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

  Demo DMFAL 
  seed: 0 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 256, '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           	0.17165     	-5682293547312.33301	0.53602     	0           
  10          	0.17163     	-973499070.60415	0.53600     	0           
  100         	0.12863     	-48.53845   	0.48372     	0           
  300         	0.11651     	-22.22358   	0.46147     	0           
  500         	0.11193     	-17.88747   	0.45427     	1           
  1000        	0.10947     	-15.07511   	0.44900     	2           
---> try to load best state
              	0.10947     	-15.07511   	0.44900     	2                eval state : test_on_restore;
              	0.10947     	-15.07511   	0.44900     	2                eval state : test_on_last_epoch;
---> final result
              	0.10947     	-15.07511   	0.44900     	2                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 0 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 256, '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           	0.17175     	-46316507109.53691	0.53631     	0           
  10          	0.17171     	-140169529.29326	0.53627     	0           
  100         	0.13663     	-86.47910   	0.49711     	0           
  300         	0.10489     	-7.85802    	0.42894     	0           
  500         	0.10813     	-14.13042   	0.44790     	1           
  1000        	0.10504     	-8.44687    	0.43233     	3           
---> try to load best state
              	0.10504     	-8.44687    	0.43233     	3                eval state : test_on_restore;
              	0.10504     	-8.44687    	0.43233     	3                eval state : test_on_last_epoch;
---> final result
              	0.10504     	-8.44687    	0.43233     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 0 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 256, '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           	0.17257     	-12156948544.37930	0.53032     	0           
  10          	0.17238     	-6856932.98752	0.53030     	0           
  100         	0.10203     	-8.01439    	0.41592     	0           
  300         	0.10939     	-17.42478   	0.44082     	0           
  500         	0.09754     	-9.58548    	0.41545     	1           
  1000        	0.09132     	-6.56266    	0.40152     	2           
---> try to load best state
              	0.09132     	-6.56266    	0.40152     	2                eval state : test_on_restore;
              	0.09132     	-6.56266    	0.40152     	2                eval state : test_on_last_epoch;
---> final result
              	0.09132     	-6.56266    	0.40152     	2                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 0 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 256, '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           	0.17854     	-1021960490.89065	0.52319     	0           
  10          	0.17826     	-1084846.29960	0.52293     	0           
  100         	0.08221     	-2.96324    	0.36465     	0           
  300         	0.07046     	-1.78046    	0.33062     	0           
  500         	0.06369     	-1.19120    	0.31546     	1           
  1000        	0.06578     	-1.41113    	0.32126     	2           
---> try to load best state
              	0.06578     	-1.41113    	0.32126     	2                eval state : test_on_restore;
              	0.06578     	-1.41113    	0.32126     	2                eval state : test_on_last_epoch;
---> final result
              	0.06578     	-1.41113    	0.32126     	2                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 0 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 256, '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: 64
  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           	0.28635     	-19891323.77753	0.51278     	0           
  10          	0.29042     	-133632.81256	0.51338     	0           
  100         	0.06941     	0.59890     	0.15551     	0           
  300         	0.02874     	0.68649     	0.11356     	0           
  500         	0.02933     	0.66522     	0.11210     	1           
  1000        	0.03512     	0.68579     	0.11486     	2           
---> try to load best state
              	0.03512     	0.68579     	0.11486     	2                eval state : test_on_restore;
              	0.03512     	0.68579     	0.11486     	2                eval state : test_on_last_epoch;
---> final result
              	0.03512     	0.68579     	0.11486     	2                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 0 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 256, '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: 128
  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           	0.25883     	-21087559.32091	0.50721     	0           
  10          	0.25842     	-155337.47110	0.50649     	0           
  100         	0.07437     	0.05999     	0.20297     	0           
  300         	0.03863     	0.44942     	0.14639     	0           
  500         	0.02922     	0.71196     	0.11496     	1           
  1000        	0.03842     	0.60361     	0.12467     	3           
---> try to load best state
              	0.03842     	0.60361     	0.12467     	3                eval state : test_on_restore;
