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host_cpu_engine.cc 15 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(), "[Get][OutputName] failed. 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. REPORT_CALL_ERROR("E19999", "GetShapeRange failed.");
  62. GELOGE(INTERNAL_ERROR, "[Get][ShapeRange] failed.");
  63. return INTERNAL_ERROR;
  64. }
  65. int64_t max_range_size = 1;
  66. for (const auto& item : range) {
  67. FMK_INT64_MULCHECK(max_range_size, item.second);
  68. max_range_size *= item.second;
  69. }
  70. num_size = max_range_size;
  71. }
  72. if (num_size < 0) {
  73. REPORT_INNER_ERROR("E19999", "Get negative size, num_size=%ld.", num_size);
  74. GELOGE(INTERNAL_ERROR, "[Check][Param] Get negative size, num_size=%ld.", num_size);
  75. return INTERNAL_ERROR;
  76. }
  77. data_num = static_cast<uint64_t>(num_size);
  78. return SUCCESS;
  79. }
  80. void HostCpuEngine::CloseSo() {
  81. for (auto handle : lib_handles_) {
  82. if (mmDlclose(handle) != 0) {
  83. const char *error = mmDlerror();
  84. error = (error == nullptr) ? "" : error;
  85. GELOGW("failed to close handle, message: %s", error);
  86. }
  87. }
  88. lib_handles_.clear();
  89. }
  90. ge::Status HostCpuEngine::Initialize() {
  91. std::lock_guard<std::mutex> lock(mu_);
  92. if (initialized_) {
  93. GELOGI("HostCpuEngine is already initialized");
  94. return SUCCESS;
  95. }
  96. std::string lib_dir;
  97. GE_CHK_STATUS_RET_NOLOG(GetLibPath(lib_dir));
  98. std::vector<std::string> so_paths;
  99. if (ListSoFiles(lib_dir, so_paths) == SUCCESS) {
  100. (void) LoadLibs(so_paths);
  101. }
  102. initialized_ = true;
  103. return SUCCESS;
  104. }
  105. void HostCpuEngine::Finalize() {
  106. GELOGI("start HostCpuEngine::Finalize");
  107. }
  108. bool HostCpuEngine::CheckSupported(const string &op_type) {
  109. return OpKernelRegistry::GetInstance().IsRegistered(op_type);
  110. }
  111. Status HostCpuEngine::FindOpKernel(const ge::NodePtr &node, std::unique_ptr<HostCpuOp> &op_kernel) {
  112. std::string op_type;
  113. auto status = GetOriginalType(node, op_type);
  114. GE_CHK_BOOL_EXEC_NOLOG(status == SUCCESS, return status);
  115. auto kernel = OpKernelRegistry::GetInstance().CreateHostCpuOp(op_type);
  116. if (kernel == nullptr) {
  117. GELOGD("Op of type %s is not supported by host cpu engine", op_type.c_str());
  118. return UNSUPPORTED;
  119. }
  120. GELOGD("Successfully created op kernel. op type = %s", op_type.c_str());
  121. op_kernel = std::move(kernel);
  122. return SUCCESS;
  123. }
  124. Status HostCpuEngine::PrepareInputs(const ge::ConstOpDescPtr &op_desc,
  125. const vector<ConstGeTensorPtr> &inputs,
  126. map<std::string, const Tensor> &named_inputs) {
  127. auto num_inputs = op_desc->GetInputsSize();
  128. if (num_inputs != inputs.size()) {
  129. REPORT_INNER_ERROR("E19999", "Mismatching input sizes. op_desc:%s(%s) has %zu input(s), but given %zu",
  130. op_desc->GetName().c_str(), op_desc->GetType().c_str(), num_inputs, inputs.size());
