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

  Demo DMFAL 
  seed: 0 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 64, '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     	-13820356077.39705	0.53601     	0           
  10          	0.17162     	-118067514.37963	0.53604     	0           
  100         	0.13237     	-63.13259   	0.48995     	0           
  300         	0.12620     	-39.59626   	0.47717     	0           
  500         	0.11572     	-22.08632   	0.46008     	1           
  1000        	0.11773     	-23.64682   	0.46215     	3           
---> try to load best state
              	0.11773     	-23.64682   	0.46215     	3                eval state : test_on_restore;
              	0.11773     	-23.64682   	0.46215     	3                eval state : test_on_last_epoch;
---> final result
              	0.11773     	-23.64682   	0.46215     	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': 64, '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           	0.17174     	-76704928271.54367	0.53631     	0           
  10          	0.17172     	-407618749.95023	0.53629     	0           
  100         	0.13302     	-71.25936   	0.49266     	0           
  300         	0.11411     	-20.07601   	0.45976     	1           
  500         	0.10818     	-12.98021   	0.44549     	2           
  1000        	0.11115     	-16.67137   	0.45450     	3           
---> try to load best state
              	0.11115     	-16.67137   	0.45450     	3                eval state : test_on_restore;
              	0.11115     	-16.67137   	0.45450     	3                eval state : test_on_last_epoch;
---> final result
              	0.11115     	-16.67137   	0.45450     	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': 64, '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           	0.17258     	-10949221827.41060	0.53030     	0           
  10          	0.17240     	-33741284.16869	0.53033     	0           
  100         	0.10545     	-9.90107    	0.42374     	0           
  300         	0.09487     	-7.44315    	0.40726     	1           
  500         	0.09176     	-6.59754    	0.40105     	1           
  1000        	0.08781     	-5.51235    	0.39055     	3           
---> try to load best state
              	0.08781     	-5.51235    	0.39055     	3                eval state : test_on_restore;
              	0.08781     	-5.51235    	0.39055     	3                eval state : test_on_last_epoch;
---> final result
              	0.08781     	-5.51235    	0.39055     	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': 64, '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           	0.17859     	-11997430512.31101	0.52317     	0           
  10          	0.17853     	-3554166.87940	0.52287     	0           
  100         	0.08088     	-2.40831    	0.35481     	0           
  300         	0.07206     	-1.92886    	0.33741     	1           
  500         	0.05993     	-0.81541    	0.30506     	2           
  1000        	0.06382     	-1.27402    	0.31491     	4           
---> try to load best state
              	0.06382     	-1.27402    	0.31491     	4                eval state : test_on_restore;
              	0.06382     	-1.27402    	0.31491     	4                eval state : test_on_last_epoch;
---> final result
              	0.06382     	-1.27402    	0.31491     	4                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': 64, '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           	0.28366     	-85084243.35333	0.51211     	0           
  10          	0.27893     	-114660.26193	0.51008     	0           
  100         	0.09424     	0.72467     	0.22685     	0           
  300         	0.04459     	0.80091     	0.13869     	1           
  500         	0.03507     	0.68030     	0.11875     	1           
  1000        	0.03570     	0.73066     	0.14238     	3           
---> try to load best state
              	0.03570     	0.73066     	0.14238     	3                eval state : test_on_restore;
              	0.03570     	0.73066     	0.14238     	3                eval state : test_on_last_epoch;
---> final result
              	0.03570     	0.73066     	0.14238     	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': 64, '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     	-148688885009.63104	0.53216     	0           
  10          	0.17177     	-68710298.51136	0.53214     	0           
  100         	0.11781     	-24.49783   	0.46197     	0           
  300         	0.09781     	-8.15786    	0.42139     	1           
  500         	0.09194     	-5.79357    	0.40726     	1           
  1000        	0.09580     	-7.31894    	0.41551     	3           
---> try to load best state
              	0.09580     	-7.31894    	0.41551     	3                eval state : test_on_restore;
              	0.09580     	-7.31894    	0.41551     	3                eval state : test_on_last_epoch;
---> final result
              	0.09580     	-7.31894    	0.41551     	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': 64, '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           	0.18561     	-560737858.56666	0.51865     	0           
