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single_op.cc 9.9 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/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/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. auto rt_ret = rtGetTaskIdAndStreamID(&task_id, &stream_id);
  55. if (rt_ret != RT_ERROR_NONE) {
  56. GELOGE(rt_ret, "Get task_id and stream_id failed.");
  57. return RT_ERROR_TO_GE_STATUS(rt_ret);
  58. }
  59. TaskDescInfo tmp_task_desc_info;
  60. tmp_task_desc_info.model_name = model_name;
  61. tmp_task_desc_info.op_name = op_name;
  62. tmp_task_desc_info.block_dim = block_dim;
  63. tmp_task_desc_info.task_id = task_id;
  64. tmp_task_desc_info.stream_id = stream_id;
  65. tmp_task_desc_info.shape_type = shape_type;
  66. tmp_task_desc_info.cur_iter_num = 0;
  67. tmp_task_desc_info.task_type = op_task->GetTaskType();
  68. GELOGD("GetTaskDescInfo of op [%s] end, task_id[%u], stream_id[%u]", op_name.c_str(), task_id, stream_id);
  69. task_desc_info.emplace_back(tmp_task_desc_info);
  70. std::vector<ComputeGraphDescInfo> compute_graph_info;
  71. auto &profiling_manager = ProfilingManager::Instance();
  72. profiling_manager.ReportProfilingData(model_id, task_desc_info, compute_graph_info);
  73. return SUCCESS;
  74. }
  75. } // namespace
  76. SingleOp::SingleOp(StreamResource *stream_resource, std::mutex *stream_mutex, rtStream_t stream)
  77. : stream_resource_(stream_resource), stream_mutex_(stream_mutex), stream_(stream) {
  78. }
  79. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY SingleOp::~SingleOp() {
  80. for (auto task : tasks_) {
  81. delete task;
  82. task = nullptr;
  83. }
  84. }
  85. Status SingleOp::ValidateArgs(const std::vector<DataBuffer> &inputs, const std::vector<DataBuffer> &outputs) {
  86. auto num_inputs = inputs.size();
  87. if (num_inputs != input_sizes_.size()) {
  88. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "Input num mismatch. model expect %zu, but given %zu", input_addr_list_.size(),
  89. inputs.size());
  90. return ACL_ERROR_GE_PARAM_INVALID;
  91. }
  92. for (size_t i = 0; i < num_inputs; ++i) {
  93. // preventing from read out of bound
  94. size_t aligned_size = GetAlignedSize(inputs[i].length);
  95. GELOGI("Input [%zu], aligned_size:%zu, inputs.length:%lu, input_sizes_:%zu",
  96. i, aligned_size, inputs[i].length, input_sizes_[i]);
  97. if (aligned_size < input_sizes_[i]) {
  98. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "Input size mismatch. index = %zu, model expect %zu,"
  99. " but given %zu(after align)", i, input_sizes_[i], aligned_size);
  100. return ACL_ERROR_GE_PARAM_INVALID;
  101. }
  102. }
  103. auto num_outputs = outputs.size();
  104. if (num_outputs != output_sizes_.size()) {
  105. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "output num mismatch. model expect %zu, but given %zu",
  106. output_sizes_.size(), outputs.size());
  107. return ACL_ERROR_GE_PARAM_INVALID;
  108. }
  109. for (size_t i = 0; i < num_outputs; ++i) {
  110. // preventing from write out of bound
  111. size_t aligned_size = GetAlignedSize(outputs[i].length);
  112. GELOGI("Output [%zu], aligned_size:%zu, outputs.length:%lu, output_sizes_:%zu",
  113. i, aligned_size, outputs[i].length, output_sizes_[i]);
  114. if (aligned_size < output_sizes_[i]) {
  115. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "Output size mismatch. index = %zu, model expect %zu,"
  116. "but given %zu(after align)", i, output_sizes_[i], aligned_size);
  117. return ACL_ERROR_GE_PARAM_INVALID;
  118. }
  119. }
  120. return SUCCESS;
  121. }
  122. Status SingleOp::GetArgs(const std::vector<DataBuffer> &inputs, const std::vector<DataBuffer> &outputs) {
  123. size_t arg_index = 0;
  124. for (auto &input : inputs) {
  125. args_[arg_index++] = reinterpret_cast<uintptr_t>(input.data);
  126. }
  127. for (auto &output : outputs) {
  128. args_[arg_index++] = reinterpret_cast<uintptr_t>(output.data);
  129. }
  130. return SUCCESS;
  131. }
  132. Status SingleOp::UpdateArgs(const std::vector<DataBuffer> &inputs, const std::vector<DataBuffer> &outputs) {
  133. Status ret = GetArgs(inputs, outputs);
  134. if (ret != SUCCESS) {
