. return SUCCESS;
  40. }
  41. } // 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