  10          	0.18572     	-3814049.61572	0.51833     	0           
  100         	0.10127     	-6.85467    	0.40506     	0           
  300         	0.07230     	-1.63568    	0.33712     	0           
  500         	0.07503     	-1.78291    	0.34342     	1           
  1000        	0.08091     	-3.50991    	0.37428     	3           
---> try to load best state
              	0.08091     	-3.50991    	0.37428     	3                eval state : test_on_restore;
              	0.08091     	-3.50991    	0.37428     	3                eval state : test_on_last_epoch;
---> final result
              	0.08091     	-3.50991    	0.37428     	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': 64, '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           	0.20096     	-2453167676.93603	0.51170     	0           
  10          	0.20068     	-2175198.76921	0.51157     	0           
  100         	0.07318     	-1.46423    	0.32667     	0           
  300         	0.06123     	-0.73733    	0.29578     	0           
  500         	0.05284     	-0.16648    	0.26638     	1           
  1000        	0.04767     	0.08966     	0.24685     	3           
---> try to load best state
              	0.04767     	0.08966     	0.24685     	3                eval state : test_on_restore;
              	0.04767     	0.08966     	0.24685     	3                eval state : test_on_last_epoch;
---> final result
              	0.04767     	0.08966     	0.24685     	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': 64, '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           	0.21567     	-1563889019.30167	0.50785     	0           
  10          	0.21444     	-1593043.25754	0.50771     	0           
  100         	0.06746     	-0.13800    	0.27788     	0           
  300         	0.05168     	-0.07490    	0.25491     	0           
  500         	0.05943     	-0.60703    	0.27900     	1           
  1000        	0.04837     	-0.05613    	0.24502     	2           
---> try to load best state
              	0.04837     	-0.05613    	0.24502     	2                eval state : test_on_restore;
              	0.04837     	-0.05613    	0.24502     	2                eval state : test_on_last_epoch;
---> final result
              	0.04837     	-0.05613    	0.24502     	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': 64, '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           	0.23004     	-749828531.70128	0.50608     	0           
  10          	0.23056     	-385666.31818	0.50558     	0           
  100         	0.06377     	-0.07424    	0.25783     	0           
  300         	0.04617     	0.12035     	0.22289     	0           
  500         	0.04194     	0.75052     	0.13719     	1           
  1000        	0.02784     	0.76318     	0.12213     	2           
---> try to load best state
              	0.02784     	0.76318     	0.12213     	2                eval state : test_on_restore;
              	0.02784     	0.76318     	0.12213     	2                eval state : test_on_last_epoch;
---> final result
              	0.02784     	0.76318     	0.12213     	2                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': 64, '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           	0.29393     	-261644124.39471	0.51269     	0           
  10          	0.29350     	-654567.88457	0.51239     	0           
  100         	0.17975     	-3.31288    	0.43581     	0           
  300         	0.20760     	-1.67211    	0.43758     	0           
  500         	0.19634     	-2.03333    	0.43353     	1           
  1000        	0.19349     	-2.05672    	0.43179     	2           
---> try to load best state
              	0.19349     	-2.05672    	0.43179     	2                eval state : test_on_restore;
              	0.19349     	-2.05672    	0.43179     	2                eval state : test_on_last_epoch;
---> final result
              	0.19349     	-2.05672    	0.43179     	2                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': 64, '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           	0.22112     	-536324842.26651	0.50717     	0           
  10          	0.22115     	-1219721.96264	0.50690     	0           
  100         	0.11012     	-4.02334    	0.37919     	0           
  300         	0.10159     	-6.72442    	0.41304     	0           
  500         	0.10020     	-6.07665    	0.41192     	1           
  1000        	0.10345     	-5.94727    	0.40725     	3           
---> try to load best state
              	0.10345     	-5.94727    	0.40725     	3                eval state : test_on_restore;
              	0.10345     	-5.94727    	0.40725     	3                eval state : test_on_last_epoch;
---> final result
              	0.10345     	-5.94727    	0.40725     	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': 64, '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           	0.22766     	-1056715553.27977	0.50632     	0           
  10          	0.22895     	-2180280.97265	0.50598     	0           
  100         	0.05907     	0.14933     	0.23577     	0           
  300         	0.04811     	0.52326     	0.18339     	1           
