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

  Demo DMFAL 
  seed: 0 
  interp_data: False 

----------------------------------------
---> module config
  dataset: {'name': 'plasmonic2_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 128, '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     	-24261803009.69154	0.53602     	0           
  10          	0.17164     	-953688700.57570	0.53605     	0           
  100         	0.13659     	-95.39542   	0.49834     	0           
  300         	0.11099     	-16.96138   	0.45222     	0           
  500         	0.10851     	-14.76542   	0.44753     	1           
  1000        	0.10142     	-9.52512    	0.43201     	2           
---> try to load best state
              	0.10142     	-9.52512    	0.43201     	2                eval state : test_on_restore;
              	0.10142     	-9.52512    	0.43201     	2                eval state : test_on_last_epoch;
---> final result
              	0.10142     	-9.52512    	0.43201     	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': 128, '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     	-322942120916.27216	0.53631     	0           
  10          	0.17170     	-65428082.94094	0.53629     	0           
  100         	0.14014     	-107.91685  	0.50188     	0           
  300         	0.10538     	-8.08027    	0.43030     	0           
  500         	0.10357     	-7.42877    	0.42675     	1           
  1000        	0.10595     	-9.96077    	0.43739     	3           
---> try to load best state
              	0.10595     	-9.96077    	0.43739     	3                eval state : test_on_restore;
              	0.10595     	-9.96077    	0.43739     	3                eval state : test_on_last_epoch;
---> final result
              	0.10595     	-9.96077    	0.43739     	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': 128, '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           	0.17263     	-2627635665.92400	0.53017     	0           
  10          	0.17245     	-8194019.20796	0.53014     	0           
  100         	0.10722     	-11.93476   	0.43152     	0           
  300         	0.09771     	-9.07891    	0.41660     	1           
  500         	0.09701     	-9.29507    	0.41583     	2           
  1000        	0.09153     	-6.89063    	0.40160     	4           
---> try to load best state
              	0.09153     	-6.89063    	0.40160     	4                eval state : test_on_restore;
              	0.09153     	-6.89063    	0.40160     	4                eval state : test_on_last_epoch;
---> final result
              	0.09153     	-6.89063    	0.40160     	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': 128, '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           	0.17853     	-1553200084.58690	0.52323     	0           
  10          	0.17820     	-3831834.18692	0.52324     	0           
  100         	0.08985     	-4.77467    	0.38456     	0           
  300         	0.06095     	-0.83525    	0.30428     	0           
  500         	0.06221     	-0.96110    	0.30556     	1           
  1000        	0.06167     	-1.03571    	0.30950     	3           
---> try to load best state
              	0.06167     	-1.03571    	0.30950     	3                eval state : test_on_restore;
              	0.06167     	-1.03571    	0.30950     	3                eval state : test_on_last_epoch;
---> final result
              	0.06167     	-1.03571    	0.30950     	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': 128, '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           	0.28379     	-4021647.72617	0.51202     	0           
  10          	0.28024     	-32710.06914	0.50987     	0           
  100         	0.06850     	0.35441     	0.19427     	0           
  300         	0.04251     	0.71657     	0.13962     	0           
  500         	0.05089     	0.81274     	0.16787     	1           
  1000        	0.03319     	0.72121     	0.11386     	3           
---> try to load best state
              	0.03319     	0.72121     	0.11386     	3                eval state : test_on_restore;
              	0.03319     	0.72121     	0.11386     	3                eval state : test_on_last_epoch;
---> final result
              	0.03319     	0.72121     	0.11386     	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': 128, '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           	0.26058     	-1445000070.91208	0.50746     	0           
  10          	0.26101     	-340571.73243	0.50689     	0           
  100         	0.06356     	0.51126     	0.18454     	0           
  300         	0.04867     	0.36024     	0.16037     	1           
  500         	0.02719     	0.70362     	0.10997     	2           
  1000        	0.02868     	0.76379     	0.11785     	4           
---> try to load best state
              	0.02868     	0.76379     	0.11785     	4                eval state : test_on_restore;
              	0.02868     	0.76379     	0.11785     	4                eval state : test_on_last_epoch;
