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single_op_model_unittest.cc 12 kB

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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 <gtest/gtest.h>
  17. #include <vector>
  18. #define protected public
  19. #define private public
  20. #include "graph/load/model_manager/model_utils.h"
  21. #include "graph/utils/graph_utils.h"
  22. #include "runtime/rt.h"
  23. #include "single_op/single_op_model.h"
  24. #include "single_op/task/tbe_task_builder.h"
  25. #include "single_op/task/rts_kernel_task_builder.h"
  26. #include "single_op/task/op_task.h"
  27. #include "framework/common/helper/model_helper.h"
  28. #include "single_op/single_op.h"
  29. #include "single_op/stream_resource.h"
  30. #include "graph/passes/graph_builder_utils.h"
  31. #include "graph/op_desc_impl.h"
  32. #undef private
  33. #undef protected
  34. using namespace std;
  35. using namespace testing;
  36. using namespace ge;
  37. namespace {
  38. constexpr char const *kAttrSupportDynamicShape = "support_dynamicshape";
  39. } // namespace
  40. class UtestSingleOpModel : public testing::Test {
  41. protected:
  42. void SetUp() {}
  43. void TearDown() {}
  44. };
  45. //rt api stub
  46. rtError_t rtGetTaskIdAndStreamID(uint32_t *taskId, uint32_t *streamId) {
  47. return RT_ERROR_NONE;
  48. }
  49. /*
  50. TEST_F(UtestSingleOpModel, test_init_model) {
  51. string model_data_str = "123456789";
  52. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  53. ASSERT_EQ(model.InitModel(), FAILED);
  54. }
  55. void ParseOpModelParamsMock(ModelHelper &model_helper, SingleOpModelParam &param) {}
  56. TEST_F(UtestSingleOpModel, test_parse_input_node) {
  57. string model_data_str = "123456789";
  58. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  59. auto op_desc = make_shared<OpDesc>("Data", "Data");
  60. ASSERT_EQ(model.ParseInputNode(op_desc), PARAM_INVALID);
  61. vector<int64_t> shape{1, 2, 3, 4};
  62. vector<int64_t> offsets{16};
  63. GeShape ge_shape(shape);
  64. GeTensorDesc desc(ge_shape);
  65. op_desc->AddOutputDesc(desc);
  66. op_desc->SetOutputOffset(offsets);
  67. ASSERT_EQ(model.ParseInputNode(op_desc), SUCCESS);
  68. op_desc->AddOutputDesc(desc);
  69. offsets.push_back(32);
  70. op_desc->SetOutputOffset(offsets);
  71. ASSERT_EQ(model.ParseInputNode(op_desc), PARAM_INVALID);
  72. }
  73. */
  74. TEST_F(UtestSingleOpModel, test_parse_output_node) {
  75. string model_data_str = "123456789";
  76. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  77. auto op_desc = make_shared<OpDesc>("NetOutput", "NetOutput");
  78. vector<int64_t> shape{1, 2, 3, 4};
  79. vector<int64_t> offsets{16};
  80. GeShape ge_shape(shape);
  81. GeTensorDesc desc(ge_shape);
  82. op_desc->AddInputDesc(desc);
  83. op_desc->SetInputOffset(offsets);
  84. op_desc->AddOutputDesc(desc);
  85. op_desc->SetOutputOffset(offsets);
  86. ASSERT_NO_THROW(model.ParseOutputNode(op_desc));
  87. ASSERT_NO_THROW(model.ParseOutputNode(op_desc));
  88. }
  89. TEST_F(UtestSingleOpModel, test_set_inputs_and_outputs) {
  90. string model_data_str = "123456789";
  91. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  92. model.input_offset_list_.push_back(0);
  93. model.input_sizes_.push_back(16);
  94. model.output_offset_list_.push_back(0);
