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