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single_op_model_unittest.cc 9.8 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. #include "graph/load/model_manager/model_utils.h"
  19. #include "graph/utils/graph_utils.h"
  20. #include "runtime/rt.h"
  21. #define protected public
  22. #define private public
  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. #undef private
  31. #undef protected
  32. #include "graph/passes/graph_builder_utils.h"
  33. using namespace std;
  34. using namespace testing;
  35. using namespace ge;
  36. class UtestSingleOpModel : public testing::Test {
  37. protected:
  38. void SetUp() {}
  39. void TearDown() {}
  40. };
  41. //rt api stub
  42. rtError_t rtGetTaskIdAndStreamID(uint32_t *taskId, uint32_t *streamId) {
  43. return RT_ERROR_NONE;
  44. }
  45. /*
  46. TEST_F(UtestSingleOpModel, test_init_model) {
  47. string model_data_str = "123456789";
  48. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  49. ASSERT_EQ(model.InitModel(), FAILED);
  50. }
  51. void ParseOpModelParamsMock(ModelHelper &model_helper, SingleOpModelParam &param) {}
  52. TEST_F(UtestSingleOpModel, test_parse_input_node) {
  53. string model_data_str = "123456789";
  54. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  55. auto op_desc = make_shared<OpDesc>("Data", "Data");
  56. ASSERT_EQ(model.ParseInputNode(op_desc), PARAM_INVALID);
  57. vector<int64_t> shape{1, 2, 3, 4};
  58. vector<int64_t> offsets{16};
  59. GeShape ge_shape(shape);
  60. GeTensorDesc desc(ge_shape);
  61. op_desc->AddOutputDesc(desc);
  62. op_desc->SetOutputOffset(offsets);
  63. ASSERT_EQ(model.ParseInputNode(op_desc), SUCCESS);
  64. op_desc->AddOutputDesc(desc);
  65. offsets.push_back(32);
  66. op_desc->SetOutputOffset(offsets);
  67. ASSERT_EQ(model.ParseInputNode(op_desc), PARAM_INVALID);
  68. }
  69. */
  70. TEST_F(UtestSingleOpModel, test_parse_output_node) {
  71. string model_data_str = "123456789";
  72. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  73. auto op_desc = make_shared<OpDesc>("NetOutput", "NetOutput");
  74. vector<int64_t> shape{1, 2, 3, 4};
  75. vector<int64_t> offsets{16};
  76. GeShape ge_shape(shape);
  77. GeTensorDesc desc(ge_shape);
  78. op_desc->AddInputDesc(desc);
  79. op_desc->SetInputOffset(offsets);
  80. op_desc->AddOutputDesc(desc);
  81. op_desc->SetOutputOffset(offsets);
  82. ASSERT_NO_THROW(model.ParseOutputNode(op_desc));
  83. ASSERT_NO_THROW(model.ParseOutputNode(op_desc));
  84. }
  85. TEST_F(UtestSingleOpModel, test_set_inputs_and_outputs) {
  86. string model_data_str = "123456789";
  87. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  88. model.input_offset_list_.push_back(0);
  89. model.input_sizes_.push_back(16);
  90. model.output_offset_list_.push_back(0);
  91. model.output_sizes_.push_back(16);
  92. std::mutex stream_mu_;
  93. rtStream_t stream_ = nullptr;
  94. // SingleOp single_op(&stream_mu_, stream_);
  95. //
  96. // ASSERT_EQ(model.SetInputsAndOutputs(single_op), SUCCESS);
  97. }
  98. /*
  99. TEST_F(UtestSingleOpModel, test_build_kernel_task) {
  100. string model_data_str = "123456789";
  101. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  102. model.input_offset_list_.push_back(0);
  103. model.input_sizes_.push_back(16);
