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.

graph_optimize_unittest.cc 9.3 kB

4 years ago
4 years ago
4 years ago
4 years ago
4 years ago
4 years ago
4 years ago
4 years ago
4 years ago
4 years ago
4 years ago
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242
  1. /**
  2. * Copyright 2021 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. #include <memory>
  18. #include <iostream>
  19. #define protected public
  20. #define private public
  21. #include "graph/optimize/graph_optimize.h"
  22. #include "init/gelib.h"
  23. #include "ge/ge_api.h"
  24. #undef private
  25. #undef protected
  26. using namespace std;
  27. using namespace testing;
  28. using namespace ge;
  29. namespace {
  30. const char *const kVectorCore = "VectorCore";
  31. const char *const kAicoreEngine = "AIcoreEngine";
  32. void CreateEngineConfigJson(string &dir_path, string &file_path) {
  33. GELOGI("Begin to create engine config json file.");
  34. string base_path = PluginManager::GetPath();
  35. GELOGI("Base path is %s.", base_path.c_str());
  36. dir_path = base_path.substr(0, base_path.rfind('/') + 1) + "plugin/nnengine/ge_config";
  37. string cmd = "mkdir -p " + dir_path;
  38. system(cmd.c_str());
  39. file_path = dir_path + "/engine_conf.json";
  40. GELOGI("Begin to write into the config file: %s.", file_path.c_str());
  41. ofstream ofs(file_path, ios::out);
  42. EXPECT_EQ(!ofs, false);
  43. ofs << "{\n"
  44. " \"schedule_units\" : [ {\n"
  45. " \"id\" : \"TS_1\",\n"
  46. " \"name\" : \"1980_hwts\",\n"
  47. " \"ex_attrs\" : \"\",\n"
  48. " \"cal_engines\" : [\n"
  49. " {\"id\" : \"DNN_VM_GE_LOCAL\", \"name\" : \"GE_LOCAL\", \"independent\" : false, \"attch\" : true, \"skip_assign_stream\" : true },\n"
  50. " {\"id\" : \"AIcoreEngine\", \"name\" : \"AICORE\", \"independent\" : false, \"attch\" : false, \"skip_assign_stream\" : false}\n"
  51. " ]\n"
  52. " } ]\n"
  53. "}";
  54. ofs.close();
  55. GELOGI("Json config file %s has been written.", file_path.c_str());
  56. }
  57. void DeleteFile(const string &file_name) {
  58. auto ret = remove(file_name.c_str());
  59. if (ret == 0) {
  60. GELOGI("Delete file successfully, file:%s.", file_name.c_str());
  61. }
  62. }
  63. }
  64. class UtestGraphOptimizeTest : public testing::Test {
  65. protected:
  66. void SetUp() {
  67. CreateEngineConfigJson(config_dir_, config_file_);
  68. }
  69. void TearDown() {
  70. DeleteFile(config_file_);
  71. DeleteFile(config_dir_);
  72. DNNEngineManager::GetInstance().schedulers_.clear();
  73. OpsKernelManager::GetInstance().atomic_first_optimizers_by_priority_.clear();
  74. }
  75. private:
  76. string config_dir_;
  77. string config_file_;
  78. };
  79. class TestGraphOptimizerSuccess : public GraphOptimizer {
  80. public:
  81. ~TestGraphOptimizerSuccess() override { Finalize(); }
  82. Status Initialize(const map<string, string> &options) override { return SUCCESS; }
  83. Status Finalize() override { return SUCCESS; }
  84. Status OptimizeGraphPrepare(ComputeGraph& graph) override { return SUCCESS; }
  85. Status OptimizeGraphBeforeBuild(ComputeGraph& graph) override { return SUCCESS; }
  86. Status OptimizeOriginalGraph(ComputeGraph &graph) override { return SUCCESS; }
  87. Status OptimizeOriginalGraphJudgeInsert(ComputeGraph &graph) override { return SUCCESS; }
  88. Status OptimizeFusedGraph(ComputeGraph &graph) override { return SUCCESS; }