  95. model.output_sizes_.push_back(16);
  96. std::mutex stream_mu_;
  97. rtStream_t stream_ = nullptr;
  98. // SingleOp single_op(&stream_mu_, stream_);
  99. //
  100. // ASSERT_EQ(model.SetInputsAndOutputs(single_op), SUCCESS);
  101. }
  102. /*
  103. TEST_F(UtestSingleOpModel, test_build_kernel_task) {
  104. string model_data_str = "123456789";
  105. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  106. model.input_offset_list_.push_back(0);
  107. model.input_sizes_.push_back(16);
  108. model.output_offset_list_.push_back(0);
  109. model.output_sizes_.push_back(16);
  110. auto graph = make_shared<ComputeGraph>("graph");
  111. auto op_desc = make_shared<OpDesc>("AddN", "AddN");
  112. vector<int64_t> shape{16, 16};
  113. GeShape ge_shape(shape);
  114. GeTensorDesc desc(ge_shape);
  115. op_desc->AddInputDesc(desc);
  116. op_desc->AddOutputDesc(desc);
  117. auto node = graph->AddNode(op_desc);
  118. std::mutex stream_mu_;
  119. rtStream_t stream_ = nullptr;
  120. SingleOp single_op(&stream_mu_, stream_);
  121. domi::KernelDef kernel_def;
  122. kernel_def.mutable_context()->set_kernel_type(cce::ccKernelType::TE);
  123. TbeOpTask *task = nullptr;
  124. ASSERT_EQ(model.BuildKernelTask(kernel_def, &task), UNSUPPORTED);
  125. kernel_def.mutable_context()->set_kernel_type(cce::ccKernelType::TE);
  126. ASSERT_EQ(model.BuildKernelTask(kernel_def, &task), INTERNAL_ERROR);
  127. model.op_list_[0] = node;
  128. ASSERT_EQ(model.BuildKernelTask(kernel_def, &task), PARAM_INVALID);
  129. ASSERT_EQ(task, nullptr);
  130. delete task;
  131. }
  132. TEST_F(UtestSingleOpModel, test_init) {
  133. string model_data_str = "123456789";
  134. SingleOpModel op_model("model", model_data_str.c_str(), model_data_str.size());
  135. ASSERT_EQ(op_model.Init(), FAILED);
  136. }
  137. */
  138. /*
  139. TEST_F(UtestSingleOpModel, test_parse_arg_table) {
  140. string model_data_str = "123456789";
  141. SingleOpModel op_model("model", model_data_str.c_str(), model_data_str.size());
  142. TbeOpTask task;
  143. OpDescPtr op_desc;
  144. std::mutex stream_mu_;
  145. rtStream_t stream_ = nullptr;
  146. SingleOp op(&stream_mu_, stream_);
  147. op.arg_table_.resize(2);
  148. auto args = std::unique_ptr<uint8_t[]>(new uint8_t[sizeof(uintptr_t) * 2]);
  149. auto *arg_base = (uintptr_t*)args.get();
  150. arg_base[0] = 0x100000;
  151. arg_base[1] = 0x200000;
  152. task.SetKernelArgs(std::move(args), 16, 1, op_desc);
  153. op_model.model_params_.addr_mapping_[0x100000] = 1;
  154. op_model.ParseArgTable(&task, op);
  155. ASSERT_EQ(op.arg_table_[0].size(), 0);
  156. ASSERT_EQ(op.arg_table_[1].size(), 1);
  157. ASSERT_EQ(op.arg_table_[1].front(), &arg_base[0]);
  158. }
  159. */
  160. TEST_F(UtestSingleOpModel, test_op_task_get_profiler_args) {
  161. string name = "relu";
  162. string type = "relu";
  163. auto op_desc = std::make_shared<ge::OpDesc>(name, type);
  164. op_desc->SetStreamId(0);
  165. op_desc->SetId(0);
  166. TbeOpTask task;
  167. task.op_desc_ = op_desc;
  168. task.model_name_ = "resnet_50";
  169. task.model_id_ = 1;
  170. TaskDescInfo task_desc_info;
  171. uint32_t model_id;
  172. task.GetProfilingArgs(task_desc_info, model_id);
  173. ASSERT_EQ(task_desc_info.model_name, "resnet_50");
  174. ASSERT_EQ(model_id, 1);