  104. model.output_offset_list_.push_back(0);
  105. model.output_sizes_.push_back(16);
  106. auto graph = make_shared<ComputeGraph>("graph");
  107. auto op_desc = make_shared<OpDesc>("AddN", "AddN");
  108. vector<int64_t> shape{16, 16};
  109. GeShape ge_shape(shape);
  110. GeTensorDesc desc(ge_shape);
  111. op_desc->AddInputDesc(desc);
  112. op_desc->AddOutputDesc(desc);
  113. auto node = graph->AddNode(op_desc);
  114. std::mutex stream_mu_;
  115. rtStream_t stream_ = nullptr;
  116. SingleOp single_op(&stream_mu_, stream_);
  117. domi::KernelDef kernel_def;
  118. kernel_def.mutable_context()->set_kernel_type(cce::ccKernelType::TE);
  119. TbeOpTask *task = nullptr;
  120. ASSERT_EQ(model.BuildKernelTask(kernel_def, &task), UNSUPPORTED);
  121. kernel_def.mutable_context()->set_kernel_type(cce::ccKernelType::TE);
  122. ASSERT_EQ(model.BuildKernelTask(kernel_def, &task), INTERNAL_ERROR);
  123. model.op_list_[0] = node;
  124. ASSERT_EQ(model.BuildKernelTask(kernel_def, &task), PARAM_INVALID);
  125. ASSERT_EQ(task, nullptr);
  126. delete task;
  127. }
  128. TEST_F(UtestSingleOpModel, test_init) {
  129. string model_data_str = "123456789";
  130. SingleOpModel op_model("model", model_data_str.c_str(), model_data_str.size());
  131. ASSERT_EQ(op_model.Init(), FAILED);
  132. }
  133. */
  134. /*
  135. TEST_F(UtestSingleOpModel, test_parse_arg_table) {
  136. string model_data_str = "123456789";
  137. SingleOpModel op_model("model", model_data_str.c_str(), model_data_str.size());
  138. TbeOpTask task;
  139. OpDescPtr op_desc;
  140. std::mutex stream_mu_;
  141. rtStream_t stream_ = nullptr;
  142. SingleOp op(&stream_mu_, stream_);
  143. op.arg_table_.resize(2);
  144. auto args = std::unique_ptr<uint8_t[]>(new uint8_t[sizeof(uintptr_t) * 2]);
  145. auto *arg_base = (uintptr_t*)args.get();
  146. arg_base[0] = 0x100000;
  147. arg_base[1] = 0x200000;
  148. task.SetKernelArgs(std::move(args), 16, 1, op_desc);
  149. op_model.model_params_.addr_mapping_[0x100000] = 1;
  150. op_model.ParseArgTable(&task, op);
  151. ASSERT_EQ(op.arg_table_[0].size(), 0);
  152. ASSERT_EQ(op.arg_table_[1].size(), 1);
  153. ASSERT_EQ(op.arg_table_[1].front(), &arg_base[0]);
  154. }
  155. */
  156. TEST_F(UtestSingleOpModel, test_op_task_get_profiler_args) {
  157. string name = "relu";
  158. string type = "relu";
  159. auto op_desc = std::make_shared<ge::OpDesc>(name, type);
  160. op_desc->SetStreamId(0);
  161. op_desc->SetId(0);
  162. TbeOpTask task;
  163. task.op_desc_ = op_desc;
  164. task.model_name_ = "resnet_50";
  165. task.model_id_ = 1;
  166. TaskDescInfo task_desc_info;
  167. uint32_t model_id;
  168. task.GetProfilingArgs(task_desc_info, model_id);
  169. ASSERT_EQ(task_desc_info.model_name, "resnet_50");
  170. ASSERT_EQ(model_id, 1);
  171. }
  172. TEST_F(UtestSingleOpModel, test_build_dynamic_op) {
  173. string model_data_str = "123456789";
  174. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  175. model.netoutput_op_ = make_shared<OpDesc>("NetOutput", "NetOutput");
  176. model.model_helper_.model_ = ge::MakeShared<ge::GeModel>();
  177. // make graph
  178. auto compute_graph = make_shared<ComputeGraph>("graph");
  179. auto data_op = make_shared<OpDesc>("Data", DATA);
  180. auto data_node = compute_graph->AddNode(data_op);
