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hybrid_profiler.cc 2.9 kB

4 years ago
4 years ago
4 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. #include "hybrid_profiler.h"
  17. #include <iomanip>
  18. #include <iostream>
  19. #include <cstdarg>
  20. #include "framework/common/debug/ge_log.h"
  21. #include "securec.h"
  22. namespace ge {
  23. namespace hybrid {
  24. namespace {
  25. const int kMaxEvents = 10000;
  26. const int kEventDescMax = 256;
  27. const int kMaxEventTypes = 8;
  28. const int kIndent = 8;
  29. }
  30. HybridProfiler::HybridProfiler(): counter_(0) {
  31. Reset();
  32. }
  33. void HybridProfiler::RecordEvent(EventType event_type, const char *fmt, ...) {
  34. va_list args;
  35. va_start(args, fmt);
  36. char buf[kEventDescMax];
  37. if (vsnprintf_s(buf, kEventDescMax, kEventDescMax - 1, fmt, args) == -1) {
  38. GELOGE(FAILED, "Format %s failed.", fmt);
  39. va_end(args);
  40. return;
  41. }
  42. va_end(args);
  43. std::string event = buf;
  44. auto index = counter_++;
  45. auto &evt = events_[index];
  46. evt.timestamp = std::chrono::system_clock::now();
  47. evt.desc = std::move(event);
  48. evt.event_type = event_type;
  49. }
  50. void HybridProfiler::Dump(std::ostream &output_stream) {
  51. if (events_.empty()) {
  52. return;
  53. }
  54. auto start_dump = std::chrono::system_clock::now();
  55. auto first_evt = events_[0];
  56. auto start = first_evt.timestamp;
  57. std::vector<decltype(start)> prev_timestamps;
  58. prev_timestamps.resize(kMaxEventTypes, start);
  59. for (int i = 0; i < counter_; ++i) {
  60. auto &evt = events_[i];
  61. auto elapsed = std::chrono::duration_cast<std::chrono::microseconds>(evt.timestamp - start).count();
  62. auto &prev_ts = prev_timestamps[evt.event_type];
  63. auto cost = std::chrono::duration_cast<std::chrono::microseconds>(evt.timestamp - prev_ts).count();
  64. prev_ts = evt.timestamp;
  65. output_stream << std::setw(kIndent) << elapsed << "\t\t" << cost << "\t\t" << evt.desc << std::endl;
  66. }
  67. auto end_dump = std::chrono::system_clock::now();
  68. auto elapsed_dump = std::chrono::duration_cast<std::chrono::microseconds>(end_dump - start).count();
  69. auto cost_dump = std::chrono::duration_cast<std::chrono::microseconds>(end_dump - start_dump).count();
  70. output_stream << std::setw(kIndent) << elapsed_dump << "\t\t" << cost_dump
  71. << "\t\t" << "[Dump profiling]" << std::endl;
  72. events_.clear();
  73. }
  74. void HybridProfiler::Reset() {
  75. counter_ = 0;
  76. events_.clear();
  77. events_.resize(kMaxEvents);
  78. }
  79. } // namespace hybrid
  80. } // 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