----------------------------------------

  Demo DMFAL 
  seed: None 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'burger_v4_02', 'interp_data': False, 'seed': None, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[0]', 'y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  second_fidelity_sample: 4
  second_fidelity_start_index: 0
  non_subset: False
  lr: {'opt_param': 0.01}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  nn_param: {'hlayers_w': [40, 40], 'hlayers_d': [2, 2], 'base_dim': [32, 32], 'activation': 'relu', 'M': 2}
  reg_strength: 0.001
---> training record
  epoch       	mae         	r2          	rmse        	time        
  1           	0.04153     	-18707935459.98011	0.08285     	0           
  10          	0.04144     	-29783632.97785	0.08270     	0           
  100         	0.01135     	-0.75087    	0.02658     	0           
  300         	0.01239     	0.65206     	0.02765     	1           
  500         	0.00893     	0.74715     	0.02332     	2           
  1000        	0.00632     	0.85547     	0.01714     	4           
---> try to load best state
              	0.00632     	0.85547     	0.01714     	4                eval state : test_on_restore;
              	0.00632     	0.85547     	0.01714     	4                eval state : test_on_last_epoch;
---> final result
              	0.00632     	0.85547     	0.01714     	4                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

----------------------------------------

  Demo DMFAL 
  seed: None 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'burger_v4_02', 'interp_data': False, 'seed': None, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[0]', 'y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  second_fidelity_sample: 8
  second_fidelity_start_index: 0
  non_subset: False
  lr: {'opt_param': 0.01}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  nn_param: {'hlayers_w': [40, 40], 'hlayers_d': [2, 2], 'base_dim': [32, 32], 'activation': 'relu', 'M': 2}
  reg_strength: 0.001
---> training record
  epoch       	mae         	r2          	rmse        	time        
  1           	0.03184     	-6991972043.11315	0.07167     	0           
  10          	0.03184     	-7395999.03381	0.07166     	0           
  100         	0.00779     	0.71714     	0.02617     	0           
  300         	0.00785     	0.81860     	0.02684     	1           
  500         	0.00716     	0.85865     	0.02576     	2           
  1000        	0.00310     	0.96531     	0.00899     	4           
---> try to load best state
              	0.00310     	0.96531     	0.00899     	4                eval state : test_on_restore;
              	0.00310     	0.96531     	0.00899     	4                eval state : test_on_last_epoch;
---> final result
              	0.00310     	0.96531     	0.00899     	4                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

----------------------------------------

  Demo DMFAL 
  seed: None 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'burger_v4_02', 'interp_data': False, 'seed': None, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[0]', 'y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  second_fidelity_sample: 16
  second_fidelity_start_index: 0
  non_subset: False
  lr: {'opt_param': 0.01}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  nn_param: {'hlayers_w': [40, 40], 'hlayers_d': [2, 2], 'base_dim': [32, 32], 'activation': 'relu', 'M': 2}
  reg_strength: 0.001
---> training record
  epoch       	mae         	r2          	rmse        	time        
  1           	0.02812     	-9946658803.68223	0.06880     	0           
  10          	0.02809     	-14877766.61654	0.06877     	0           
  100         	0.01313     	0.77072     	0.03247     	0           
  300         	0.00979     	0.56330     	0.03006     	2           
  500         	0.00843     	0.86869     	0.02332     	3           
  1000        	0.00443     	0.97802     	0.01198     	7           
---> try to load best state
              	0.00443     	0.97802     	0.01198     	7                eval state : test_on_restore;
              	0.00443     	0.97802     	0.01198     	7                eval state : test_on_last_epoch;
---> final result
              	0.00443     	0.97802     	0.01198     	7                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

----------------------------------------

  Demo DMFAL 
  seed: None 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'burger_v4_02', 'interp_data': False, 'seed': None, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[0]', 'y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  second_fidelity_sample: 32
  second_fidelity_start_index: 0
  non_subset: False
  lr: {'opt_param': 0.01}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  nn_param: {'hlayers_w': [40, 40], 'hlayers_d': [2, 2], 'base_dim': [32, 32], 'activation': 'relu', 'M': 2}
  reg_strength: 0.001
---> training record
  epoch       	mae         	r2          	rmse        	time        
  1           	0.02657     	-5892052585.43065	0.06797     	0           
  10          	0.02662     	-8465969.65579	0.06797     	0           
  100         	0.01074     	0.51398     	0.02800     	0           
  300         	0.00903     	0.46503     	0.02734     	2           
  500         	0.01052     	0.81540     	0.02944     	3           
  1000        	0.00476     	0.95264     	0.01386     	7           
---> try to load best state
              	0.00476     	0.95264     	0.01386     	7                eval state : test_on_restore;
              	0.00476     	0.95264     	0.01386     	7                eval state : test_on_last_epoch;
---> final result
              	0.00476     	0.95264     	0.01386     	7                eval state : final;module_name : dmfal;cp_record_file : True;