              	0.03842     	0.60361     	0.12467     	3                eval state : test_on_last_epoch;
---> final result
              	0.03842     	0.60361     	0.12467     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 0 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 256, '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: 256
  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           	0.26097     	-17846467.50478	0.50712     	0           
  10          	0.25938     	-86955.99793	0.50622     	0           
  100         	0.10977     	0.78148     	0.24103     	0           
  300         	0.02736     	0.87590     	0.08672     	0           
  500         	0.04124     	0.91297     	0.15339     	1           
  1000        	0.02937     	0.87259     	0.09032     	3           
---> try to load best state
              	0.02937     	0.87259     	0.09032     	3                eval state : test_on_restore;
              	0.02937     	0.87259     	0.09032     	3                eval state : test_on_last_epoch;
---> final result
              	0.02937     	0.87259     	0.09032     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 1 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 256, '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           	0.17182     	-28760724637.36365	0.53216     	0           
  10          	0.17180     	-86858924.44737	0.53210     	0           
  100         	0.12183     	-27.79913   	0.46276     	0           
  300         	0.10672     	-9.81703    	0.42183     	0           
  500         	0.10636     	-9.38600    	0.41845     	1           
  1000        	0.10604     	-9.14755    	0.41883     	2           
---> try to load best state
              	0.10604     	-9.14755    	0.41883     	2                eval state : test_on_restore;
              	0.10604     	-9.14755    	0.41883     	2                eval state : test_on_last_epoch;
---> final result
              	0.10604     	-9.14755    	0.41883     	2                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 1 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 256, '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           	0.18565     	-921441067.00717	0.51866     	0           
  10          	0.18548     	-5124727.02721	0.51856     	0           
  100         	0.08859     	-3.66291    	0.37467     	0           
  300         	0.07849     	-1.56978    	0.32886     	0           
  500         	0.07188     	-1.13982    	0.32110     	1           
  1000        	0.08201     	-2.33792    	0.35643     	2           
---> try to load best state
              	0.08201     	-2.33792    	0.35643     	2                eval state : test_on_restore;
              	0.08201     	-2.33792    	0.35643     	2                eval state : test_on_last_epoch;
---> final result
              	0.08201     	-2.33792    	0.35643     	2                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 1 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 256, '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           	0.20091     	-12704656193.24653	0.51171     	0           
  10          	0.20173     	-2634343.87878	0.51123     	0           
  100         	0.06877     	-0.81754    	0.30138     	0           
  300         	0.04769     	0.67234     	0.17502     	1           
  500         	0.04637     	0.33753     	0.21558     	2           
  1000        	0.04450     	0.42296     	0.19825     	4           
---> try to load best state
              	0.04450     	0.42296     	0.19825     	4                eval state : test_on_restore;
              	0.04450     	0.42296     	0.19825     	4                eval state : test_on_last_epoch;
---> final result
              	0.04450     	0.42296     	0.19825     	4                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 1 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 256, '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           	0.21575     	-8637345895.58792	0.50787     	0           
  10          	0.21415     	-1060044.89551	0.50791     	0           
  100         	0.06449     	-0.47625    	0.27212     	0           
  300         	0.04626     	0.43319     	0.20025     	1           
  500         	0.04134     	0.38433     	0.20420     	2           
  1000        	0.03632     	0.52017     	0.17876     	4           
---> try to load best state
              	0.03632     	0.52017     	0.17876     	4                eval state : test_on_restore;
              	0.03632     	0.52017     	0.17876     	4                eval state : test_on_last_epoch;
---> final result
              	0.03632     	0.52017     	0.17876     	4                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 1 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 256, '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: 64
  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           	0.22939     	-387766547.17701	0.50614     	0           
  10          	0.22885     	-398825.60174	0.50571     	0           
  100         	0.06928     	0.27283     	0.24733     	0           
  300         	0.02945     	0.79136     	0.11586     	1           
  500         	0.03880     	0.75756     	0.12575     	1           
  1000        	0.02679     	0.78947     	0.11463     	4           
---> try to load best state
              	0.02679     	0.78947     	0.11463     	4                eval state : test_on_restore;