  500         	0.04563     	0.51739     	0.19308     	2           
  1000        	0.04482     	0.31566     	0.21414     	4           
---> try to load best state
              	0.04482     	0.31566     	0.21414     	4                eval state : test_on_restore;
              	0.04482     	0.31566     	0.21414     	4                eval state : test_on_last_epoch;
---> final result
              	0.04482     	0.31566     	0.21414     	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': 64, '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           	0.30303     	-623600653.82554	0.51757     	0           
  10          	0.30341     	-239047.77837	0.51712     	0           
  100         	0.07045     	0.69590     	0.17202     	0           
  300         	0.04051     	0.49977     	0.15894     	1           
  500         	0.03379     	0.75318     	0.11032     	1           
  1000        	0.03424     	0.77835     	0.10101     	4           
---> try to load best state
              	0.03424     	0.77835     	0.10101     	4                eval state : test_on_restore;
              	0.03424     	0.77835     	0.10101     	4                eval state : test_on_last_epoch;
---> final result
              	0.03424     	0.77835     	0.10101     	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': 64, '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           	0.28057     	-199941694.32659	0.51023     	0           
  10          	0.27899     	-241661.84348	0.50907     	0           
  100         	0.06779     	0.70291     	0.16605     	0           
  300         	0.04236     	0.75516     	0.13692     	1           
  500         	0.02678     	0.85522     	0.10657     	1           
  1000        	0.03451     	0.82918     	0.12365     	3           
---> try to load best state
              	0.03451     	0.82918     	0.12365     	3                eval state : test_on_restore;
              	0.03451     	0.82918     	0.12365     	3                eval state : test_on_last_epoch;
---> final result
              	0.03451     	0.82918     	0.12365     	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': 64, '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           	0.25364     	-188735437.12209	0.50632     	0           
  10          	0.25230     	-838359.31576	0.50586     	0           
  100         	0.07394     	-1.03556    	0.29869     	0           
  300         	0.08012     	-1.18580    	0.32792     	1           
  500         	0.09610     	-0.99015    	0.33648     	2           
  1000        	0.08482     	-1.41849    	0.34306     	4           
---> try to load best state
              	0.08482     	-1.41849    	0.34306     	4                eval state : test_on_restore;
              	0.08482     	-1.41849    	0.34306     	4                eval state : test_on_last_epoch;
---> final result
              	0.08482     	-1.41849    	0.34306     	4                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': 64, '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           	0.20645     	-366512103.04288	0.50996     	0           
  10          	0.20670     	-2664955.73152	0.50968     	0           
  100         	0.07347     	-1.67889    	0.31986     	0           
  300         	0.06319     	-0.08004    	0.25624     	1           
  500         	0.05853     	-0.11235    	0.25620     	1           
  1000        	0.06642     	-0.31367    	0.28693     	3           
---> try to load best state
              	0.06642     	-0.31367    	0.28693     	3                eval state : test_on_restore;
              	0.06642     	-0.31367    	0.28693     	3                eval state : test_on_last_epoch;
---> final result
              	0.06642     	-0.31367    	0.28693     	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': 64, '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           	0.19174     	-813684672.75149	0.51498     	0           
  10          	0.19048     	-522996.01474	0.51501     	0           
  100         	0.07798     	-0.91017    	0.31996     	0           
  300         	0.05576     	-0.13822    	0.26553     	1           
  500         	0.05400     	-0.30642    	0.27364     	1           
  1000        	0.05350     	0.11464     	0.24957     	3           
---> try to load best state
              	0.05350     	0.11464     	0.24957     	3                eval state : test_on_restore;
              	0.05350     	0.11464     	0.24957     	3                eval state : test_on_last_epoch;
---> final result
              	0.05350     	0.11464     	0.24957     	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': 64, '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           	0.40206     	-51555154.15050	0.56021     	0           
  10          	0.40529     	-79462.43649	0.56184     	0           
  100         	0.10162     	0.82448     	0.25492     	0           
  300         	0.05756     	0.95263     	0.10636     	1           
  500         	0.04458     	0.95025     	0.10291     	1           
  1000        	0.04897     	0.92539     	0.12446     	3           
---> try to load best state
              	0.04897     	0.92539     	0.12446     	3                eval state : test_on_restore;
