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

  Demo DC 
  seed: None 
  interp_data: False 

----------------------------------------
---> Training x -> yl part
---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': None, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[0]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.01, 'optional_param': 0.01, 'noise': 0.01}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	229.16650   	400.25040   	-218717.34231	0           
  10          	228.86861   	399.94827   	-42056.28915	0           
  100         	227.20862   	398.14847   	-2842.27901 	0           
---> try to load best state
              	227.20862   	398.14847   	-2842.27901 	0                eval state : test_on_restore;
              	227.20862   	398.14847   	-2842.27901 	0                eval state : test_on_last_epoch;
---> final result
              	227.20862   	398.14847   	-2842.27901 	0                eval state : final;
----------> finish x-yl training


---------->
NAR for 4 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': None, 'train_start_index': 0, 'train_sample': 4, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	222.18645   	396.78598   	-362763627748492864.00000	0           
  10          	222.18645   	396.78598   	-362763627748492864.00000	0           
  100         	222.18645   	396.78598   	-362763627748492864.00000	0           
---> try to load best state
              	222.18645   	396.78598   	-362763627748492864.00000	0                eval state : test_on_restore;
              	222.18645   	396.78598   	-362763627748492864.00000	0                eval state : test_on_last_epoch;
---> final result
              	222.18645   	396.78598   	-362763627748492864.00000	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 8 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': None, 'train_start_index': 0, 'train_sample': 8, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	223.72980   	399.03928   	-1222959812046806016.00000	0           
  10          	223.72980   	399.03928   	-1222959812046806016.00000	0           
  100         	223.72980   	399.03928   	-1222959812046806016.00000	0           
---> try to load best state
              	223.72980   	399.03928   	-1222959812046806016.00000	0                eval state : test_on_restore;
              	223.72980   	399.03928   	-1222959812046806016.00000	0                eval state : test_on_last_epoch;
---> final result
              	223.72980   	399.03928   	-1222959812046806016.00000	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 16 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': None, 'train_start_index': 0, 'train_sample': 16, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	220.52234   	393.68842   	-2575515085986559688704.00000	0           
  10          	220.52234   	393.68842   	-422787013725769984.00000	0           
  100         	220.52234   	393.68842   	-403589130296931776.00000	0           
---> try to load best state
              	220.52234   	393.68842   	-403589130296931776.00000	0                eval state : test_on_restore;
              	220.52234   	393.68842   	-403589130296931776.00000	0                eval state : test_on_last_epoch;
---> final result
              	220.52234   	393.68842   	-403589130296931776.00000	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 32 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': None, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	210.45300   	377.01804   	-4494860023647.65625	0           
  10          	210.40845   	376.96637   	-2444444.14615	0           
  100         	210.23152   	376.70245   	-50647.85737	0           
---> try to load best state
              	210.23152   	376.70245   	-50647.85737	0                eval state : test_on_restore;
              	210.23152   	376.70245   	-50647.85737	0                eval state : test_on_last_epoch;
---> final result
              	210.23152   	376.70245   	-50647.85737	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end

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

  Demo DC 
  seed: 0 
  interp_data: False 

----------------------------------------
---> Training x -> yl part
---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[0]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.01, 'optional_param': 0.01, 'noise': 0.01}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	136.96867   	288.47672   	-20.63287   	0           
  10          	130.51237   	280.25156   	-18.87523   	0           
  100         	109.15409   	248.18044   	-15.00918   	0           
---> try to load best state
              	109.15409   	248.18044   	-15.00918   	0                eval state : test_on_restore;
              	109.15409   	248.18044   	-15.00918   	0                eval state : test_on_last_epoch;
---> final result
              	109.15409   	248.18044   	-15.00918   	0                eval state : final;
----------> finish x-yl training