              	0.02679     	0.78947     	0.11463     	4                eval state : test_on_last_epoch;
---> final result
              	0.02679     	0.78947     	0.11463     	4                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 1 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 256, '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: 128
  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           	0.23870     	-533002624.88881	0.50580     	0           
  10          	0.23948     	-173803.37834	0.50511     	0           
  100         	0.07747     	0.57640     	0.18944     	0           
  300         	0.03290     	0.79118     	0.11001     	1           
  500         	0.03270     	0.86621     	0.11557     	2           
  1000        	0.03645     	0.90103     	0.16824     	5           
---> try to load best state
              	0.03645     	0.90103     	0.16824     	5                eval state : test_on_restore;
              	0.03645     	0.90103     	0.16824     	5                eval state : test_on_last_epoch;
---> final result
              	0.03645     	0.90103     	0.16824     	5                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 1 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 256, '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: 256
  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           	0.23483     	-47974499.78251	0.50581     	0           
  10          	0.23583     	-202856.00892	0.50507     	0           
  100         	0.07405     	0.52533     	0.22747     	0           
  300         	0.03992     	0.55708     	0.16168     	1           
  500         	0.04284     	0.80435     	0.11027     	2           
  1000        	0.03380     	0.83520     	0.10243     	5           
---> try to load best state
              	0.03380     	0.83520     	0.10243     	5                eval state : test_on_restore;
              	0.03380     	0.83520     	0.10243     	5                eval state : test_on_last_epoch;
---> final result
              	0.03380     	0.83520     	0.10243     	5                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 2 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 256, '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           	0.29428     	-253363628.49440	0.51278     	0           
  10          	0.29406     	-1674803.95498	0.51262     	0           
  100         	0.17082     	-2.86974    	0.42106     	0           
  300         	0.17247     	-3.01012    	0.43021     	2           
  500         	0.16846     	-3.49591    	0.43183     	3           
  1000        	0.17834     	-2.24521    	0.42623     	6           
---> try to load best state
              	0.17834     	-2.24521    	0.42623     	6                eval state : test_on_restore;
              	0.17834     	-2.24521    	0.42623     	6                eval state : test_on_last_epoch;
---> final result
              	0.17834     	-2.24521    	0.42623     	6                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 2 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 256, '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           	0.22074     	-31890159380.65437	0.50725     	0           
  10          	0.22040     	-5707371.71476	0.50712     	0           
  100         	0.09554     	-3.88089    	0.37541     	0           
  300         	0.10802     	-8.57038    	0.42443     	1           
  500         	0.09838     	-6.08784    	0.40657     	2           
  1000        	0.09609     	-6.47146    	0.40851     	4           
---> try to load best state
              	0.09609     	-6.47146    	0.40851     	4                eval state : test_on_restore;
              	0.09609     	-6.47146    	0.40851     	4                eval state : test_on_last_epoch;
---> final result
              	0.09609     	-6.47146    	0.40851     	4                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 2 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 256, '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           	0.22835     	-1040579713.68852	0.50624     	0           
  10          	0.22788     	-2120435.07220	0.50600     	0           
  100         	0.05801     	0.31436     	0.21908     	0           
  300         	0.04872     	0.28853     	0.21705     	1           
  500         	0.03927     	0.65434     	0.16415     	2           
  1000        	0.03510     	0.80452     	0.12490     	4           
---> try to load best state
              	0.03510     	0.80452     	0.12490     	4                eval state : test_on_restore;
              	0.03510     	0.80452     	0.12490     	4                eval state : test_on_last_epoch;
---> final result
              	0.03510     	0.80452     	0.12490     	4                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 2 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 256, '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           	0.30338     	-119828626.41669	0.51753     	0           
  10          	0.30327     	-286338.80949	0.51667     	0           
  100         	0.04811     	0.56950     	0.15729     	0           
  300         	0.03566     	0.79581     	0.11327     	1           
  500         	0.03643     	0.54114     	0.14742     	2           