  89. Status OptimizeWholeGraph(ComputeGraph &graph) override { return SUCCESS; }
  90. Status GetAttributes(GraphOptimizerAttribute &attrs) const override {
  91. attrs.engineName = "AIcoreEngine";
  92. attrs.scope = OPTIMIZER_SCOPE::ENGINE;
  93. return SUCCESS;
  94. }
  95. Status OptimizeStreamGraph(ComputeGraph &graph, const RunContext &context) override { return SUCCESS; }
  96. Status OptimizeFusedGraphAfterGraphSlice(ComputeGraph &graph) override { return SUCCESS; }
  97. Status OptimizeAfterStage1(ComputeGraph &graph) override { return SUCCESS; }
  98. };
  99. class TestGraphOptimizerFail : public GraphOptimizer {
  100. public:
  101. ~TestGraphOptimizerFail() override { Finalize(); }
  102. Status Initialize(const map<string, string> &options) override { return SUCCESS; }
  103. Status Finalize() override { return SUCCESS; }
  104. Status OptimizeGraphPrepare(ComputeGraph& graph) override { return FAILED; }
  105. Status OptimizeGraphBeforeBuild(ComputeGraph& graph) override { return FAILED; }
  106. Status OptimizeOriginalGraph(ComputeGraph &graph) override { return FAILED; }
  107. Status OptimizeOriginalGraphJudgeInsert(ComputeGraph &graph) override { return FAILED; }
  108. Status OptimizeFusedGraph(ComputeGraph &graph) override { return FAILED; }
  109. Status OptimizeWholeGraph(ComputeGraph &graph) override { return FAILED; }
  110. Status GetAttributes(GraphOptimizerAttribute &attrs) const override {
  111. attrs.engineName = "AIcoreEngine";
  112. attrs.scope = OPTIMIZER_SCOPE::ENGINE;
  113. return SUCCESS;
  114. }
  115. Status OptimizeStreamGraph(ComputeGraph &graph, const RunContext &context) override { return FAILED; }
  116. Status OptimizeFusedGraphAfterGraphSlice(ComputeGraph &graph) override { return FAILED; }
  117. Status OptimizeAfterStage1(ComputeGraph &graph) override { return FAILED; }
  118. };
  119. TEST_F(UtestGraphOptimizeTest, test_OptimizeAfterStage1_succ) {
  120. map<string, string> options;
  121. Status ret = ge::GELib::Initialize(options);
  122. EXPECT_EQ(ret, SUCCESS);
  123. GraphOptimizerPtr graph_opt = MakeShared<TestGraphOptimizerSuccess>();
  124. OpsKernelManager::GetInstance().atomic_first_optimizers_by_priority_.push_back(make_pair("AIcoreEngine", graph_opt));
  125. ComputeGraphPtr compute_graph = MakeShared<ComputeGraph>("test_graph");
  126. GraphOptimize base_optimize;
  127. ret = base_optimize.OptimizeAfterStage1(compute_graph);
  128. EXPECT_EQ(ret, SUCCESS);
  129. base_optimize.core_type_ = kVectorCore;
  130. ret = base_optimize.OptimizeAfterStage1(compute_graph);
  131. EXPECT_EQ(ret, SUCCESS);
  132. shared_ptr<GELib> instance_ptr = ge::GELib::GetInstance();
  133. EXPECT_NE(instance_ptr, nullptr);
  134. ret = instance_ptr->Finalize();
  135. EXPECT_EQ(ret, SUCCESS);
  136. }
  137. TEST_F(UtestGraphOptimizeTest, test_OptimizeAfterStage1_fail) {
  138. ComputeGraphPtr compute_graph = nullptr;
  139. GraphOptimize base_optimize;
  140. // 1. Input graph is nullptr.
  141. Status ret = base_optimize.OptimizeAfterStage1(compute_graph);
  142. EXPECT_EQ(ret, PARAM_INVALID);
  143. // 2. GELib is not initialized.
  144. compute_graph = MakeShared<ComputeGraph>("test_graph");
  145. ret = base_optimize.OptimizeAfterStage1(compute_graph);
  146. EXPECT_EQ(ret, GE_CLI_GE_NOT_INITIALIZED);
  147. // 3. The optimizer registered with the engine returned a failure.