---> final result
              	0.02868     	0.76379     	0.11785     	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': 128, '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           	0.17184     	-3504864881.63479	0.53209     	0           
  10          	0.17172     	-16680752.67906	0.53203     	0           
  100         	0.11438     	-20.23148   	0.45570     	0           
  300         	0.09765     	-7.86430    	0.41754     	1           
  500         	0.09865     	-7.84519    	0.41644     	1           
  1000        	0.10365     	-8.93978    	0.42163     	3           
---> try to load best state
              	0.10365     	-8.93978    	0.42163     	3                eval state : test_on_restore;
              	0.10365     	-8.93978    	0.42163     	3                eval state : test_on_last_epoch;
---> final result
              	0.10365     	-8.93978    	0.42163     	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': 128, '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           	0.18578     	-6476350218.44178	0.51856     	0           
  10          	0.18523     	-4052890.04355	0.51866     	0           
  100         	0.09314     	-4.91524    	0.38680     	0           
  300         	0.07196     	-1.11049    	0.32066     	1           
  500         	0.07828     	-2.34797    	0.35289     	1           
  1000        	0.09615     	-7.15911    	0.40615     	3           
---> try to load best state
              	0.09615     	-7.15911    	0.40615     	3                eval state : test_on_restore;
              	0.09615     	-7.15911    	0.40615     	3                eval state : test_on_last_epoch;
---> final result
              	0.09615     	-7.15911    	0.40615     	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': 128, '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           	0.20135     	-488278687.50258	0.51153     	0           
  10          	0.20137     	-2987235.89100	0.51121     	0           
  100         	0.06175     	-0.39035    	0.28555     	0           
  300         	0.04849     	0.16239     	0.24023     	1           
  500         	0.04452     	0.28903     	0.22546     	1           
  1000        	0.03989     	0.39948     	0.20487     	3           
---> try to load best state
              	0.03989     	0.39948     	0.20487     	3                eval state : test_on_restore;
              	0.03989     	0.39948     	0.20487     	3                eval state : test_on_last_epoch;
---> final result
              	0.03989     	0.39948     	0.20487     	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': 128, '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           	0.21571     	-1176761732.94870	0.50786     	0           
  10          	0.21541     	-1320830.32812	0.50765     	0           
  100         	0.06425     	-0.00427    	0.25958     	0           
  300         	0.05125     	0.14663     	0.22807     	1           
  500         	0.06032     	-0.41995    	0.26601     	1           
  1000        	0.03592     	0.61403     	0.16711     	3           
---> try to load best state
              	0.03592     	0.61403     	0.16711     	3                eval state : test_on_restore;
              	0.03592     	0.61403     	0.16711     	3                eval state : test_on_last_epoch;
---> final result
              	0.03592     	0.61403     	0.16711     	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': 128, '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           	0.22961     	-1226621934.38138	0.50613     	0           
  10          	0.22827     	-504674.19512	0.50568     	0           
  100         	0.06925     	-0.56167    	0.27638     	0           
  300         	0.03229     	0.59744     	0.15477     	1           
  500         	0.03451     	0.76036     	0.12085     	1           
  1000        	0.02868     	0.71347     	0.12432     	3           
---> try to load best state
              	0.02868     	0.71347     	0.12432     	3                eval state : test_on_restore;
              	0.02868     	0.71347     	0.12432     	3                eval state : test_on_last_epoch;
---> final result
              	0.02868     	0.71347     	0.12432     	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': 128, '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           	0.23824     	-80689934.00424	0.50578     	0           
  10          	0.23751     	-620412.42140	0.50506     	0           
  100         	0.05660     	0.53251     	0.18842     	0           
  300         	0.03578     	0.75252     	0.12412     	1           
  500         	0.03025     	0.83060     	0.11683     	1           
  1000        	0.03851     	0.89111     	0.16556     	3           
---> try to load best state
              	0.03851     	0.89111     	0.16556     	3                eval state : test_on_restore;
              	0.03851     	0.89111     	0.16556     	3                eval state : test_on_last_epoch;
