/** * Copyright 2019 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #ifndef MINDSPORE_CCSRC_DEBUG_TENSOR_LOAD_H_ #define MINDSPORE_CCSRC_DEBUG_TENSOR_LOAD_H_ #include #include #include #include #include #include #include #include "debug/tensor_data.h" #include "debug/data_dump/dump_json_parser.h" #include "ir/dtype.h" namespace mindspore { class TensorLoader { public: TensorLoader() : iter_num(-1) {} ~TensorLoader() { EmptyTensor(); } void MoveTensorCurrentToPrev(std::string tensor_name) { auto handle = tensor_list_map.extract(tensor_name); if (!handle.empty()) { MS_LOG(INFO) << "Moving " << tensor_name << " from current map to previous map"; prev_tensor_list_map.insert(std::move(handle)); } } void SwapCurrentPrev() { tensor_list_map.swap(prev_tensor_list_map); } bool TensorExistsInCurrent(std::string tensor_name) { return tensor_list_map.find(tensor_name) != tensor_list_map.end(); } // only parameters will return true bool PrevTensorExistsInCurrent(std::string tensor_name) { return TensorExistsInCurrent(tensor_name + ":prev"); } void MoveParametersCurrentToPrev() { MS_LOG(INFO) << "Moving parameters from current map to previous map"; auto iter = tensor_list_map.begin(); while (iter != tensor_list_map.end()) { auto key = iter->first; if (PrevTensorExistsInCurrent(key)) { // :prev tensor only exists for parameter. Move it to prev ++iter; MoveTensorCurrentToPrev(key); } else { ++iter; } } } bool IsPrevTensor(std::string tensor_name) { const std::string suffix = ":prev"; if (tensor_name.length() <= suffix.length()) return false; return std::equal(suffix.rbegin(), suffix.rend(), tensor_name.rbegin()); } bool LoadNewTensor(std::shared_ptr tensor, bool keep_prev) { std::lock_guard lg(lock_); if (keep_prev) { // add prev step tensor into current step map with ":prev" suffix auto handle = prev_tensor_list_map.extract(tensor->GetName()); if (!handle.empty()) { handle.key() = tensor->GetName() + ":prev"; tensor_list_map.insert(std::move(handle)); } } tensor_list_map[tensor->GetName()] = tensor; // use [] instead of insert to ensure latest value auto node_name = tensor->GetName(); node_name = node_name.substr(0, node_name.find_first_of(":")); node_tensor_map.insert({node_name, tensor}); return true; } std::vector> GetTensor() { std::vector> tensor_list; for (auto &it : tensor_list_map) { if (!IsPrevTensor(it.first)) tensor_list.push_back(it.second); } return tensor_list; } std::shared_ptr GetTensor(const std::string &tensor_name) { auto iter = tensor_list_map.find(tensor_name); if (iter != tensor_list_map.end()) return iter->second; return nullptr; } uint32_t GetIterNum() { return iter_num; } std::map> GetTensorMap() { return tensor_list_map; } std::shared_ptr GetPrevTensor(const std::string &tensor_name) { if (tensor_list_map.find(tensor_name + ":prev") != tensor_list_map.end()) { return tensor_list_map[tensor_name + ":prev"]; } return nullptr; } std::vector> GetNodeTensorMap(std::string node_name) { std::vector> tensors; for (auto itr = node_tensor_map.begin(); itr != node_tensor_map.end(); itr++) { if (itr->first == node_name) { tensors.push_back(itr->second); } } return tensors; } void SearchTensors(const std::vector &search_list, std::vector>> *result_list) { for (auto i : search_list) { std::map>::iterator iter; iter = tensor_list_map.find(i); if (iter != tensor_list_map.end()) { result_list->push_back(std::make_tuple(i, iter->second)); } else { result_list->push_back(std::make_tuple(i, nullptr)); } } } void EmptyTensor() { std::lock_guard lg(lock_); prev_tensor_list_map.clear(); node_tensor_map.clear(); tensor_list_map.swap(prev_tensor_list_map); } void EmptyPrevTensor() { prev_tensor_list_map.clear(); } void EmptyCurrentTensor() { tensor_list_map.clear(); node_tensor_map.clear(); } void set_iter_num(uint32_t iter_num) { this->iter_num = iter_num; } bool DumpTensorToFile(const std::string &tensor_name, bool trans_flag, const std::string &filepath, const std::string &host_fmt, const std::vector &host_shape, TypeId host_type, TypeId addr_type_id, const std::string &addr_format, size_t slot) const { if (filepath.empty()) { MS_LOG(ERROR) << "Dump file path is null!"; return false; } std::string shape = "shape"; if (host_shape.size()) { for (auto &value : host_shape) { shape = shape + '_' + std::to_string(value); } } else { shape = shape + "_0"; } std::string file_extension = ".bin"; std::string path = ""; if (trans_flag) { path = filepath + '_' + shape + '_' + TypeIdLabel(host_type) + '_' + host_fmt + file_extension; } else { path = filepath + '_' + shape + '_' + TypeIdToType(addr_type_id)->ToString() + '_' + addr_format + file_extension; } MS_LOG(INFO) << "Dump path is " << path; std::string tensor_loader_name = tensor_name + ":" + std::to_string(slot); auto iter = tensor_list_map.find(tensor_loader_name); if (iter != tensor_list_map.end()) { std::shared_ptr node = iter->second; mindspore::tensor::TensorPtr out_tensor = node->GetTensor(); size_t host_size = out_tensor->data().nbytes(); return DumpJsonParser::DumpToFile(path, out_tensor->data_c(), host_size); } MS_LOG(INFO) << "Tensor name:" << tensor_name << " not found in tensor_list_map"; return true; } private: std::map> tensor_list_map; std::multimap> node_tensor_map; std::map> prev_tensor_list_map; uint32_t iter_num; std::mutex lock_; }; } // namespace mindspore #endif // MINDSPORE_CCSRC_DEBUG_TENSOR_LOAD_H_