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host_cpu_engine.cc 14 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 "host_cpu_engine.h"
  17. #include "graph/common/omg_util.h"
  18. #include "graph/utils/op_desc_utils.h"
  19. #include "graph/utils/tensor_adapter.h"
  20. #include "register/op_kernel_registry.h"
  21. #include "register/host_cpu_context.h"
  22. #include "common/ge/ge_util.h"
  23. #include "common/ge/plugin_manager.h"
  24. #include "graph/utils/type_utils.h"
  25. #include "common/fp16_t.h"
  26. #include "common/math/math_util.h"
  27. namespace {
  28. #define CREATE_OUTPUT_CASE(DTYPE, TYPE) \
  29. case (DTYPE): { \
  30. GeTensorPtr ge_tensor = nullptr; \
  31. if (need_create_flag) { \
  32. uint64_t size = data_num * sizeof(TYPE); \
  33. ge_tensor = MakeShared<GeTensor>(out_desc, size); \
  34. GE_CHECK_NOTNULL(ge_tensor); \
  35. GELOGD("node:%s allocate output %zu success, size=%ld", op_desc->GetName().c_str(), i, size); \
  36. ge_tensor->MutableTensorDesc().SetDataType(out_desc.GetDataType()); \
  37. ge_tensor->MutableTensorDesc().SetShape(out_desc.GetShape()); \
  38. } else { \
  39. ge_tensor = outputs[i]; \
  40. GE_CHECK_NOTNULL(ge_tensor); \
  41. GELOGD("node:%s existed output %zu", op_desc->GetName().c_str(), i); \
  42. } \
  43. auto tensor = TensorAdapter::AsTensor(*ge_tensor); \
  44. auto tensor_name = op_desc->GetOutputNameByIndex(i); \
  45. GE_RETURN_WITH_LOG_IF_TRUE(tensor_name.empty(), "Failed to get output name. node = %s, index = %zu", \
  46. op_desc->GetName().c_str(), i); \
  47. named_outputs.emplace(tensor_name, tensor); \
  48. break; \
  49. }
  50. }
  51. namespace ge {
  52. namespace {
  53. const char *kEnvKeyOppPath = "ASCEND_OPP_PATH";
  54. const char *kHostCpuLibRelativePath = "/op_impl/built-in/host_cpu";
  55. }
  56. Status GetDataNumber(const GeTensorDesc &out_desc, uint64_t &data_num) {
  57. int64_t num_size = out_desc.GetShape().IsScalar() ? 1 : out_desc.GetShape().GetShapeSize();
  58. if (out_desc.GetShape().IsUnknownShape()) {
  59. std::vector<std::pair<int64_t, int64_t>> range;
  60. if (out_desc.GetShapeRange(range) != GRAPH_SUCCESS) {
  61. GELOGE(INTERNAL_ERROR, "Get shape range failed.");
  62. return INTERNAL_ERROR;
  63. }
  64. int64_t max_range_size = 1;
  65. for (const auto& item : range) {
  66. FMK_INT64_MULCHECK(max_range_size, item.second);
  67. max_range_size *= item.second;
  68. }
  69. num_size = max_range_size;
  70. }
  71. if (num_size < 0) {
  72. GELOGE(INTERNAL_ERROR, "Get negative size, num_size=%ld.", num_size);
  73. return INTERNAL_ERROR;
  74. }
  75. data_num = static_cast<uint64_t>(num_size);
  76. return SUCCESS;
  77. }
  78. void HostCpuEngine::CloseSo() {
  79. for (auto handle : lib_handles_) {
  80. if (mmDlclose(handle) != 0) {
  81. const char *error = mmDlerror();
  82. error = (error == nullptr) ? "" : error;
  83. GELOGW("failed to close handle, message: %s", error);
  84. }
  85. }
  86. lib_handles_.clear();
  87. }
  88. ge::Status HostCpuEngine::Initialize() {
  89. std::lock_guard<std::mutex> lock(mu_);
  90. if (initialized_) {
  91. GELOGI("HostCpuEngine is already initialized");
  92. return SUCCESS;
  93. }
  94. std::string lib_dir;
  95. GE_CHK_STATUS_RET_NOLOG(GetLibPath(lib_dir));
  96. std::vector<std::string> so_paths;