              	0.04897     	0.92539     	0.12446     	3                eval state : test_on_last_epoch;
---> final result
              	0.04897     	0.92539     	0.12446     	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': 64, '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           	0.30862     	-9620190.83831	0.51748     	0           
  10          	0.31120     	-28071.49711	0.51693     	0           
  100         	0.21628     	0.61370     	0.53690     	0           
  300         	0.07227     	0.87333     	0.19989     	1           
  500         	0.03736     	0.93689     	0.10903     	1           
  1000        	0.04661     	0.92111     	0.13173     	3           
---> try to load best state
              	0.04661     	0.92111     	0.13173     	3                eval state : test_on_restore;
              	0.04661     	0.92111     	0.13173     	3                eval state : test_on_last_epoch;
---> final result
              	0.04661     	0.92111     	0.13173     	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': 64, '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     	-262642857883.82010	0.53728     	0           
  10          	0.17209     	-386736151.71793	0.53724     	0           
  100         	0.14641     	-222.17288  	0.51282     	0           
  300         	0.11957     	-16.67499   	0.45905     	1           
  500         	0.11886     	-16.64143   	0.45903     	2           
  1000        	0.13216     	-65.30815   	0.49359     	4           
---> try to load best state
              	0.13216     	-65.30815   	0.49359     	4                eval state : test_on_restore;
              	0.13216     	-65.30815   	0.49359     	4                eval state : test_on_last_epoch;
---> final result
              	0.13216     	-65.30815   	0.49359     	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': 64, '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           	0.26734     	-69005466.44591	0.50794     	0           
  10          	0.26903     	-112488.49427	0.50742     	0           
  100         	0.06532     	-0.73810    	0.28979     	0           
  300         	0.05819     	0.24031     	0.21531     	1           
  500         	0.06179     	0.20148     	0.21891     	2           
  1000        	0.04721     	0.47094     	0.18178     	3           
---> try to load best state
              	0.04721     	0.47094     	0.18178     	3                eval state : test_on_restore;
              	0.04721     	0.47094     	0.18178     	3                eval state : test_on_last_epoch;
---> final result
              	0.04721     	0.47094     	0.18178     	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': 64, '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           	0.27169     	-19087640.08349	0.50856     	0           
  10          	0.27218     	-118711.09529	0.50793     	0           
  100         	0.07540     	0.20366     	0.26690     	0           
  300         	0.05009     	0.34239     	0.21054     	1           
  500         	0.05382     	0.47507     	0.19523     	1           
  1000        	0.04687     	0.74863     	0.14790     	3           
---> try to load best state
              	0.04687     	0.74863     	0.14790     	3                eval state : test_on_restore;
              	0.04687     	0.74863     	0.14790     	3                eval state : test_on_last_epoch;
---> final result
              	0.04687     	0.74863     	0.14790     	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': 64, '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           	0.34860     	-38724133.15863	0.53483     	0           
  10          	0.34539     	-87347.30032	0.53282     	0           
  100         	0.06315     	0.74345     	0.15069     	0           
  300         	0.03351     	0.93294     	0.09425     	1           
  500         	0.03340     	0.94190     	0.07994     	1           
  1000        	0.03477     	0.95155     	0.08154     	3           
---> try to load best state
              	0.03477     	0.95155     	0.08154     	3                eval state : test_on_restore;
              	0.03477     	0.95155     	0.08154     	3                eval state : test_on_last_epoch;
---> final result
              	0.03477     	0.95155     	0.08154     	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': 64, '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           	0.26880     	-1453707388.49965	0.50800     	0           
  10          	0.26390     	-83681.30495	0.50605     	0           
  100         	0.08177     	0.69712     	0.21768     	0           
  300         	0.03045     	0.88058     	0.09748     	1           
  500         	0.02761     	0.90569     	0.09549     	1           
  1000        	0.03249     	0.92297     	0.08103     	3           
---> try to load best state
              	0.03249     	0.92297     	0.08103     	3                eval state : test_on_restore;
              	0.03249     	0.92297     	0.08103     	3                eval state : test_on_last_epoch;
---> final result
              	0.03249     	0.92297     	0.08103     	3                eval state : final;module_name : dmfal;cp_record_file : True;