  175. }
  176. TEST_F(UtestSingleOpModel, test_build_dynamic_op) {
  177. string model_data_str = "123456789";
  178. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  179. model.netoutput_op_ = make_shared<OpDesc>("NetOutput", "NetOutput");
  180. model.model_helper_.model_ = ge::MakeShared<ge::GeModel>();
  181. // make graph
  182. ut::GraphBuilder builder = ut::GraphBuilder("graph");
  183. auto data = builder.AddNode("Data", "Data", 1, 1);
  184. auto transdata = builder.AddNode("Transdata", "Transdata", 1, 1);
  185. auto netoutput = builder.AddNode("Netoutput", "NetOutput", 1, 0);
  186. builder.AddDataEdge(data, 0, transdata, 0);
  187. builder.AddDataEdge(transdata, 0, netoutput, 0);
  188. auto compute_graph = builder.GetGraph();
  189. auto graph = GraphUtils::CreateGraphFromComputeGraph(compute_graph);
  190. model.model_helper_.model_->SetGraph(graph);
  191. auto op_desc = transdata->GetOpDesc();
  192. const vector<string> depend_names = { "Data" };
  193. op_desc->SetOpInferDepends(depend_names);
  194. (void)AttrUtils::SetBool(op_desc, kAttrSupportDynamicShape, true);
  195. // set task_def
  196. auto model_task_def = make_shared<domi::ModelTaskDef>();
  197. domi::TaskDef *task_def = model_task_def->add_task();
  198. task_def->set_type(RT_MODEL_TASK_KERNEL);
  199. domi::KernelDef *kernel_def = task_def->mutable_kernel();
  200. domi::KernelContext *context = kernel_def->mutable_context();
  201. context->set_kernel_type(2); // ccKernelType::TE
  202. model.model_helper_.model_->SetModelTaskDef(model_task_def);
  203. std::mutex stream_mu_;
  204. DynamicSingleOp dynamic_single_op(0, &stream_mu_, nullptr);
  205. StreamResource res((uintptr_t)1);
  206. model.BuildDynamicOp(res, dynamic_single_op);
  207. op_desc->impl_->input_name_idx_["Data"] = 0;
  208. model.BuildDynamicOp(res, dynamic_single_op);
  209. auto tensor = std::make_shared<GeTensor>();
  210. auto data_desc = data->GetOpDesc();
  211. auto tensor_desc = data_desc->MutableInputDesc(0);
  212. AttrUtils::SetTensor(tensor_desc, "_value", tensor);
  213. model.BuildDynamicOp(res, dynamic_single_op);
  214. }
  215. TEST_F(UtestSingleOpModel, test_host_mem) {
  216. string model_data_str = "123456789";
  217. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  218. // make graph
  219. ut::GraphBuilder builder = ut::GraphBuilder("graph");
  220. auto data = builder.AddNode("Data", "Data", 0, 1);
  221. auto netoutput = builder.AddNode("Netoutput", "NetOutput", 1, 0);
  222. builder.AddDataEdge(data, 0, netoutput, 0);
  223. auto graph = builder.GetGraph();
  224. model.op_with_hostmem_[0] = data;
  225. std::mutex stream_mu_;
  226. DynamicSingleOp single_op(0, &stream_mu_, nullptr);
  227. ASSERT_EQ(model.SetHostMemTensor(single_op), SUCCESS);
  228. }
  229. TEST_F(UtestSingleOpModel, BuildTaskList) {
  230. ComputeGraphPtr graph = make_shared<ComputeGraph>("single_op");
  231. GeModelPtr ge_model = make_shared<GeModel>();
  232. ge_model->SetGraph(GraphUtils::CreateGraphFromComputeGraph(graph));
  233. shared_ptr<domi::ModelTaskDef> model_task_def = make_shared<domi::ModelTaskDef>();
  234. ge_model->SetModelTaskDef(model_task_def);
  235. NodePtr node = nullptr;
  236. {
  237. auto op_desc = std::make_shared<ge::OpDesc>("memcpy", MEMCPYASYNC);