  1000        	0.03001     	0.76126     	0.10783     	4           
---> try to load best state
              	0.03001     	0.76126     	0.10783     	4                eval state : test_on_restore;
              	0.03001     	0.76126     	0.10783     	4                eval state : test_on_last_epoch;
---> final result
              	0.03001     	0.76126     	0.10783     	4                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 2 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 256, '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: 64
  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           	0.28049     	-1301380002.09736	0.51016     	0           
  10          	0.27885     	-526922.24537	0.50948     	0           
  100         	0.07911     	0.82729     	0.17272     	0           
  300         	0.04073     	0.94035     	0.10670     	1           
  500         	0.02721     	0.89577     	0.08707     	2           
  1000        	0.02753     	0.91284     	0.09667     	4           
---> try to load best state
              	0.02753     	0.91284     	0.09667     	4                eval state : test_on_restore;
              	0.02753     	0.91284     	0.09667     	4                eval state : test_on_last_epoch;
---> final result
              	0.02753     	0.91284     	0.09667     	4                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 2 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 256, '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: 128
  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           	0.28668     	-24018662.31075	0.51123     	0           
  10          	0.28303     	-221141.16910	0.50986     	0           
  100         	0.07046     	0.85307     	0.15834     	0           
  300         	0.02862     	0.94365     	0.07532     	1           
  500         	0.02403     	0.95975     	0.07089     	1           
  1000        	0.02671     	0.91110     	0.10188     	3           
---> try to load best state
              	0.02671     	0.91110     	0.10188     	3                eval state : test_on_restore;
              	0.02671     	0.91110     	0.10188     	3                eval state : test_on_last_epoch;
---> final result
              	0.02671     	0.91110     	0.10188     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 2 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 256, '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: 256
  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           	0.25740     	-721213666.52996	0.50655     	0           
  10          	0.25757     	-754149.61136	0.50626     	0           
  100         	0.06410     	0.69803     	0.18086     	0           
  300         	0.03150     	0.92149     	0.10025     	0           
  500         	0.03296     	0.93954     	0.10258     	1           
  1000        	0.03248     	0.94277     	0.08008     	2           
---> try to load best state
              	0.03248     	0.94277     	0.08008     	2                eval state : test_on_restore;
              	0.03248     	0.94277     	0.08008     	2                eval state : test_on_last_epoch;
---> final result
              	0.03248     	0.94277     	0.08008     	2                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 3 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 256, '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           	0.25284     	-3206171164.39086	0.50623     	0           
  10          	0.25363     	-797444.37198	0.50598     	0           
  100         	0.07538     	0.03546     	0.26089     	0           
  300         	0.09208     	-0.42155    	0.30791     	0           
  500         	0.10618     	-1.44762    	0.34221     	1           
  1000        	0.10576     	-1.16238    	0.35407     	3           
---> try to load best state
              	0.10576     	-1.16238    	0.35407     	3                eval state : test_on_restore;
              	0.10576     	-1.16238    	0.35407     	3                eval state : test_on_last_epoch;
---> final result
              	0.10576     	-1.16238    	0.35407     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 3 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 256, '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           	0.20627     	-536093526.57950	0.50997     	0           
  10          	0.20658     	-1174287.90713	0.50955     	0           
  100         	0.06690     	-0.23414    	0.27709     	0           
  300         	0.06830     	0.54239     	0.19825     	0           
  500         	0.05386     	0.30216     	0.22406     	1           
  1000        	0.06206     	-0.48726    	0.27444     	2           
---> try to load best state
              	0.06206     	-0.48726    	0.27444     	2                eval state : test_on_restore;
              	0.06206     	-0.48726    	0.27444     	2                eval state : test_on_last_epoch;
---> final result
              	0.06206     	-0.48726    	0.27444     	2                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 3 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 256, '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           	0.19224     	-1085883981.40109	0.51476     	0           
  10          	0.19154     	-1941688.60597	0.51474     	0           
  100         	0.08185     	-0.91076    	0.32339     	0           