  131. GELOGE(PARAM_INVALID, "[Check][Param] Mismatching input sizes. op_desc:%s(%s) has %zu input(s), but given %zu",
  132. op_desc->GetName().c_str(), op_desc->GetType().c_str(), num_inputs, inputs.size());
  133. return PARAM_INVALID;
  134. }
  135. for (size_t i = 0; i < num_inputs; ++i) {
  136. auto ge_tensor = inputs[i];
  137. GE_CHECK_NOTNULL(ge_tensor);
  138. auto tensor = TensorAdapter::AsTensor(*ge_tensor);
  139. auto tensor_name = op_desc->GetInputNameByIndex(i);
  140. GE_RETURN_WITH_LOG_IF_TRUE(tensor_name.empty(), "[Get][InputName] failed. node = %s, index = %zu",
  141. op_desc->GetName().c_str(), i);
  142. GELOGD("Successfully inserted input tensor. node = %s, index = %zu, input name = %s",
  143. op_desc->GetName().c_str(), i, tensor_name.c_str());
  144. named_inputs.emplace(tensor_name, tensor);
  145. }
  146. return SUCCESS;
  147. }
  148. Status HostCpuEngine::PrepareOutputs(const ge::ConstOpDescPtr &op_desc,
  149. vector<GeTensorPtr> &outputs,
  150. map<std::string, Tensor> &named_outputs) {
  151. if (!outputs.empty() && (outputs.size() != op_desc->GetOutputsSize())) {
  152. GELOGW("size of outputs not match, size of outputs = %zu, exactly output_num=%zu.",
  153. outputs.size(), op_desc->GetOutputsSize());
  154. outputs.clear();
  155. }
  156. bool need_create_flag = (outputs.size() != op_desc->GetOutputsSize());
  157. for (size_t i = 0; i < op_desc->GetOutputsSize(); ++i) {
  158. const auto &out_desc = op_desc->GetOutputDesc(i);
  159. uint64_t data_num = 0;
  160. if (need_create_flag) {
  161. if (GetDataNumber(out_desc, data_num) != SUCCESS) {
  162. GELOGE(INTERNAL_ERROR, "[Get][Number] node:%s get size for output %zu failed", op_desc->GetName().c_str(), i);
  163. return INTERNAL_ERROR;
  164. }
  165. }
  166. switch (out_desc.GetDataType()) {
  167. CREATE_OUTPUT_CASE(DT_BOOL, bool)
  168. CREATE_OUTPUT_CASE(DT_INT8, int8_t)
  169. CREATE_OUTPUT_CASE(DT_INT16, int16_t)
  170. CREATE_OUTPUT_CASE(DT_INT32, int32_t)
  171. CREATE_OUTPUT_CASE(DT_INT64, int64_t)
  172. CREATE_OUTPUT_CASE(DT_UINT8, uint8_t)
  173. CREATE_OUTPUT_CASE(DT_UINT16, uint16_t)
  174. CREATE_OUTPUT_CASE(DT_UINT32, uint32_t)
  175. CREATE_OUTPUT_CASE(DT_UINT64, uint64_t)
  176. CREATE_OUTPUT_CASE(DT_FLOAT16, fp16_t)
  177. CREATE_OUTPUT_CASE(DT_FLOAT, float)
  178. CREATE_OUTPUT_CASE(DT_DOUBLE, double)
  179. default:
  180. GELOGW("data type %s not support.",
  181. TypeUtils::DataTypeToSerialString(out_desc.GetDataType()).c_str());
  182. return NOT_CHANGED;
  183. }
  184. }
  185. return SUCCESS;
  186. }
  187. Status HostCpuEngine::RunInternal(const ge::OpDescPtr &op_desc,
  188. HostCpuOp &op_kernel,
  189. map<std::string, const Tensor> &named_inputs,
  190. map<std::string, Tensor> &named_outputs) {
  191. GELOGD("Run operation on host cpu, op name: %s", op_desc->GetName().c_str());
  192. Operator op = ge::OpDescUtils::CreateOperatorFromOpDesc(op_desc);
  193. auto ret = op_kernel.Compute(op, named_inputs, named_outputs);
  194. if (ret != GRAPH_SUCCESS) {