  238. GeTensorDesc tensor(GeShape(), FORMAT_NCHW, DT_FLOAT);
  239. op_desc->AddInputDesc(tensor);
  240. op_desc->AddOutputDesc(tensor);
  241. op_desc->SetInputOffset({0});
  242. op_desc->SetOutputOffset({0});
  243. node = graph->AddNode(op_desc);
  244. domi::TaskDef *task_def = model_task_def->add_task();
  245. task_def->set_stream_id(0);
  246. task_def->set_type(RT_MODEL_TASK_MEMCPY_ASYNC);
  247. domi::MemcpyAsyncDef *memcpy_async = task_def->mutable_memcpy_async();
  248. memcpy_async->set_src(0);
  249. memcpy_async->set_dst(0);
  250. memcpy_async->set_dst_max(512);
  251. memcpy_async->set_count(1);
  252. memcpy_async->set_kind(RT_MEMCPY_DEVICE_TO_DEVICE);
  253. memcpy_async->set_op_index(0);
  254. }
  255. string model_data_str = "123456789";
  256. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  257. StreamResource *res = new (std::nothrow) StreamResource(1);
  258. std::mutex stream_mu;
  259. rtStream_t stream = nullptr;
  260. rtStreamCreate(&stream, 0);
  261. SingleOp single_op(res, &stream_mu, stream);
  262. model.model_helper_.model_ = ge_model;
  263. model.op_list_.emplace(0, node);
  264. ASSERT_EQ(model.BuildTaskList(res, single_op), SUCCESS);
  265. MemcpyAsyncTask mem_task;
  266. ASSERT_EQ(mem_task.LaunchKernel(0), SUCCESS);
  267. }
  268. TEST_F(UtestSingleOpModel, build_dynamic_task) {
  269. ComputeGraphPtr graph = make_shared<ComputeGraph>("single_op");
  270. GeModelPtr ge_model = make_shared<GeModel>();
  271. ge_model->SetGraph(GraphUtils::CreateGraphFromComputeGraph(graph));
  272. shared_ptr<domi::ModelTaskDef> model_task_def = make_shared<domi::ModelTaskDef>();
  273. ge_model->SetModelTaskDef(model_task_def);
  274. domi::TaskDef *task_def = model_task_def->add_task();
  275. task_def->set_type(RT_MODEL_TASK_KERNEL_EX);
  276. domi::TaskDef *task_def2 = model_task_def->add_task();
  277. task_def2->set_type(RT_MODEL_TASK_KERNEL);
  278. domi::KernelDef *kernel_def = task_def2->mutable_kernel();
  279. domi::KernelContext *context = kernel_def->mutable_context();
  280. context->set_kernel_type(6); // ccKernelType::AI_CPU
  281. domi::TaskDef *task_def3 = model_task_def->add_task();
  282. task_def3->set_type(RT_MODEL_TASK_ALL_KERNEL);
  283. string model_data_str = "123456789";
  284. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  285. std::mutex stream_mu;
  286. rtStream_t stream = nullptr;
  287. rtStreamCreate(&stream, 0);
  288. DynamicSingleOp single_op(0, &stream_mu, stream);
  289. model.model_helper_.model_ = ge_model;
  290. auto op_desc = std::make_shared<ge::OpDesc>("add", "Add");
  291. std::vector<char> kernelBin;
  292. TBEKernelPtr tbe_kernel = std::make_shared<ge::OpKernelBin>("name/Add", std::move(kernelBin));
  293. op_desc->SetExtAttr(ge::OP_EXTATTR_NAME_TBE_KERNEL, tbe_kernel);
  294. NodePtr node = graph->AddNode(op_desc);
  295. model.op_list_[0] = node;
  296. StreamResource *res = new (std::nothrow) StreamResource(1);
  297. ASSERT_EQ(model.ParseTasks(), SUCCESS);
  298. ASSERT_EQ(model.BuildTaskListForDynamicOp(res, single_op), SUCCESS);
  299. model.tbe_tasks_.clear();
  300. ASSERT_EQ(model.BuildTaskListForDynamicOp(res, single_op), SUCCESS);
  301. model.aicpu_tasks_[0] = *task_def2;
  302. model.BuildTaskListForDynamicOp(res, single_op);
  303. }

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