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single_op.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 "single_op/single_op.h"
  17. #include "common/fmk_types.h"
  18. #include "common/ge_types.h"
  19. #include "common/math/math_util.h"
  20. #include "common/profiling/profiling_manager.h"
  21. #include "framework/common/debug/ge_log.h"
  22. #include "framework/common/util.h"
  23. #include "graph/load/new_model_manager/model_utils.h"
  24. #include "runtime/mem.h"
  25. #include "single_op/single_op_manager.h"
  26. #include "single_op/task/build_task_utils.h"
  27. #include "graph/load/new_model_manager/model_manager.h"
  28. namespace ge {
  29. namespace {
  30. const size_t kDataMemAlignSize = 32;
  31. const size_t kDataMemAlignUnit = 2;
  32. const string kShapeTypeDynamic = "dynamic";
  33. const string kShapeTypeStatic = "static";
  34. size_t GetAlignedSize(size_t size) {
  35. size_t aligned_size = (size + kDataMemAlignUnit * kDataMemAlignSize - 1) / kDataMemAlignSize * kDataMemAlignSize;
  36. return aligned_size;
  37. }
  38. Status ProfilingTaskInfo(OpTask *op_task, const string &shape_type) {
  39. if (!ProfilingManager::Instance().ProfilingModelLoadOn()) {
  40. return SUCCESS;
  41. }
  42. string model_name;
  43. string op_name;
  44. uint32_t model_id;
  45. uint32_t block_dim;
  46. if (op_task->GetProfilingArgs(model_name, op_name, model_id, block_dim) != SUCCESS) {
  47. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "Get profiling data of task failed");
  48. return ACL_ERROR_GE_PARAM_INVALID;
  49. }
  50. GELOGD("ProfilingReport of op[%s] model[%s] start.", op_name.c_str(), model_name.c_str());
  51. std::vector<TaskDescInfo> task_desc_info;
  52. uint32_t task_id = 0;
  53. uint32_t stream_id = 0;
  54. if (rtGetTaskIdAndStreamID(&task_id, &stream_id) != RT_ERROR_NONE) {
  55. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "Get task_id and stream_id failed.");
  56. return ACL_ERROR_GE_PARAM_INVALID;
  57. }
  58. TaskDescInfo tmp_task_desc_info;
  59. tmp_task_desc_info.model_name = model_name;
  60. tmp_task_desc_info.op_name = op_name;
  61. tmp_task_desc_info.block_dim = block_dim;
  62. tmp_task_desc_info.task_id = task_id;
  63. tmp_task_desc_info.stream_id = stream_id;
  64. tmp_task_desc_info.shape_type = shape_type;
  65. tmp_task_desc_info.cur_iter_num = 0;
  66. GELOGD("GetTaskDescInfo of op [%s] end, task_id[%u], stream_id[%u]", op_name.c_str(), task_id, stream_id);
  67. task_desc_info.emplace_back(tmp_task_desc_info);
  68. std::vector<ComputeGraphDescInfo> compute_graph_info;
  69. auto &profiling_manager = ProfilingManager::Instance();
  70. profiling_manager.ReportProfilingData(model_id, task_desc_info, compute_graph_info);
  71. return SUCCESS;
  72. }
  73. } // namespace
  74. SingleOp::SingleOp(StreamResource *stream_resource, std::mutex *stream_mutex, rtStream_t stream)
  75. : stream_resource_(stream_resource), stream_mutex_(stream_mutex), stream_(stream) {
  76. }
  77. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY SingleOp::~SingleOp() {
  78. for (auto task : tasks_) {
  79. delete task;
  80. task = nullptr;
  81. }
  82. }
  83. Status SingleOp::ValidateArgs(const std::vector<DataBuffer> &inputs, const std::vector<DataBuffer> &outputs) {
  84. auto num_inputs = inputs.size();
  85. if (num_inputs != input_sizes_.size()) {
  86. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "Input num mismatch. model expect %zu, but given %zu", input_addr_list_.size(),
  87. inputs.size());
  88. return ACL_ERROR_GE_PARAM_INVALID;
  89. }
  90. for (size_t i = 0; i < num_inputs; ++i) {
  91. // preventing from read out of bound
  92. size_t aligned_size = GetAlignedSize(inputs[i].length);
  93. GELOGI("Input [%zu], aligned_size:%zu, inputs.length:%lu, input_sizes_:%zu",
  94. i, aligned_size, inputs[i].length, input_sizes_[i]);
  95. if (aligned_size < input_sizes_[i]) {
  96. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "Input size mismatch. index = %zu, model expect %zu,"
  97. " but given %zu(after align)", i, input_sizes_[i], aligned_size);
  98. return ACL_ERROR_GE_PARAM_INVALID;
  99. }
  100. }
  101. auto num_outputs = outputs.size();
  102. if (num_outputs != output_sizes_.size()) {
  103. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "output num mismatch. model expect %zu, but given %zu",
  104. output_sizes_.size(), outputs.size());
  105. return ACL_ERROR_GE_PARAM_INVALID;
  106. }
  107. for (size_t i = 0; i < num_outputs; ++i) {
  108. // preventing from write out of bound
  109. size_t aligned_size = GetAlignedSize(outputs[i].length);
  110. GELOGI("Output [%zu], aligned_size:%zu, outputs.length:%lu, output_sizes_:%zu",
  111. i, aligned_size, outputs[i].length, output_sizes_[i]);
  112. if (aligned_size < output_sizes_[i]) {
  113. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "Output size mismatch. index = %zu, model expect %zu,"