  181. auto graph = GraphUtils::CreateGraphFromComputeGraph(compute_graph);
  182. model.model_helper_.model_->SetGraph(graph);
  183. // set task_def
  184. auto model_task_def = make_shared<domi::ModelTaskDef>();
  185. domi::TaskDef *task_def = model_task_def->add_task();
  186. task_def->set_type(RT_MODEL_TASK_KERNEL);
  187. domi::KernelDef *kernel_def = task_def->mutable_kernel();
  188. domi::KernelContext *context = kernel_def->mutable_context();
  189. context->set_kernel_type(2); // ccKernelType::TE
  190. model.model_helper_.model_->SetModelTaskDef(model_task_def);
  191. std::mutex stream_mu_;
  192. DynamicSingleOp dynamic_single_op(0, &stream_mu_, nullptr);
  193. StreamResource res((uintptr_t)1);
  194. model.BuildDynamicOp(res, dynamic_single_op);
  195. }
  196. TEST_F(UtestSingleOpModel, test_host_mem) {
  197. string model_data_str = "123456789";
  198. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  199. // make graph
  200. ut::GraphBuilder builder = ut::GraphBuilder("graph");
  201. auto data = builder.AddNode("Data", "Data", 0, 1);
  202. auto netoutput = builder.AddNode("Netoutput", "NetOutput", 1, 0);
  203. builder.AddDataEdge(data, 0, netoutput, 0);
  204. auto graph = builder.GetGraph();
  205. model.op_with_hostmem_[0] = data;
  206. std::mutex stream_mu_;
  207. DynamicSingleOp single_op(0, &stream_mu_, nullptr);
  208. ASSERT_EQ(model.SetHostMemTensor(single_op), SUCCESS);
  209. }
  210. TEST_F(UtestSingleOpModel, BuildTaskList) {
  211. ComputeGraphPtr graph = make_shared<ComputeGraph>("single_op");
  212. GeModelPtr ge_model = make_shared<GeModel>();
  213. ge_model->SetGraph(GraphUtils::CreateGraphFromComputeGraph(graph));
  214. shared_ptr<domi::ModelTaskDef> model_task_def = make_shared<domi::ModelTaskDef>();
  215. ge_model->SetModelTaskDef(model_task_def);
  216. NodePtr node = nullptr;
  217. {
  218. auto op_desc = std::make_shared<ge::OpDesc>("memcpy", MEMCPYASYNC);
  219. GeTensorDesc tensor(GeShape(), FORMAT_NCHW, DT_FLOAT);
  220. op_desc->AddInputDesc(tensor);
  221. op_desc->AddOutputDesc(tensor);
  222. op_desc->SetInputOffset({0});
  223. op_desc->SetOutputOffset({0});
  224. node = graph->AddNode(op_desc);
  225. domi::TaskDef *task_def = model_task_def->add_task();
  226. task_def->set_stream_id(0);
  227. task_def->set_type(RT_MODEL_TASK_MEMCPY_ASYNC);
  228. domi::MemcpyAsyncDef *memcpy_async = task_def->mutable_memcpy_async();
  229. memcpy_async->set_src(0);
  230. memcpy_async->set_dst(0);
  231. memcpy_async->set_dst_max(512);
  232. memcpy_async->set_count(1);
  233. memcpy_async->set_kind(RT_MEMCPY_DEVICE_TO_DEVICE);
  234. memcpy_async->set_op_index(0);
  235. }
  236. string model_data_str = "123456789";
  237. SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
  238. StreamResource *res = new (std::nothrow) StreamResource(1);
  239. std::mutex stream_mu;
  240. rtStream_t stream = nullptr;
  241. rtStreamCreate(&stream, 0);
  242. SingleOp single_op(res, &stream_mu, stream);
  243. model.model_helper_.model_ = ge_model;
  244. model.op_list_.emplace(0, node);
  245. ASSERT_EQ(model.BuildTaskList(res, single_op), SUCCESS);
  246. MemcpyAsyncTask mem_task;
  247. ASSERT_EQ(mem_task.LaunchKernel(0), SUCCESS);
  248. }

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