---> final result
              	0.03851     	0.89111     	0.16556     	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': 128, '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           	0.29442     	-100481839.61978	0.51282     	0           
  10          	0.29512     	-438263.28844	0.51274     	0           
  100         	0.17281     	-3.81142    	0.43710     	0           
  300         	0.17879     	-2.78919    	0.43435     	1           
  500         	0.17225     	-3.00929    	0.43117     	1           
  1000        	0.15961     	-3.01810    	0.41912     	3           
---> try to load best state
              	0.15961     	-3.01810    	0.41912     	3                eval state : test_on_restore;
              	0.15961     	-3.01810    	0.41912     	3                eval state : test_on_last_epoch;
---> final result
              	0.15961     	-3.01810    	0.41912     	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': 128, '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           	0.22076     	-261224094.77267	0.50725     	0           
  10          	0.22025     	-2192439.98711	0.50720     	0           
  100         	0.09661     	-2.46007    	0.35681     	0           
  300         	0.10384     	-5.57427    	0.39879     	1           
  500         	0.09784     	-5.96880    	0.40585     	1           
  1000        	0.09714     	-6.29476    	0.40602     	4           
---> try to load best state
              	0.09714     	-6.29476    	0.40602     	4                eval state : test_on_restore;
              	0.09714     	-6.29476    	0.40602     	4                eval state : test_on_last_epoch;
---> final result
              	0.09714     	-6.29476    	0.40602     	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': 128, '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           	0.22769     	-371735196.74543	0.50631     	0           
  10          	0.22812     	-4694204.74321	0.50613     	0           
  100         	0.06675     	-0.35284    	0.27073     	0           
  300         	0.04425     	0.65375     	0.16889     	1           
  500         	0.04273     	0.50653     	0.17929     	1           
  1000        	0.03364     	0.67723     	0.16026     	3           
---> try to load best state
              	0.03364     	0.67723     	0.16026     	3                eval state : test_on_restore;
              	0.03364     	0.67723     	0.16026     	3                eval state : test_on_last_epoch;
---> final result
              	0.03364     	0.67723     	0.16026     	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': 128, '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           	0.30318     	-122385992.91856	0.51746     	0           
  10          	0.30592     	-268355.75651	0.51789     	0           
  100         	0.04666     	0.63460     	0.14103     	0           
  300         	0.04089     	0.51701     	0.14707     	1           
  500         	0.03406     	0.61390     	0.13515     	1           
  1000        	0.03024     	0.72765     	0.11186     	3           
---> try to load best state
              	0.03024     	0.72765     	0.11186     	3                eval state : test_on_restore;
              	0.03024     	0.72765     	0.11186     	3                eval state : test_on_last_epoch;
---> final result
              	0.03024     	0.72765     	0.11186     	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': 128, '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           	0.27818     	-43958500.14077	0.50969     	0           
  10          	0.27401     	-62642.18824	0.50780     	0           
  100         	0.08810     	0.81614     	0.15848     	0           
  300         	0.05334     	0.89421     	0.16524     	1           
  500         	0.05105     	0.91364     	0.11598     	1           
  1000        	0.03835     	0.93411     	0.09251     	3           
---> try to load best state
              	0.03835     	0.93411     	0.09251     	3                eval state : test_on_restore;
              	0.03835     	0.93411     	0.09251     	3                eval state : test_on_last_epoch;
---> final result
              	0.03835     	0.93411     	0.09251     	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': 128, '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           	0.28862     	-418893828.60341	0.51182     	0           
  10          	0.29125     	-417091.69371	0.51234     	0           
  100         	0.06687     	0.77562     	0.16451     	0           
  300         	0.06060     	0.91143     	0.14127     	1           
  500         	0.02440     	0.94185     	0.08340     	1           
  1000        	0.02483     	0.95133     	0.07853     	3           
---> try to load best state
              	0.02483     	0.95133     	0.07853     	3                eval state : test_on_restore;
              	0.02483     	0.95133     	0.07853     	3                eval state : test_on_last_epoch;
---> final result
