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

  Demo DMFAL 
  seed: 4 
  interp_data: True 

----------------------------------------
---> module config
  dataset: {'name': 'Heat_mfGent_v5', 'interp_data': True, 'seed': 4, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[1]', '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: 30
  non_subset: True
  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           	0.10686     	-22710323626.65959	0.14684     	0           
  10          	0.10677     	-26209971.57588	0.14673     	0           
  100         	0.04141     	-1.68998    	0.05977     	1           
  300         	0.02506     	0.40890     	0.04464     	3           
  500         	0.02586     	0.60875     	0.04237     	6           
  1000        	0.02573     	0.60577     	0.04398     	13          
---> try to load best state
              	0.02573     	0.60577     	0.04398     	13               eval state : test_on_restore;
              	0.02573     	0.60577     	0.04398     	13               eval state : test_on_last_epoch;
---> final result
              	0.02573     	0.60577     	0.04398     	13               eval state : final;module_name : dmfal;subset : 2.0;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 4 
  interp_data: True 

----------------------------------------
---> module config
  dataset: {'name': 'Heat_mfGent_v5', 'interp_data': True, 'seed': 4, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[1]', '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: 28
  non_subset: True
  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           	0.09991     	-23271805300.80449	0.13915     	0           
  10          	0.09990     	-15377969.45016	0.13914     	0           
  100         	0.03357     	-4.12988    	0.04693     	1           
  300         	0.01863     	0.81850     	0.02866     	4           
  500         	0.01531     	0.85873     	0.02411     	7           
  1000        	0.01425     	0.85330     	0.02745     	14          
---> try to load best state
              	0.01425     	0.85330     	0.02745     	14               eval state : test_on_restore;
              	0.01425     	0.85330     	0.02745     	14               eval state : test_on_last_epoch;
---> final result
              	0.01425     	0.85330     	0.02745     	14               eval state : final;module_name : dmfal;subset : 4.0;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 4 
  interp_data: True 

----------------------------------------
---> module config
  dataset: {'name': 'Heat_mfGent_v5', 'interp_data': True, 'seed': 4, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[1]', '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: 24
  non_subset: True
  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           	0.09629     	-28559206336.07841	0.13637     	0           
  10          	0.09638     	-113036569.18254	0.13643     	0           
  100         	0.02580     	-2.97824    	0.04506     	1           
  300         	0.01845     	0.56681     	0.02979     	4           
  500         	0.01325     	0.79263     	0.02379     	7           
  1000        	0.01100     	0.86968     	0.02532     	15          
---> try to load best state
              	0.01100     	0.86968     	0.02532     	15               eval state : test_on_restore;
              	0.01100     	0.86968     	0.02532     	16               eval state : test_on_last_epoch;
---> final result
              	0.01100     	0.86968     	0.02532     	16               eval state : final;module_name : dmfal;subset : 8.0;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 4 
  interp_data: True 

----------------------------------------
---> module config
  dataset: {'name': 'Heat_mfGent_v5', 'interp_data': True, 'seed': 4, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[1]', '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: 16
  non_subset: True
  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           	0.09106     	-35563313027.70053	0.13373     	0           
  10          	0.09095     	-38916773.02570	0.13368     	0           
  100         	0.02745     	-159.31948  	0.04375     	1           
  300         	0.01901     	0.36918     	0.03050     	4           
  500         	0.01088     	0.73129     	0.02626     	8           
  1000        	0.01390     	0.90175     	0.02774     	15          
---> try to load best state
              	0.01390     	0.90175     	0.02774     	15               eval state : test_on_restore;
              	0.01390     	0.90175     	0.02774     	15               eval state : test_on_last_epoch;
---> final result
              	0.01390     	0.90175     	0.02774     	15               eval state : final;module_name : dmfal;subset : 16.0;cp_record_file : True;
