Merge pull request #31 from WenjieDu/fix_config_err_for_NNI_tuning

Fixing errors in config files for NNI tuning

NNI_tuning/BRITS/BRITS_basic_config.ini

@@ -42,16 +42,18 @@ model_type = BRITS
 rnn_hidden_size = 1024
 
 [training]
-; whether to have masked imputation task in training
-masked_imputation_task = False
+; whether to have Masked Imputation Task (MIT) in training
+MIT = False
+; whether to have Observed Reconstruction Task (ORT) in training
+ORT = True
 ; max num of training epochs
 epochs = 100
 ; which device for training, cpu/cuda
 device = cuda
 ; learning rate
 lr = 0.001
-; weight for regression loss
-regression_loss_weight = 1
+; weight for reconstruction loss
+reconstruction_loss_weight = 1
 ; weight for imputation loss
 imputation_loss_weight = 1
 ; weight for consistency loss, here we use to adjust the importance of consistency loss

NNI_tuning/MRNN/MRNN_basic_config.ini

@@ -42,20 +42,20 @@ model_type = MRNN
 rnn_hidden_size = 1024
 
 [training]
-; whether to have masked imputation task in training
-masked_imputation_task = False
+; whether to have Masked Imputation Task (MIT) in training
+MIT = False
+; whether to have Observed Reconstruction Task (ORT) in training
+ORT = True
 ; max num of training epochs
 epochs = 100
 ; which device for training, cpu/cuda
 device = cuda
 ; learning rate
 lr = 0.001
-; weight for regression loss
-regression_loss_weight = 1
+; weight for reconstruction loss
+reconstruction_loss_weight = 1
 ; weight for imputation loss
 imputation_loss_weight = 1
-; weight for consistency loss, here we use to adjust the importance of consistency loss
-consistency_loss_weight = 1
 ; patience of early stopping, -1 means not applied (current early stopping is based on total loss)
 early_stop_patience = 30
 ; what type of optimizer to use, adam/adamw

NNI_tuning/SAITS/SAITS_basic_config.ini

@@ -62,17 +62,19 @@ dropout = 0.1
 diagonal_attention_mask = True
 
 [training]
-; whether to have masked imputation task in training
-masked_imputation_task = True
+; whether to have Masked Imputation Task (MIT) in training
+MIT = True
+; whether to have Observed Reconstruction Task (ORT) in training
+ORT = True
 ; max num of training epochs
 epochs = 100
 ; which device for training, cpu/cuda
 device = cuda
 ; learning rate
 lr = 0.001
-; weight for regression loss, 0.3 is the default one from original paper
-regression_loss_weight = 1
-; weight for imputation loss, 0.3 is the default one from original paper
+; weight for reconstruction loss
+reconstruction_loss_weight = 1
+; weight for imputation loss
 imputation_loss_weight = 1
 ; patience of early stopping, -1 means not applied (current early stopping is based on total loss)
 early_stop_patience = -1

NNI_tuning/Transformer/Transformer_basic_config.ini

@@ -62,17 +62,19 @@ dropout = 0.1
 diagonal_attention_mask = False
 
 [training]
-; whether to have masked imputation task in training
-masked_imputation_task = True
+; whether to have Masked Imputation Task (MIT) in training
+MIT = True
+; whether to have Observed Reconstruction Task (ORT) in training
+ORT = True
 ; max num of training epochs
 epochs = 100
 ; which device for training, cpu/cuda
 device = cuda
 ; learning rate
 lr = 0.001
-; weight for regression loss, 0.3 is the default one from original paper
-regression_loss_weight = 1
-; weight for imputation loss, 0.3 is the default one from original paper
+; weight for reconstruction loss
+reconstruction_loss_weight = 1
+; weight for imputation loss
 imputation_loss_weight = 1
 ; patience of early stopping, -1 means not applied (current early stopping is based on total loss)
 early_stop_patience = -1