---------->
NAR for 4 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 4, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	172.84198   	318.02939   	-213865.66634	0           
  10          	171.09187   	315.85513   	-2140.33053 	0           
  100         	163.76331   	305.39502   	-326.94863  	0           
---> try to load best state
              	163.76331   	305.39502   	-326.94863  	0                eval state : test_on_restore;
              	163.76331   	305.39502   	-326.94863  	0                eval state : test_on_last_epoch;
---> final result
              	163.76331   	305.39502   	-326.94863  	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 8 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 8, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	186.91475   	339.24283   	-79531081.80472	0           
  10          	185.05280   	336.12204   	-9730.18964 	0           
  100         	161.28819   	299.15411   	-279.83813  	0           
---> try to load best state
              	161.28819   	299.15411   	-279.83813  	0                eval state : test_on_restore;
              	161.28819   	299.15411   	-279.83813  	0                eval state : test_on_last_epoch;
---> final result
              	161.28819   	299.15411   	-279.83813  	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 16 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 16, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	185.77962   	338.11545   	-2528287.66027	0           
  10          	179.48213   	330.32883   	-1007.13498 	0           
  100         	132.57875   	271.14706   	-42.28158   	0           
---> try to load best state
              	132.57875   	271.14706   	-42.28158   	0                eval state : test_on_restore;
              	132.57875   	271.14706   	-42.28158   	0                eval state : test_on_last_epoch;
---> final result
              	132.57875   	271.14706   	-42.28158   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 32 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 0, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	179.76506   	329.34964   	-2519.82358 	0           
  10          	169.60982   	317.98926   	-222.71570  	0           
  100         	126.58013   	265.29282   	-37.10372   	0           
---> try to load best state
              	126.58013   	265.29282   	-37.10372   	0                eval state : test_on_restore;
              	126.58013   	265.29282   	-37.10372   	0                eval state : test_on_last_epoch;
---> final result
              	126.58013   	265.29282   	-37.10372   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end

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

  Demo DC 
  seed: 1 
  interp_data: False 

----------------------------------------
---> Training x -> yl part
---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[0]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.01, 'optional_param': 0.01, 'noise': 0.01}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	141.62970   	295.41553   	-21.97943   	0           
  10          	135.75763   	288.24619   	-19.63268   	0           
  100         	111.21845   	252.30324   	-15.99886   	0           
---> try to load best state
              	111.21845   	252.30324   	-15.99886   	0                eval state : test_on_restore;
              	111.21845   	252.30324   	-15.99886   	0                eval state : test_on_last_epoch;
---> final result
              	111.21845   	252.30324   	-15.99886   	0                eval state : final;
----------> finish x-yl training


---------->
NAR for 4 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 4, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	207.04236   	370.20746   	-5403425293034173.00000	0           
  10          	207.04236   	370.20746   	-5403425293034173.00000	0           
  100         	207.04236   	370.20746   	-5403425293034173.00000	0           
---> try to load best state
              	207.04236   	370.20746   	-5403425293034173.00000	0                eval state : test_on_restore;
              	207.04236   	370.20746   	-5403425293034173.00000	0                eval state : test_on_last_epoch;
---> final result
              	207.04236   	370.20746   	-5403425293034173.00000	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 8 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 8, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	205.09174   	367.50717   	-9843038141947.46094	0           
  10          	204.83018   	366.91150   	-955440.34466	0           
  100         	189.25099   	338.28131   	-676.52899  	0           
---> try to load best state
              	189.25099   	338.28131   	-676.52899  	0                eval state : test_on_restore;
              	189.25099   	338.28131   	-676.52899  	0                eval state : test_on_last_epoch;
---> final result
              	189.25099   	338.28131   	-676.52899  	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 16 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 16, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	194.23352   	352.51825   	-863.73162  	0           
  10          	182.27119   	339.56555   	-168.63525  	0           
  100         	123.98197   	262.70721   	-34.31686   	0           
---> try to load best state
              	123.98197   	262.70721   	-34.31686   	0                eval state : test_on_restore;
              	123.98197   	262.70721   	-34.31686   	0                eval state : test_on_last_epoch;
---> final result
              	123.98197   	262.70721   	-34.31686   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 32 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 1, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	179.72917   	329.32907   	-3102.20332 	0           
  10          	168.38405   	317.28839   	-316.74092  	0           
  100         	135.80992   	277.59116   	-45.64690   	0           
---> try to load best state
              	135.80992   	277.59116   	-45.64690   	0                eval state : test_on_restore;
              	135.80992   	277.59116   	-45.64690   	0                eval state : test_on_last_epoch;
---> final result
              	135.80992   	277.59116   	-45.64690   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end

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

  Demo DC 
  seed: 2 
  interp_data: False 

----------------------------------------
---> Training x -> yl part
---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[0]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.01, 'optional_param': 0.01, 'noise': 0.01}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	143.97435   	300.47186   	-20.65250   	0           
  10          	137.87355   	292.61481   	-18.50099   	0           
  100         	116.11007   	259.64233   	-15.07110   	0           
---> try to load best state
              	116.11007   	259.64233   	-15.07110   	0                eval state : test_on_restore;
              	116.11007   	259.64233   	-15.07110   	0                eval state : test_on_last_epoch;
---> final result
              	116.11007   	259.64233   	-15.07110   	0                eval state : final;
----------> finish x-yl training