              	0.02483     	0.95133     	0.07853     	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': 128, '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           	0.25320     	-138895169.48747	0.50627     	0           
  10          	0.25526     	-520536.97559	0.50615     	0           
  100         	0.08909     	-0.42666    	0.27891     	0           
  300         	0.08785     	-0.84960    	0.32673     	1           
  500         	0.07492     	-1.63639    	0.33670     	1           
  1000        	0.09942     	-1.13870    	0.35493     	3           
---> try to load best state
              	0.09942     	-1.13870    	0.35493     	3                eval state : test_on_restore;
              	0.09942     	-1.13870    	0.35493     	3                eval state : test_on_last_epoch;
---> final result
              	0.09942     	-1.13870    	0.35493     	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': 128, '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           	0.20687     	-438160150.37899	0.50975     	0           
  10          	0.20666     	-1560793.66058	0.50939     	0           
  100         	0.06891     	-0.56525    	0.29197     	0           
  300         	0.05364     	0.57780     	0.18732     	1           
  500         	0.05488     	0.35375     	0.21488     	1           
  1000        	0.05892     	-0.29754    	0.27049     	3           
---> try to load best state
              	0.05892     	-0.29754    	0.27049     	3                eval state : test_on_restore;
              	0.05892     	-0.29754    	0.27049     	3                eval state : test_on_last_epoch;
---> final result
              	0.05892     	-0.29754    	0.27049     	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': 128, '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           	0.19171     	-1361957709.89183	0.51498     	0           
  10          	0.19130     	-2108673.35999	0.51481     	0           
  100         	0.07462     	-1.57600    	0.33284     	0           
  300         	0.05273     	-0.02121    	0.25691     	1           
  500         	0.05005     	-0.06256    	0.25806     	1           
  1000        	0.04899     	0.03180     	0.25031     	3           
---> try to load best state
              	0.04899     	0.03180     	0.25031     	3                eval state : test_on_restore;
              	0.04899     	0.03180     	0.25031     	3                eval state : test_on_last_epoch;
---> final result
              	0.04899     	0.03180     	0.25031     	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': 128, '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           	0.39833     	-36518015.29387	0.55801     	0           
  10          	0.39807     	-112744.04520	0.55730     	0           
  100         	0.12962     	0.77284     	0.31483     	0           
  300         	0.03746     	0.96921     	0.07409     	1           
  500         	0.05586     	0.95221     	0.09004     	1           
  1000        	0.02710     	0.96547     	0.08546     	4           
---> try to load best state
              	0.02710     	0.96547     	0.08546     	4                eval state : test_on_restore;
              	0.02710     	0.96547     	0.08546     	4                eval state : test_on_last_epoch;
---> final result
              	0.02710     	0.96547     	0.08546     	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': 128, '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           	0.30849     	-46239840.34659	0.51758     	0           
  10          	0.30373     	-468754.98344	0.51547     	0           
  100         	0.14604     	0.76274     	0.28017     	0           
  300         	0.03553     	0.91187     	0.09370     	1           
  500         	0.07585     	0.85038     	0.25727     	1           
  1000        	0.02959     	0.94824     	0.09131     	3           
---> try to load best state
              	0.02959     	0.94824     	0.09131     	3                eval state : test_on_restore;
              	0.02959     	0.94824     	0.09131     	3                eval state : test_on_last_epoch;
---> final result
              	0.02959     	0.94824     	0.09131     	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': 128, '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           	0.26225     	-26637875.56801	0.50695     	0           
  10          	0.26761     	-88963.09446	0.50636     	0           
  100         	0.07347     	0.58392     	0.18488     	0           
  300         	0.02948     	0.92612     	0.10362     	1           
  500         	0.04422     	0.89808     	0.10163     	1           
  1000        	0.02613     	0.95568     	0.10009     	3           
---> try to load best state
              	0.02613     	0.95568     	0.10009     	3                eval state : test_on_restore;
              	0.02613     	0.95568     	0.10009     	3                eval state : test_on_last_epoch;
---> final result
