How to use model_execute method in fMBT

Best Python code snippet using fMBT_python

main.py

Source:main.py Github

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...57 D = data_input_config.D58 Q = data_input_config.Q59 s = data_input_config.s60# model execute61model.model_execute(p, d, q, P, D, Q, s)62model.residuals_analysis()63model.acf_pacf_residuals()64model.ts_residuals_plot()65model.adjust_predict()...

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main_test.py

Source:main_test.py Github

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1from test import *2# Ignore warnings3import warnings4warnings.filterwarnings("ignore")5### Initialize6opt = Args()7opt.set_graphtype('pivotMds_grid')8#opt.scale = 4009print(opt.__dict__) 10### Modify the epoch number to the suitable value11epoch=150012# model_execute = "ModelName_DatasetName_TrialID"13# model_execute = "GraphLSTM_pyg-grid_v2-demo1"14model_execute = "GraphLSTM_pyg-pivotMds_grid-demo1"15model_name = 'model_'+model_execute+'_'+str(epoch)+'.pkl'16model_file = opt.main_data_folder + 'model_save/' + model_name17opt.DGL_input = False # Set this value as True, if the trained model is GraphLSTM_dgl; Otherwise, set it as False.18opt.PYG_input = True # Set this value as False, if the trained model is GraphLSTM_pyg; Otherwise, set it as False.19folder_prefix = opt.main_data_folder + 'testing_results/'20bfs_order = False21scale_constant = 122pred_scale_constant = 123PA_corrected = True24cpu_mode = False25Scale_corrected = True26### Clean Folder27if os.path.exists(folder_prefix):28 shutil.rmtree(folder_prefix)29if not os.path.exists(folder_prefix):30 os.mkdir(folder_prefix)31### Read Model32if cpu_mode == True:33 model = torch.load(model_file, map_location=lambda storage, loc: storage)34else:35 model = torch.load(model_file)36# ## Copy model in testing_results 37# shutil.copyfile(model_file,folder_prefix+model_name)38## Initialize Dataset39graph_dataset,valid_graph_dataset,test_graph_dataset = getdataset(opt)40## Begin test samples from test dataset41model_testdataset_inference_params = {42 "max_samples":24,43 "dataset":test_graph_dataset,44 "test_params":{45 "folder":folder_prefix+'test_random/',46 "model":model,47 "opt":opt,48 "cpu_mode":cpu_mode,49 "bfs_order":bfs_order,50 "Scale_corrected":Scale_corrected,51 "PA_corrected":PA_corrected,52 "scale_constant":scale_constant,53 "pred_scale_constant":pred_scale_constant54 }55}...

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ModelExecuteDao.py

Source:ModelExecuteDao.py Github

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...17 return query18 except Exception:19 print(traceback.print_exc())20 return False21def create_model_execute(model_execute):22 """23 创建 model_execute24 :param model_execute: 类型 ModelExecute25 :return:26 """27 try:28 session = db.session29 session.add(model_execute)30 session.commit()31 print('成功创建一条执行记录')32 return model_execute33 except Exception:34 print(traceback.print_exc())35 return False36def update_model_execute(model_execute_id, status, run_info, end_time):37 """38 更新 model_execute39 :param model_execute_id:40 :param status:41 :param run_info:42 :param end_time:43 :return:44 """45 try:46 filters = {47 ModelExecute.id == model_execute_id,48 }49 result = ModelExecute.query.filter(*filters).first()50 result.status = status...

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