---------->
NAR for 4 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 4, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	209.80206   	375.97742   	-32589825895041588.00000	0           
  10          	209.80206   	375.97742   	-32589825895041588.00000	0           
  100         	209.80206   	375.97742   	-32589825895041588.00000	0           
---> try to load best state
              	209.80206   	375.97742   	-32589825895041588.00000	0                eval state : test_on_restore;
              	209.80206   	375.97742   	-32589825895041588.00000	0                eval state : test_on_last_epoch;
---> final result
              	209.80206   	375.97742   	-32589825895041588.00000	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 8 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 8, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	187.63960   	347.93884   	-993.91361  	0           
  10          	168.30450   	328.01562   	-372.84177  	0           
  100         	130.94838   	279.53003   	-53.72443   	0           
---> try to load best state
              	130.94838   	279.53003   	-53.72443   	0                eval state : test_on_restore;
              	130.94838   	279.53003   	-53.72443   	0                eval state : test_on_last_epoch;
---> final result
              	130.94838   	279.53003   	-53.72443   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 16 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 16, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	187.02490   	342.32532   	-740.35418  	0           
  10          	173.58690   	327.82388   	-112.13526  	0           
  100         	135.28989   	280.91422   	-36.72769   	0           
---> try to load best state
              	135.28989   	280.91422   	-36.72769   	0                eval state : test_on_restore;
              	135.28989   	280.91422   	-36.72769   	0                eval state : test_on_last_epoch;
---> final result
              	135.28989   	280.91422   	-36.72769   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 32 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 2, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	182.45958   	334.67157   	-2977.26190 	0           
  10          	167.76320   	318.08167   	-138.21260  	0           
  100         	127.06474   	270.58987   	-28.02411   	0           
---> try to load best state
              	127.06474   	270.58987   	-28.02411   	0                eval state : test_on_restore;
              	127.06474   	270.58987   	-28.02411   	0                eval state : test_on_last_epoch;
---> final result
              	127.06474   	270.58987   	-28.02411   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end

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

  Demo DC 
  seed: 3 
  interp_data: False 

----------------------------------------
---> Training x -> yl part
---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[0]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.01, 'optional_param': 0.01, 'noise': 0.01}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	142.28430   	299.41339   	-18.13008   	0           
  10          	136.60651   	292.02847   	-16.50376   	0           
  100         	127.83466   	279.89227   	-14.52510   	0           
---> try to load best state
              	127.83466   	279.89227   	-14.52510   	0                eval state : test_on_restore;
              	127.83466   	279.89227   	-14.52510   	0                eval state : test_on_last_epoch;
---> final result
              	127.83466   	279.89227   	-14.52510   	0                eval state : final;
----------> finish x-yl training


---------->
NAR for 4 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 4, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	202.90852   	365.36447   	-834214034952376.12500	0           
  10          	202.90852   	365.36447   	-829528925979814.37500	0           
  100         	202.90852   	365.36447   	-827771118981551.37500	0           
---> try to load best state
              	202.90852   	365.36447   	-827771118981551.37500	0                eval state : test_on_restore;
              	202.90852   	365.36447   	-827771118981551.37500	0                eval state : test_on_last_epoch;
---> final result
              	202.90852   	365.36447   	-827771118981551.37500	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 8 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 8, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	199.87715   	359.79538   	-621417257274431.12500	0           
  10          	199.86232   	359.76514   	-27461232.80100	0           
  100         	198.77588   	357.44196   	-21945.18746	0           
---> try to load best state
              	198.77588   	357.44196   	-21945.18746	0                eval state : test_on_restore;
              	198.77588   	357.44196   	-21945.18746	0                eval state : test_on_last_epoch;
---> final result
              	198.77588   	357.44196   	-21945.18746	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 16 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 16, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	195.56828   	354.99185   	-629.29922  	0           
  10          	185.33308   	345.33139   	-96.95755   	0           
  100         	143.25920   	293.81494   	-33.57906   	0           
---> try to load best state
              	143.25920   	293.81494   	-33.57906   	0                eval state : test_on_restore;
              	143.25920   	293.81494   	-33.57906   	0                eval state : test_on_last_epoch;
---> final result
              	143.25920   	293.81494   	-33.57906   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 32 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 3, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	182.86755   	334.86252   	-2475.89029 	0           
  10          	169.24937   	320.20935   	-117.99632  	0           
  100         	135.41681   	283.55493   	-24.51623   	0           
---> try to load best state
              	135.41681   	283.55493   	-24.51623   	0                eval state : test_on_restore;
              	135.41681   	283.55493   	-24.51623   	0                eval state : test_on_last_epoch;
---> final result
              	135.41681   	283.55493   	-24.51623   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end