  97. if (ListSoFiles(lib_dir, so_paths) == SUCCESS) {
  98. (void) LoadLibs(so_paths);
  99. }
  100. initialized_ = true;
  101. return SUCCESS;
  102. }
  103. void HostCpuEngine::Finalize() {
  104. GELOGI("start HostCpuEngine::Finalize");
  105. }
  106. bool HostCpuEngine::CheckSupported(const string &op_type) {
  107. return OpKernelRegistry::GetInstance().IsRegistered(op_type);
  108. }
  109. Status HostCpuEngine::FindOpKernel(const ge::NodePtr &node, std::unique_ptr<HostCpuOp> &op_kernel) {
  110. std::string op_type;
  111. auto status = GetOriginalType(node, op_type);
  112. GE_CHK_BOOL_EXEC_NOLOG(status == SUCCESS, return status);
  113. auto kernel = OpKernelRegistry::GetInstance().CreateHostCpuOp(op_type);
  114. if (kernel == nullptr) {
  115. GELOGD("Op of type %s is not supported by host cpu engine", op_type.c_str());
  116. return UNSUPPORTED;
  117. }
  118. GELOGD("Successfully created op kernel. op type = %s", op_type.c_str());
  119. op_kernel = std::move(kernel);
  120. return SUCCESS;
  121. }
  122. Status HostCpuEngine::PrepareInputs(const ge::ConstOpDescPtr &op_desc,
  123. const vector<ConstGeTensorPtr> &inputs,
  124. map<std::string, const Tensor> &named_inputs) {
  125. auto num_inputs = op_desc->GetInputsSize();
  126. if (num_inputs != inputs.size()) {
  127. GELOGE(PARAM_INVALID,
  128. "Mismatching input sizes. op_desc has %zu input(s), but given %zu",
  129. num_inputs,
  130. inputs.size());
  131. return PARAM_INVALID;
  132. }
  133. for (size_t i = 0; i < num_inputs; ++i) {
  134. auto ge_tensor = inputs[i];
  135. GE_CHECK_NOTNULL(ge_tensor);
  136. auto tensor = TensorAdapter::AsTensor(*ge_tensor);
  137. auto tensor_name = op_desc->GetInputNameByIndex(i);
  138. GE_RETURN_WITH_LOG_IF_TRUE(tensor_name.empty(),
  139. "Failed to get input name. node = %s, index = %zu", op_desc->GetName().c_str(), i);
  140. GELOGD("Successfully inserted input tensor. node = %s, index = %zu, input name = %s",
  141. op_desc->GetName().c_str(), i, tensor_name.c_str());
  142. named_inputs.emplace(tensor_name, tensor);
  143. }
  144. return SUCCESS;
  145. }
  146. Status HostCpuEngine::PrepareOutputs(const ge::ConstOpDescPtr &op_desc,
  147. vector<GeTensorPtr> &outputs,
  148. map<std::string, Tensor> &named_outputs) {
  149. if (!outputs.empty() && (outputs.size() != op_desc->GetOutputsSize())) {
  150. GELOGW("size of outputs not match, size of outputs = %zu, exactly output_num=%zu.",
  151. outputs.size(), op_desc->GetOutputsSize());
  152. outputs.clear();
  153. }
  154. bool need_create_flag = (outputs.size() != op_desc->GetOutputsSize());
  155. for (size_t i = 0; i < op_desc->GetOutputsSize(); ++i) {
  156. const auto &out_desc = op_desc->GetOutputDesc(i);
  157. uint64_t data_num = 0;
  158. if (need_create_flag) {
  159. if (GetDataNumber(out_desc, data_num) != SUCCESS) {
  160. GELOGE(INTERNAL_ERROR, "node:%s, get size for output %zu failed", op_desc->GetName().c_str(), i);
  161. return INTERNAL_ERROR;
  162. }
  163. }
  164. switch (out_desc.GetDataType()) {
  165. CREATE_OUTPUT_CASE(DT_BOOL, bool)
  166. CREATE_OUTPUT_CASE(DT_INT8, int8_t)
  167. CREATE_OUTPUT_CASE(DT_INT16, int16_t)
  168. CREATE_OUTPUT_CASE(DT_INT32, int32_t)
  169. CREATE_OUTPUT_CASE(DT_INT64, int64_t)
  170. CREATE_OUTPUT_CASE(DT_UINT8, uint8_t)
