// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. // // 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. #include "paddle/fluid/jit/serializer.h" #include #include "paddle/fluid/framework/var_desc.h" #include "paddle/fluid/framework/variable.h" #include "paddle/fluid/platform/device_context.h" #include "paddle/fluid/jit/executor_function.h" #include "paddle/fluid/jit/layer.h" #include "paddle/fluid/jit/pe_function.h" #include "paddle/fluid/jit/property.h" #include "paddle/fluid/jit/serializer_utils.h" DECLARE_string(jit_engine_type); namespace paddle { namespace jit { Layer Deserializer::operator()(const std::string& path, const phi::Place& place) { const auto& pdmodel_paths = utils::PdmodelFilePaths(path); // set is ordered std::set param_names_set; std::vector> infos; Name2VariableMap params_dict; for (auto& it : pdmodel_paths) { auto& func_name = it.first; auto program_desc = LoadProgram(it.second); // TODO(dev): load int/float attrs std::vector persist_var_names; auto all_var_desc = program_desc.Block(0).AllVars(); for (auto* desc_ptr : all_var_desc) { if (utils::IsPersistable(desc_ptr)) { persist_var_names.emplace_back(desc_ptr->Name()); } } param_names_set.insert(persist_var_names.begin(), persist_var_names.end()); infos.emplace_back(std::make_shared( func_name, persist_var_names, program_desc)); } ReadTensorData(path + PDPARAMS_SUFFIX, param_names_set, place, ¶ms_dict); // ReadAttributeData(); Layer layer = Layer(params_dict, place); for (auto& info : infos) { if (FLAGS_jit_engine_type == "Executor") { VLOG(3) << "Add function type: ExecutorFunction."; layer.SetFunction( info->FunctionName(), utils::MakeFunction(info, params_dict, place)); } else if (FLAGS_jit_engine_type == "PE") { VLOG(3) << "Add function type: PEFunction."; layer.SetFunction( info->FunctionName(), utils::MakeFunction(info, params_dict, place)); } else { PD_THROW("Invalid JitLayer funciton type."); } } return layer; } void Deserializer::ReadTensorData(const std::string& file_name, const std::set& var_name, const phi::Place& place, Name2VariableMap* params_dict) const { VLOG(3) << "ReadTensorData from: " << file_name; std::ifstream fin(file_name, std::ios::binary); platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance(); auto& dev_ctx = *pool.Get(place); for (auto it = var_name.begin(); it != var_name.end(); it++) { VLOG(3) << "load Tensor: " << *it; Variable v; // TODO(dev): Support framework::Vocab DenseTensor* dense_tesnor = v.GetMutable(); framework::DeserializeFromStream(fin, dense_tesnor, dev_ctx); (*params_dict)[*it] = std::make_shared(v); } } void Deserializer::ReadAttributeData(const std::string& file_path, Name2VariableMap* attrs_dict) const {} framework::ProgramDesc Deserializer::LoadProgram(const std::string& file_name) { VLOG(3) << "LoadProgram from: " << file_name; std::ifstream fin(file_name, std::ios::in | std::ios::binary); fin.seekg(0, std::ios::end); std::string buffer(fin.tellg(), ' '); fin.seekg(0, std::ios::beg); fin.read(&buffer[0], buffer.size()); fin.close(); return framework::ProgramDesc(buffer); } Layer Load(const std::string& file_path, const phi::Place& place) { auto deserializer = Deserializer(); return deserializer(file_path, place); } } // namespace jit } // namespace paddle