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

  Demo DC 
  seed: 4 
  interp_data: False 

----------------------------------------
---> Training x -> yl part
---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]'], 'outputs_format': ['y[0]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.01, 'optional_param': 0.01, 'noise': 0.01}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	134.84125   	285.12491   	-21.99945   	0           
  10          	129.69356   	278.58139   	-20.08405   	0           
  100         	100.20673   	230.74681   	-17.32935   	0           
---> try to load best state
              	100.20673   	230.74681   	-17.32935   	0                eval state : test_on_restore;
              	100.20673   	230.74681   	-17.32935   	0                eval state : test_on_last_epoch;
---> final result
              	100.20673   	230.74681   	-17.32935   	0                eval state : final;
----------> finish x-yl training


---------->
NAR for 4 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 4, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	176.50136   	322.97412   	-645882507303476.87500	0           
  10          	176.48674   	322.95038   	-284350264.50256	0           
  100         	176.38771   	322.77426   	-7559477.51964	0           
---> try to load best state
              	176.38771   	322.77426   	-7559477.51964	0                eval state : test_on_restore;
              	176.38771   	322.77426   	-7559477.51964	0                eval state : test_on_last_epoch;
---> final result
              	176.38771   	322.77426   	-7559477.51964	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 8 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 8, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	158.74631   	296.44135   	-9689.42466 	0           
  10          	155.31369   	293.01593   	-1070.09695 	0           
  100         	126.61762   	258.07401   	-82.03151   	0           
---> try to load best state
              	126.61762   	258.07401   	-82.03151   	0                eval state : test_on_restore;
              	126.61762   	258.07401   	-82.03151   	0                eval state : test_on_last_epoch;
---> final result
              	126.61762   	258.07401   	-82.03151   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 16 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 16, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	161.71968   	301.18765   	-85383.95984	0           
  10          	157.09636   	296.24915   	-936.66774  	0           
  100         	118.51624   	247.64883   	-54.63981   	0           
---> try to load best state
              	118.51624   	247.64883   	-54.63981   	0                eval state : test_on_restore;
              	118.51624   	247.64883   	-54.63981   	0                eval state : test_on_last_epoch;
---> final result
              	118.51624   	247.64883   	-54.63981   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
---> end


---------->
NAR for 32 samples
---> Training x,yl -> yh part

---> module config
  dataset: {'name': 'FlowMix3D_MF', 'interp_data': False, 'seed': 4, 'train_start_index': 0, 'train_sample': 32, 'eval_start_index': 0, 'eval_sample': 128, 'inputs_format': ['x[0]', 'y[0]'], 'outputs_format': ['y[-1]'], 'force_2d': True, 'x_sample_to_last_dim': False, 'y_sample_to_last_dim': False, 'slice_param': [0.6, 0.4]}
  lr: {'kernel': 0.1, 'optional_param': 0.1, 'noise': 0.1}
  kernel: {'K1': {'SE': {'exp_restrict': False, 'length_scale': 1.0, 'scale': 1.0}}}
  evaluate_method: ['mae', 'rmse', 'r2']
  optimizer: adam
  exp_restrict: False
  input_normalize: True
  output_normalize: True
  noise_init: 100.0
  pca: {'type': 'listPCA', 'r': 0.99}
---> training record
  epoch       	mae         	rmse        	r2          	time        
  1           	174.15630   	320.20688   	-3656.81464 	0           
  10          	164.52467   	309.19717   	-304.86328  	0           
  100         	140.19066   	276.59131   	-97.96545   	0           
---> try to load best state
              	140.19066   	276.59131   	-97.96545   	0                eval state : test_on_restore;
              	140.19066   	276.59131   	-97.96545   	0                eval state : test_on_last_epoch;
---> final result
              	140.19066   	276.59131   	-97.96545   	0                eval state : final;module_name : DC_cigp;cp_record_file : True;