  114. "but given %zu(after align)", i, output_sizes_[i], aligned_size);
  115. return ACL_ERROR_GE_PARAM_INVALID;
  116. }
  117. }
  118. return SUCCESS;
  119. }
  120. Status SingleOp::GetArgs(const std::vector<DataBuffer> &inputs, const std::vector<DataBuffer> &outputs) {
  121. size_t arg_index = 0;
  122. for (auto &input : inputs) {
  123. args_[arg_index++] = reinterpret_cast<uintptr_t>(input.data);
  124. }
  125. for (auto &output : outputs) {
  126. args_[arg_index++] = reinterpret_cast<uintptr_t>(output.data);
  127. }
  128. return SUCCESS;
  129. }
  130. Status SingleOp::UpdateArgs(const std::vector<DataBuffer> &inputs, const std::vector<DataBuffer> &outputs) {
  131. Status ret = GetArgs(inputs, outputs);
  132. if (ret != SUCCESS) {
  133. return ret;
  134. }
  135. // update tbe task args
  136. size_t num_args = arg_table_.size();
  137. for (size_t i = 0; i < num_args; ++i) {
  138. std::vector<uintptr_t *> &ptr_to_arg_in_tasks = arg_table_[i];
  139. if (ptr_to_arg_in_tasks.empty()) {
  140. GELOGW("found NO arg address to update for arg[%lu]", i);
  141. continue;
  142. }
  143. for (uintptr_t *arg_addr : ptr_to_arg_in_tasks) {
  144. *arg_addr = args_[i];
  145. }
  146. }
  147. return SUCCESS;
  148. }
  149. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status SingleOp::ExecuteAsync(const std::vector<DataBuffer> &inputs,
  150. const std::vector<DataBuffer> &outputs) {
  151. Status ret = ValidateArgs(inputs, outputs);
  152. if (ret != SUCCESS) {
  153. return ret;
  154. }
  155. GE_CHECK_NOTNULL(stream_resource_);
  156. std::lock_guard<std::mutex> lk(*stream_mutex_);
  157. auto current_mem_base = stream_resource_->GetMemoryBase();
  158. if (running_param_->mem_base != current_mem_base) {
  159. running_param_->mem_base = const_cast<uint8_t *>(current_mem_base);
  160. GELOGD("Memory base changed, new memory base = %p", current_mem_base);
  161. for (auto &task : tasks_) {
  162. auto new_address = BuildTaskUtils::GetAddresses(task->GetOpdesc(), *running_param_);
  163. GE_CHK_STATUS_RET(task->UpdateArgTable(*running_param_),
  164. "[%s] Failed to update arg table",
  165. task->GetOpdesc()->GetName().c_str());
  166. }
  167. }
  168. ret = UpdateArgs(inputs, outputs);
  169. if (ret != SUCCESS) {
  170. return ret;
  171. }
  172. for (auto &task : tasks_) {
  173. ret = task->LaunchKernel(stream_);
  174. if (ret != SUCCESS) {
  175. return ret;
  176. }
  177. GE_CHK_STATUS_RET_NOLOG(ProfilingTaskInfo(task, kShapeTypeStatic));
  178. }
  179. return ret;
  180. }
  181. void SingleOp::SetStream(rtStream_t stream) {
  182. stream_ = stream;
  183. }
  184. DynamicSingleOp::DynamicSingleOp(uintptr_t resource_id, std::mutex *stream_mutex, rtStream_t stream)
  185. : resource_id_(resource_id), stream_mutex_(stream_mutex), stream_(stream) {
  186. }
  187. Status DynamicSingleOp::ValidateParams(const vector<GeTensorDesc> &input_desc,
  188. const std::vector<DataBuffer> &inputs,
  189. std::vector<GeTensorDesc> &output_desc,
  190. std::vector<DataBuffer> &outputs) const {
  191. if (inputs.size() != input_desc.size()) {
  192. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  193. "Input number mismatches input desc number. Input num = %zu, input desc num = %zu",
  194. inputs.size(),
  195. input_desc.size());
  196. return ACL_ERROR_GE_PARAM_INVALID;
  197. }
  198. if (outputs.size() != output_desc.size()) {
  199. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  200. "Output number mismatches output desc number. Output num = %zu, output desc num = %zu",
  201. outputs.size(),
  202. output_desc.size());
  203. return ACL_ERROR_GE_PARAM_INVALID;
  204. }
  205. if (input_desc.size() != num_inputs_) {
  206. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  207. "Input number mismatches. expect %zu, but given %zu",
  208. num_inputs_,
  209. input_desc.size());
  210. return ACL_ERROR_GE_PARAM_INVALID;
  211. }
  212. if (output_desc.size() != num_outputs_) {
  213. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  214. "Output number mismatches. expect %zu, but given %zu",
  215. num_outputs_,
  216. output_desc.size());
  217. return ACL_ERROR_GE_PARAM_INVALID;
  218. }
  219. return SUCCESS;
  220. }
  221. Status DynamicSingleOp::ExecuteAsync(const vector<GeTensorDesc> &input_desc,
  222. const vector<DataBuffer> &input_buffers,
  223. vector<GeTensorDesc> &output_desc,
  224. vector<DataBuffer> &output_buffers) {
  225. GE_CHECK_NOTNULL(op_task_);
  226. GE_CHK_STATUS_RET_NOLOG(ValidateParams(input_desc, input_buffers, output_desc, output_buffers));
  227. std::lock_guard<std::mutex> lk(*stream_mutex_);
  228. GE_CHK_STATUS_RET_NOLOG(op_task_->LaunchKernel(input_desc, input_buffers, output_desc, output_buffers, stream_));
  229. GE_CHK_STATUS_RET_NOLOG(ProfilingTaskInfo(op_task_.get(), kShapeTypeDynamic));
  230. return SUCCESS;
  231. }
  232. } // 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