  195. GELOGW("Failed to compute host cpu op. node = %s", op_desc->GetName().c_str());
  196. return FAILED;
  197. }
  198. op.BreakConnect();
  199. return SUCCESS;
  200. }
  201. Status HostCpuEngine::Run(NodePtr &node, const vector<ConstGeTensorPtr> &inputs, std::vector<GeTensorPtr> &outputs) {
  202. GE_CHECK_NOTNULL(node);
  203. GE_CHECK_NOTNULL(node->GetOpDesc());
  204. GELOGD("Run node by host cpu engine. node name = %s", node->GetName().c_str());
  205. std::unique_ptr<HostCpuOp> op_kernel;
  206. GE_CHK_STATUS_RET_NOLOG(FindOpKernel(node, op_kernel));
  207. std::map<std::string, const Tensor> named_inputs;
  208. std::map<std::string, Tensor> named_outputs;
  209. auto op_desc = node->GetOpDesc();
  210. GE_CHK_STATUS_RET_NOLOG(PrepareInputs(op_desc, inputs, named_inputs));
  211. GE_CHK_STATUS_RET_NOLOG(PrepareOutputs(op_desc, outputs, named_outputs));
  212. GE_CHK_STATUS_RET_NOLOG(RunInternal(op_desc, *op_kernel, named_inputs, named_outputs));
  213. std::vector<GeTensorPtr> tmp_outputs;
  214. for (size_t i = 0; i < op_desc->GetOutputsSize(); i++) {
  215. auto tensor_name = op_desc->GetOutputNameByIndex(i);
  216. if (tensor_name.empty()) {
  217. REPORT_INNER_ERROR("E19999", "GetOutputNameByIndex failed, node = %s, index = %zu",
  218. op_desc->GetName().c_str(), i);
  219. GELOGE(INTERNAL_ERROR, "[Get][OutputName] failed. node = %s, index = %zu", op_desc->GetName().c_str(), i);
  220. return INTERNAL_ERROR;
  221. }
  222. auto iter = named_outputs.find(tensor_name);
  223. if (iter == named_outputs.end()) {
  224. REPORT_INNER_ERROR("E19999", "get output tensor failed, node = %s, index = %zu, tensor_name = %s",
  225. op_desc->GetName().c_str(), i, tensor_name.c_str());
  226. GELOGE(INTERNAL_ERROR, "[Get][OutputTensor] failed. node = %s, index = %zu, tensor_name = %s",
  227. op_desc->GetName().c_str(), i, tensor_name.c_str());
  228. return INTERNAL_ERROR;
  229. }
  230. auto ge_tensor = MakeShared<GeTensor>(TensorAdapter::AsGeTensor(iter->second));
  231. GE_CHECK_NOTNULL(ge_tensor);
  232. tmp_outputs.emplace_back(ge_tensor);
  233. }
  234. GELOGD("Run node by host cpu engine successfully. name node = %s", node->GetName().c_str());
  235. outputs.swap(tmp_outputs);
  236. return SUCCESS;
  237. }
  238. ge::Status HostCpuEngine::GetLibPath(std::string &lib_path) {
  239. GELOGI("Start to get host cpu lib path");
  240. const char *path_env = std::getenv(kEnvKeyOppPath);
  241. if (path_env != nullptr) {
  242. lib_path = path_env;
  243. if (!lib_path.empty()) {
  244. lib_path += kHostCpuLibRelativePath;
  245. GELOGI("Get host cpu so path from env: %s", lib_path.c_str());
  246. return SUCCESS;
  247. }
  248. }
  249. lib_path = PluginManager::GetPath();
  250. GELOGI("path_base is %s", lib_path.c_str());
  251. lib_path = lib_path.substr(0, lib_path.rfind('/'));
  252. lib_path = lib_path.substr(0, lib_path.rfind('/'));
  253. lib_path += "/opp";
  254. lib_path += kHostCpuLibRelativePath;
  255. GELOGI("Get host cpu so path from PluginManager::GetPath: %s", lib_path.c_str());