  135. return ret;
  136. }
  137. // update tbe task args
  138. size_t num_args = arg_table_.size();
  139. for (size_t i = 0; i < num_args; ++i) {
  140. std::vector<uintptr_t *> &ptr_to_arg_in_tasks = arg_table_[i];
  141. if (ptr_to_arg_in_tasks.empty()) {
  142. GELOGW("found NO arg address to update for arg[%lu]", i);
  143. continue;
  144. }
  145. for (uintptr_t *arg_addr : ptr_to_arg_in_tasks) {
  146. *arg_addr = args_[i];
  147. }
  148. }
  149. return SUCCESS;
  150. }
  151. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status SingleOp::ExecuteAsync(const std::vector<DataBuffer> &inputs,
  152. const std::vector<DataBuffer> &outputs) {
  153. Status ret = ValidateArgs(inputs, outputs);
  154. if (ret != SUCCESS) {
  155. return ret;
  156. }
  157. GE_CHECK_NOTNULL(stream_resource_);
  158. std::lock_guard<std::mutex> lk(*stream_mutex_);
  159. auto current_mem_base = stream_resource_->GetMemoryBase();
  160. if (running_param_->mem_base != current_mem_base) {
  161. running_param_->mem_base = const_cast<uint8_t *>(current_mem_base);
  162. GELOGD("Memory base changed, new memory base = %p", current_mem_base);
  163. for (auto &task : tasks_) {
  164. auto new_address = BuildTaskUtils::GetAddresses(task->GetOpdesc(), *running_param_);
  165. GE_CHK_STATUS_RET(task->UpdateArgTable(*running_param_),
  166. "[%s] Failed to update arg table",
  167. task->GetOpdesc()->GetName().c_str());
  168. }
  169. }
  170. ret = UpdateArgs(inputs, outputs);
  171. if (ret != SUCCESS) {
  172. return ret;
  173. }
  174. for (auto &task : tasks_) {
  175. ret = task->LaunchKernel(stream_);
  176. if (ret != SUCCESS) {
  177. return ret;
  178. }
  179. GE_CHK_STATUS_RET_NOLOG(ProfilingTaskInfo(task, kShapeTypeStatic));
  180. }
  181. return ret;
  182. }
  183. void SingleOp::SetStream(rtStream_t stream) {
  184. stream_ = stream;
  185. }
  186. DynamicSingleOp::DynamicSingleOp(uintptr_t resource_id, std::mutex *stream_mutex, rtStream_t stream)
  187. : resource_id_(resource_id), stream_mutex_(stream_mutex), stream_(stream) {
  188. }
  189. Status DynamicSingleOp::ValidateParams(const vector<GeTensorDesc> &input_desc,
  190. const std::vector<DataBuffer> &inputs,
  191. std::vector<GeTensorDesc> &output_desc,
  192. std::vector<DataBuffer> &outputs) const {
  193. if (inputs.size() != input_desc.size()) {
  194. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  195. "Input number mismatches input desc number. Input num = %zu, input desc num = %zu",
  196. inputs.size(),
  197. input_desc.size());
  198. return ACL_ERROR_GE_PARAM_INVALID;
  199. }
  200. if (outputs.size() != output_desc.size()) {
  201. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  202. "Output number mismatches output desc number. Output num = %zu, output desc num = %zu",
  203. outputs.size(),
  204. output_desc.size());
  205. return ACL_ERROR_GE_PARAM_INVALID;
  206. }
  207. if (input_desc.size() != num_inputs_) {
  208. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  209. "Input number mismatches. expect %zu, but given %zu",
  210. num_inputs_,
  211. input_desc.size());
  212. return ACL_ERROR_GE_PARAM_INVALID;
  213. }
  214. if (output_desc.size() != num_outputs_) {
  215. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  216. "Output number mismatches. expect %zu, but given %zu",
  217. num_outputs_,
  218. output_desc.size());
  219. return ACL_ERROR_GE_PARAM_INVALID;
  220. }
  221. return SUCCESS;
  222. }
  223. Status DynamicSingleOp::ExecuteAsync(const vector<GeTensorDesc> &input_desc,
  224. const vector<DataBuffer> &input_buffers,
  225. vector<GeTensorDesc> &output_desc,
  226. vector<DataBuffer> &output_buffers) {
  227. GE_CHECK_NOTNULL(op_task_);
  228. GE_CHK_STATUS_RET_NOLOG(ValidateParams(input_desc, input_buffers, output_desc, output_buffers));
  229. std::lock_guard<std::mutex> lk(*stream_mutex_);
  230. GE_CHK_STATUS_RET_NOLOG(op_task_->LaunchKernel(input_desc, input_buffers, output_desc, output_buffers, stream_));
  231. GE_CHK_STATUS_RET_NOLOG(ProfilingTaskInfo(op_task_.get(), kShapeTypeDynamic));
  232. return SUCCESS;
  233. }
  234. } // 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