              	0.02613     	0.95568     	0.10009     	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': 128, '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           	0.17213     	-57809273706.54787	0.53730     	0           
  10          	0.17207     	-62243876.41658	0.53725     	0           
  100         	0.14573     	-198.74854  	0.51213     	0           
  300         	0.13424     	-76.65967   	0.49683     	1           
  500         	0.12883     	-48.93353   	0.48757     	2           
  1000        	0.14091     	-138.58451  	0.50674     	3           
---> try to load best state
              	0.14091     	-138.58451  	0.50674     	3                eval state : test_on_restore;
              	0.14091     	-138.58451  	0.50674     	3                eval state : test_on_last_epoch;
---> final result
              	0.14091     	-138.58451  	0.50674     	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': 128, '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           	0.26787     	-69962487.74208	0.50803     	0           
  10          	0.26819     	-250676.34388	0.50758     	0           
  100         	0.06397     	-0.16338    	0.26682     	0           
  300         	0.05182     	0.34049     	0.20563     	1           
  500         	0.05207     	0.49643     	0.18439     	1           
  1000        	0.06469     	0.08762     	0.22967     	3           
---> try to load best state
              	0.06469     	0.08762     	0.22967     	3                eval state : test_on_restore;
              	0.06469     	0.08762     	0.22967     	3                eval state : test_on_last_epoch;
---> final result
              	0.06469     	0.08762     	0.22967     	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': 128, '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           	0.27313     	-173681481.13162	0.50888     	0           
  10          	0.27157     	-245018.89559	0.50814     	0           
  100         	0.05846     	0.18214     	0.23533     	0           
  300         	0.04167     	0.75491     	0.14191     	1           
  500         	0.06094     	0.61546     	0.16409     	1           
  1000        	0.05247     	0.51323     	0.18991     	3           
---> try to load best state
              	0.05247     	0.51323     	0.18991     	3                eval state : test_on_restore;
              	0.05247     	0.51323     	0.18991     	3                eval state : test_on_last_epoch;
---> final result
              	0.05247     	0.51323     	0.18991     	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': 128, '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           	0.34663     	-30765176.62281	0.53365     	0           
  10          	0.34671     	-64114.03160	0.53294     	0           
  100         	0.07121     	0.74126     	0.17758     	0           
  300         	0.03328     	0.95284     	0.07253     	1           
  500         	0.04245     	0.72143     	0.14829     	1           
  1000        	0.02326     	0.95971     	0.07184     	3           
---> try to load best state
              	0.02326     	0.95971     	0.07184     	3                eval state : test_on_restore;
              	0.02326     	0.95971     	0.07184     	3                eval state : test_on_last_epoch;
---> final result
              	0.02326     	0.95971     	0.07184     	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': 128, '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           	0.26872     	-9559345901.52035	0.50798     	0           
  10          	0.26638     	-339681.82246	0.50711     	0           
  100         	0.05200     	0.52577     	0.19315     	0           
  300         	0.03684     	0.89448     	0.10529     	1           
  500         	0.03574     	0.89347     	0.10224     	2           
  1000        	0.03783     	0.93771     	0.12563     	4           
---> try to load best state
              	0.03783     	0.93771     	0.12563     	4                eval state : test_on_restore;
              	0.03783     	0.93771     	0.12563     	4                eval state : test_on_last_epoch;
---> final result
              	0.03783     	0.93771     	0.12563     	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': 128, '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           	0.29869     	-1382039578.09197	0.51433     	0           
  10          	0.29854     	-567772.37537	0.51435     	0           
  100         	0.07580     	0.76131     	0.19416     	0           
  300         	0.04421     	0.94292     	0.08887     	1           
  500         	0.02739     	0.94985     	0.07640     	2           
  1000        	0.03875     	0.94332     	0.08761     	4           
---> try to load best state
              	0.03875     	0.94332     	0.08761     	4                eval state : test_on_restore;
              	0.03875     	0.94332     	0.08761     	4                eval state : test_on_last_epoch;
---> final result
              	0.03875     	0.94332     	0.08761     	4                eval state : final;module_name : dmfal;cp_record_file : True;