  171. CREATE_OUTPUT_CASE(DT_UINT16, uint16_t)
  172. CREATE_OUTPUT_CASE(DT_UINT32, uint32_t)
  173. CREATE_OUTPUT_CASE(DT_UINT64, uint64_t)
  174. CREATE_OUTPUT_CASE(DT_FLOAT16, fp16_t)
  175. CREATE_OUTPUT_CASE(DT_FLOAT, float)
  176. CREATE_OUTPUT_CASE(DT_DOUBLE, double)
  177. default:
  178. GELOGW("data type %s not support.",
  179. TypeUtils::DataTypeToSerialString(out_desc.GetDataType()).c_str());
  180. return NOT_CHANGED;
  181. }
  182. }
  183. return SUCCESS;
  184. }
  185. Status HostCpuEngine::RunInternal(const ge::OpDescPtr &op_desc,
  186. HostCpuOp &op_kernel,
  187. map<std::string, const Tensor> &named_inputs,
  188. map<std::string, Tensor> &named_outputs) {
  189. GELOGD("Run operation on host cpu, op name: %s", op_desc->GetName().c_str());
  190. Operator op = ge::OpDescUtils::CreateOperatorFromOpDesc(op_desc);
  191. auto ret = op_kernel.Compute(op, named_inputs, named_outputs);
  192. if (ret != GRAPH_SUCCESS) {
  193. GELOGW("Failed to compute host cpu op. node = %s", op_desc->GetName().c_str());
  194. return FAILED;
  195. }
  196. op.BreakConnect();
  197. return SUCCESS;
  198. }
  199. Status HostCpuEngine::Run(NodePtr &node, const vector<ConstGeTensorPtr> &inputs, std::vector<GeTensorPtr> &outputs) {
  200. GE_CHECK_NOTNULL(node);
  201. GE_CHECK_NOTNULL(node->GetOpDesc());
  202. GELOGD("Run node by host cpu engine. node name = %s", node->GetName().c_str());
  203. std::unique_ptr<HostCpuOp> op_kernel;
  204. GE_CHK_STATUS_RET_NOLOG(FindOpKernel(node, op_kernel));
  205. std::map<std::string, const Tensor> named_inputs;
  206. std::map<std::string, Tensor> named_outputs;
  207. auto op_desc = node->GetOpDesc();
  208. GE_CHK_STATUS_RET_NOLOG(PrepareInputs(op_desc, inputs, named_inputs));
  209. GE_CHK_STATUS_RET_NOLOG(PrepareOutputs(op_desc, outputs, named_outputs));
  210. GE_CHK_STATUS_RET_NOLOG(RunInternal(op_desc, *op_kernel, named_inputs, named_outputs));
  211. std::vector<GeTensorPtr> tmp_outputs;
  212. for (size_t i = 0; i < op_desc->GetOutputsSize(); i++) {
  213. auto tensor_name = op_desc->GetOutputNameByIndex(i);
  214. if (tensor_name.empty()) {
  215. GELOGE(INTERNAL_ERROR, "Failed to get output name. node = %s, index = %zu", op_desc->GetName().c_str(), i);
  216. return INTERNAL_ERROR;
  217. }
  218. auto iter = named_outputs.find(tensor_name);
  219. if (iter == named_outputs.end()) {
  220. GELOGE(INTERNAL_ERROR, "Failed to get output tensor. node = %s, index = %zu, tensor_name = %s",
  221. op_desc->GetName().c_str(), i, tensor_name.c_str());
  222. return INTERNAL_ERROR;
  223. }
  224. auto ge_tensor = MakeShared<GeTensor>(TensorAdapter::AsGeTensor(iter->second));
  225. GE_CHECK_NOTNULL(ge_tensor);
  226. tmp_outputs.emplace_back(ge_tensor);
  227. }
  228. GELOGD("Run node by host cpu engine successfully. name node = %s", node->GetName().c_str());
  229. outputs.swap(tmp_outputs);
  230. return SUCCESS;
  231. }
  232. ge::Status HostCpuEngine::GetLibPath(std::string &lib_path) {
  233. GELOGI("Start to get host cpu lib path");
  234. const char *path_env = std::getenv(kEnvKeyOppPath);
  235. if (path_env != nullptr) {
  236. lib_path = path_env;
  237. if (!lib_path.empty()) {
  238. lib_path += kHostCpuLibRelativePath;
  239. GELOGI("Get host cpu so path from env: %s", lib_path.c_str());