  148. map<string, string> options;
  149. ret = ge::GELib::Initialize(options);
  150. EXPECT_EQ(ret, SUCCESS);
  151. GraphOptimizerPtr graph_opt = MakeShared<TestGraphOptimizerFail>();
  152. OpsKernelManager::GetInstance().atomic_first_optimizers_by_priority_.push_back(make_pair("AIcoreEngine", graph_opt));
  153. ret = base_optimize.OptimizeAfterStage1(compute_graph);
  154. EXPECT_EQ(ret, FAILED);
  155. shared_ptr<GELib> instance_ptr = ge::GELib::GetInstance();
  156. EXPECT_NE(instance_ptr, nullptr);
  157. ret = instance_ptr->Finalize();
  158. EXPECT_EQ(ret, SUCCESS);
  159. }
  160. TEST_F(UtestGraphOptimizeTest, test_optimizers_succ) {
  161. map<string, string> options;
  162. Status ret = ge::GELib::Initialize(options);
  163. EXPECT_EQ(ret, SUCCESS);
  164. GraphOptimizerPtr graph_opt = MakeShared<TestGraphOptimizerSuccess>();
  165. OpsKernelManager::GetInstance().atomic_first_optimizers_by_priority_.push_back(make_pair("AIcoreEngine", graph_opt));
  166. ComputeGraphPtr compute_graph = MakeShared<ComputeGraph>("test_graph");
  167. GraphOptimize base_optimize;
  168. ret = base_optimize.OptimizeOriginalGraph(compute_graph);
  169. EXPECT_EQ(ret, SUCCESS);
  170. ret = base_optimize.OptimizeOriginalGraphJudgeInsert(compute_graph);
  171. EXPECT_EQ(ret, SUCCESS);
  172. ret = base_optimize.OptimizeOriginalGraphForQuantize(compute_graph);
  173. EXPECT_EQ(ret, SUCCESS);
  174. ret = base_optimize.OptimizeGraphBeforeBuild(compute_graph);
  175. EXPECT_EQ(ret, SUCCESS);
  176. ret = base_optimize.OptimizeWholeGraph(compute_graph);
  177. EXPECT_EQ(ret, SUCCESS);
  178. shared_ptr<GELib> instance_ptr = ge::GELib::GetInstance();
  179. EXPECT_NE(instance_ptr, nullptr);
  180. ret = instance_ptr->Finalize();
  181. EXPECT_EQ(ret, SUCCESS);
  182. }
  183. TEST_F(UtestGraphOptimizeTest, test_optimizers_fail) {
  184. map<string, string> options;
  185. Status ret = ge::GELib::Initialize(options);
  186. EXPECT_EQ(ret, SUCCESS);
  187. GraphOptimizerPtr graph_opt = MakeShared<TestGraphOptimizerFail>();
  188. OpsKernelManager::GetInstance().atomic_first_optimizers_by_priority_.push_back(make_pair("AIcoreEngine", graph_opt));
  189. ComputeGraphPtr compute_graph = MakeShared<ComputeGraph>("test_graph");
  190. GraphOptimize base_optimize;
  191. ret = base_optimize.OptimizeOriginalGraph(compute_graph);
  192. EXPECT_EQ(ret, FAILED);
  193. ret = base_optimize.OptimizeOriginalGraphJudgeInsert(compute_graph);
  194. EXPECT_EQ(ret, FAILED);
  195. ret = base_optimize.OptimizeOriginalGraphForQuantize(compute_graph);
  196. EXPECT_EQ(ret, FAILED);
  197. ret = base_optimize.OptimizeGraphBeforeBuild(compute_graph);
  198. EXPECT_EQ(ret, FAILED);
  199. ret = base_optimize.OptimizeWholeGraph(compute_graph);
  200. EXPECT_EQ(ret, FAILED);
  201. shared_ptr<GELib> instance_ptr = ge::GELib::GetInstance();
  202. EXPECT_NE(instance_ptr, nullptr);
  203. ret = instance_ptr->Finalize();
  204. EXPECT_EQ(ret, SUCCESS);
  205. }

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