  300         	0.05684     	-0.49559    	0.28399     	0           
  500         	0.05097     	0.00764     	0.25421     	1           
  1000        	0.05642     	-0.15767    	0.26213     	3           
---> try to load best state
              	0.05642     	-0.15767    	0.26213     	3                eval state : test_on_restore;
              	0.05642     	-0.15767    	0.26213     	3                eval state : test_on_last_epoch;
---> final result
              	0.05642     	-0.15767    	0.26213     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 3 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 256, '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           	0.40259     	-17375860.82007	0.56060     	0           
  10          	0.40222     	-70828.01697	0.55744     	0           
  100         	0.12377     	0.78708     	0.28500     	0           
  300         	0.04101     	0.93519     	0.10843     	1           
  500         	0.03534     	0.92227     	0.09760     	1           
  1000        	0.03749     	0.92122     	0.11411     	3           
---> try to load best state
              	0.03749     	0.92122     	0.11411     	3                eval state : test_on_restore;
              	0.03749     	0.92122     	0.11411     	3                eval state : test_on_last_epoch;
---> final result
              	0.03749     	0.92122     	0.11411     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 3 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 256, '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: 64
  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           	0.30921     	-45694204.37799	0.51780     	0           
  10          	0.30813     	-98574.14329	0.51705     	0           
  100         	0.13990     	0.75557     	0.34392     	0           
  300         	0.03450     	0.93620     	0.09341     	0           
  500         	0.04273     	0.92862     	0.11636     	1           
  1000        	0.03050     	0.94533     	0.09643     	3           
---> try to load best state
              	0.03050     	0.94533     	0.09643     	3                eval state : test_on_restore;
              	0.03050     	0.94533     	0.09643     	3                eval state : test_on_last_epoch;
---> final result
              	0.03050     	0.94533     	0.09643     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 3 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 256, '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: 128
  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           	0.26354     	-70318354.67352	0.50715     	0           
  10          	0.26239     	-86858.60735	0.50620     	0           
  100         	0.13664     	0.73190     	0.34131     	0           
  300         	0.02748     	0.88063     	0.09736     	0           
  500         	0.03795     	0.90073     	0.09653     	1           
  1000        	0.02391     	0.96312     	0.07071     	3           
---> try to load best state
              	0.02391     	0.96312     	0.07071     	3                eval state : test_on_restore;
              	0.02391     	0.96312     	0.07071     	3                eval state : test_on_last_epoch;
---> final result
              	0.02391     	0.96312     	0.07071     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 3 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 256, '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: 256
  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           	0.26124     	-50327591.12621	0.50682     	0           
  10          	0.25839     	-84987.31327	0.50541     	0           
  100         	0.08456     	0.83115     	0.18515     	0           
  300         	0.07703     	0.85621     	0.24756     	0           
  500         	0.04932     	0.93878     	0.09561     	1           
  1000        	0.02577     	0.95101     	0.07944     	3           
---> try to load best state
              	0.02577     	0.95101     	0.07944     	3                eval state : test_on_restore;
              	0.02577     	0.95101     	0.07944     	3                eval state : test_on_last_epoch;
---> final result
              	0.02577     	0.95101     	0.07944     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 4 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 256, '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           	0.17212     	-116382568634.74216	0.53728     	0           
  10          	0.17209     	-170024694.59673	0.53727     	0           
  100         	0.13692     	-85.98642   	0.49884     	0           
  300         	0.11818     	-17.47970   	0.45971     	0           
  500         	0.12336     	-30.50474   	0.47555     	1           
  1000        	0.12533     	-34.63551   	0.47934     	3           
---> try to load best state
              	0.12533     	-34.63551   	0.47934     	3                eval state : test_on_restore;
              	0.12533     	-34.63551   	0.47934     	3                eval state : test_on_last_epoch;
---> final result
              	0.12533     	-34.63551   	0.47934     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 4 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 256, '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           	0.26781     	-130093140.56848	0.50801     	0           
  10          	0.26624     	-433939.34754	0.50746     	0           
