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