  256. return SUCCESS;
  257. }
  258. static int RegularFileFilterFn(const mmDirent *entry) {
  259. return entry->d_type == DT_REG;
  260. }
  261. Status HostCpuEngine::ListSoFiles(const std::string &base_dir, std::vector<std::string> &names) {
  262. std::string real_path = base_dir;
  263. GE_CHK_STATUS_RET_NOLOG(GetRealPath(real_path));
  264. real_path.push_back('/');
  265. mmDirent **entries = nullptr;
  266. auto ret = mmScandir(real_path.c_str(), &entries, RegularFileFilterFn, nullptr);
  267. if (ret < 0) {
  268. GELOGW("scan dir failed. path = %s, ret = %d, errmsg = %s", real_path.c_str(), ret, strerror(errno));
  269. return INTERNAL_ERROR;
  270. }
  271. for (int i = 0; i < ret; ++i) {
  272. mmDirent *dir_ent = entries[i];
  273. string name = string(dir_ent->d_name);
  274. if (IsSoFile(name)) {
  275. names.emplace_back(real_path + name);
  276. }
  277. }
  278. mmScandirFree(entries, ret);
  279. GELOGI("Found %d libs to load", ret);
  280. return SUCCESS;
  281. }
  282. bool HostCpuEngine::IsSoFile(const std::string &file_name) {
  283. static const std::string so_suffix(".so");
  284. auto pos = file_name.rfind(so_suffix);
  285. if (pos == string::npos) {
  286. return false;
  287. }
  288. return pos == file_name.size() - so_suffix.size();
  289. }
  290. Status HostCpuEngine::LoadLibs(std::vector<std::string> &lib_paths) {
  291. for (auto &so_path : lib_paths) {
  292. GE_CHK_STATUS_RET_NOLOG(GetRealPath(so_path));
  293. GE_CHK_STATUS_RET_NOLOG(LoadLib(so_path));
  294. }
  295. return SUCCESS;
  296. }
  297. Status HostCpuEngine::LoadLib(const std::string &lib_path) {
  298. GELOGI("To invoke dlopen on lib: %s", lib_path.c_str());
  299. auto handle = mmDlopen(lib_path.c_str(), MMPA_RTLD_NOW | MMPA_RTLD_GLOBAL);
  300. if (handle == nullptr) {
  301. const char *error = mmDlerror();
  302. error = (error == nullptr) ? "" : error;
  303. REPORT_CALL_ERROR("E19999", "mmDlopen failed, path = %s, error = %s", lib_path.c_str(), error);
  304. GELOGE(INTERNAL_ERROR, "[Invoke][DlOpen] failed. path = %s, error = %s", lib_path.c_str(), error);
  305. return INTERNAL_ERROR;
  306. }
  307. auto initialize = (Status (*)(const HostCpuContext &))mmDlsym(handle, "Initialize");
  308. if (initialize != nullptr) {
  309. GELOGI("Invoke function Initialize in lib: %s", lib_path.c_str());
  310. if (initialize(HostCpuContext()) != SUCCESS) {
  311. GELOGW("Failed to invoke function Initialize in lib: %s", lib_path.c_str());
  312. }
  313. }
  314. GELOGI("Lib: %s has been opened", lib_path.c_str());
  315. lib_handles_.emplace_back(handle);
  316. return SUCCESS;
  317. }
  318. Status HostCpuEngine::GetRealPath(std::string &path) {
  319. std::string real_path = RealPath(path.c_str());
  320. if (real_path.empty()) {
  321. GELOGW("File path %s is invalid.", path.c_str());
  322. return INTERNAL_ERROR;
  323. }
  324. path = real_path;
  325. return SUCCESS;
  326. }
  327. } // 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