  100         	0.09138     	0.20841     	0.26975     	0           
  300         	0.06861     	0.34294     	0.21264     	0           
  500         	0.05039     	0.66980     	0.15297     	1           
  1000        	0.04946     	0.38560     	0.19466     	3           
---> try to load best state
              	0.04946     	0.38560     	0.19466     	3                eval state : test_on_restore;
              	0.04946     	0.38560     	0.19466     	3                eval state : test_on_last_epoch;
---> final result
              	0.04946     	0.38560     	0.19466     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 4 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 256, '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           	0.27144     	-726975638.27678	0.50856     	0           
  10          	0.27007     	-650004.61675	0.50798     	0           
  100         	0.08684     	-0.72131    	0.29457     	0           
  300         	0.05498     	0.21225     	0.21781     	0           
  500         	0.04061     	0.74727     	0.14208     	1           
  1000        	0.05425     	0.39909     	0.20017     	3           
---> try to load best state
              	0.05425     	0.39909     	0.20017     	3                eval state : test_on_restore;
              	0.05425     	0.39909     	0.20017     	3                eval state : test_on_last_epoch;
---> final result
              	0.05425     	0.39909     	0.20017     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 4 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 256, '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           	0.34792     	-65842781.71123	0.53414     	0           
  10          	0.35113     	-114772.30808	0.53496     	0           
  100         	0.09567     	0.82527     	0.23527     	0           
  300         	0.03295     	0.89347     	0.09243     	1           
  500         	0.04991     	0.87398     	0.10808     	2           
  1000        	0.02412     	0.95005     	0.07444     	5           
---> try to load best state
              	0.02412     	0.95005     	0.07444     	5                eval state : test_on_restore;
              	0.02412     	0.95005     	0.07444     	5                eval state : test_on_last_epoch;
---> final result
              	0.02412     	0.95005     	0.07444     	5                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 4 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 256, '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: 64
  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           	0.26935     	-32865870.28487	0.50804     	0           
  10          	0.27147     	-95200.39782	0.50763     	0           
  100         	0.06920     	0.64908     	0.20258     	0           
  300         	0.02429     	0.91844     	0.08194     	1           
  500         	0.03634     	0.90350     	0.09985     	2           
  1000        	0.03025     	0.95361     	0.11202     	4           
---> try to load best state
              	0.03025     	0.95361     	0.11202     	4                eval state : test_on_restore;
              	0.03025     	0.95361     	0.11202     	4                eval state : test_on_last_epoch;
---> final result
              	0.03025     	0.95361     	0.11202     	4                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 4 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 256, '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: 128
  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           	0.30038     	-47413174.37479	0.51494     	0           
  10          	0.30333     	-115684.23421	0.51539     	0           
  100         	0.12840     	0.78604     	0.26277     	0           
  300         	0.04183     	0.93868     	0.08106     	1           
  500         	0.03353     	0.95397     	0.08012     	2           
  1000        	0.04190     	0.95285     	0.08778     	3           
---> try to load best state
              	0.04190     	0.95285     	0.08778     	3                eval state : test_on_restore;
              	0.04190     	0.95285     	0.08778     	3                eval state : test_on_last_epoch;
---> final result
              	0.04190     	0.95285     	0.08778     	3                eval state : final;module_name : dmfal;cp_record_file : True;
---> end

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

  Demo DMFAL 
  seed: 4 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 256, '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: 256
  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           	0.28164     	-11848609.52750	0.51040     	0           
  10          	0.27805     	-110493.99878	0.50880     	0           
  100         	0.06718     	0.74232     	0.16919     	0           
  300         	0.03474     	0.92724     	0.08246     	1           
  500         	0.03262     	0.93721     	0.09577     	1           
  1000        	0.03085     	0.94596     	0.08248     	3           
---> try to load best state
              	0.03085     	0.94596     	0.08248     	3                eval state : test_on_restore;
              	0.03085     	0.94596     	0.08248     	3                eval state : test_on_last_epoch;
---> final result
              	0.03085     	0.94596     	0.08248     	3                eval state : final;module_name : dmfal;cp_record_file : True;