  240. return SUCCESS;
  241. }
  242. }
  243. lib_path = PluginManager::GetPath();
  244. GELOGI("path_base is %s", lib_path.c_str());
  245. lib_path = lib_path.substr(0, lib_path.rfind('/'));
  246. lib_path = lib_path.substr(0, lib_path.rfind('/'));
  247. lib_path += "/opp";
  248. lib_path += kHostCpuLibRelativePath;
  249. GELOGI("Get host cpu so path from PluginManager::GetPath: %s", lib_path.c_str());
  250. return SUCCESS;
  251. }
  252. static int RegularFileFilterFn(const mmDirent *entry) {
  253. return entry->d_type == DT_REG;
  254. }
  255. Status HostCpuEngine::ListSoFiles(const std::string &base_dir, std::vector<std::string> &names) {
  256. std::string real_path = base_dir;
  257. GE_CHK_STATUS_RET_NOLOG(GetRealPath(real_path));
  258. real_path.push_back('/');
  259. mmDirent **entries = nullptr;
  260. auto ret = mmScandir(real_path.c_str(), &entries, RegularFileFilterFn, nullptr);
  261. if (ret < 0) {
  262. GELOGW("scan dir failed. path = %s, ret = %d, errmsg = %s", real_path.c_str(), ret, strerror(errno));
  263. return INTERNAL_ERROR;
  264. }
  265. for (int i = 0; i < ret; ++i) {
  266. mmDirent *dir_ent = entries[i];
  267. string name = string(dir_ent->d_name);
  268. if (IsSoFile(name)) {
  269. names.emplace_back(real_path + name);
  270. }
  271. }
  272. mmScandirFree(entries, ret);
  273. GELOGI("Found %d libs to load", ret);
  274. return SUCCESS;
  275. }
  276. bool HostCpuEngine::IsSoFile(const std::string &file_name) {
  277. static const std::string so_suffix(".so");
  278. auto pos = file_name.rfind(so_suffix);
  279. if (pos == string::npos) {
  280. return false;
  281. }
  282. return pos == file_name.size() - so_suffix.size();
  283. }
  284. Status HostCpuEngine::LoadLibs(std::vector<std::string> &lib_paths) {
  285. for (auto &so_path : lib_paths) {
  286. GE_CHK_STATUS_RET_NOLOG(GetRealPath(so_path));
  287. GE_CHK_STATUS_RET_NOLOG(LoadLib(so_path));
  288. }
  289. return SUCCESS;
  290. }
  291. Status HostCpuEngine::LoadLib(const std::string &lib_path) {
  292. GELOGI("To invoke dlopen on lib: %s", lib_path.c_str());
  293. auto handle = mmDlopen(lib_path.c_str(), MMPA_RTLD_NOW | MMPA_RTLD_GLOBAL);
  294. if (handle == nullptr) {
  295. const char *error = mmDlerror();
  296. error = (error == nullptr) ? "" : error;
  297. GELOGE(INTERNAL_ERROR, "Failed to invoke dlopen. path = %s, error = %s", lib_path.c_str(), error);
  298. return INTERNAL_ERROR;
  299. }
  300. auto initialize = (Status (*)(const HostCpuContext &))mmDlsym(handle, "Initialize");
  301. if (initialize != nullptr) {
  302. GELOGI("Invoke function Initialize in lib: %s", lib_path.c_str());
  303. if (initialize(HostCpuContext()) != SUCCESS) {
  304. GELOGW("Failed to invoke function Initialize in lib: %s", lib_path.c_str());
  305. }
  306. }
  307. GELOGI("Lib: %s has been opened", lib_path.c_str());
  308. lib_handles_.emplace_back(handle);
  309. return SUCCESS;
  310. }
  311. Status HostCpuEngine::GetRealPath(std::string &path) {
  312. std::string real_path = RealPath(path.c_str());
  313. if (real_path.empty()) {
  314. GELOGW("File path %s is invalid.", path.c_str());
  315. return INTERNAL_ERROR;
  316. }
  317. path = real_path;
  318. return SUCCESS;
  319. }
  320. } // 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