refactor: make patience optional, init KMeans in CRLI properly, and m…

…ake VaDER raise error when training failed;

pypots/base.py

@@ -383,7 +383,7 @@ def __init__(
         self,
         batch_size: int,
         epochs: int,
-        patience: int,
+        patience: Optional[int] = None,
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,
         saving_path: str = None,

pypots/classification/base.py

@@ -178,7 +178,7 @@ def __init__(
         n_classes: int,
         batch_size: int,
         epochs: int,
-        patience: int,
+        patience: Optional[int] = None,
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,
         saving_path: str = None,

pypots/classification/brits/model.py

@@ -193,7 +193,7 @@ def __init__(
         reconstruction_weight: float = 1,
         batch_size: int = 32,
         epochs: int = 100,
-        patience: int = None,
+        patience: Optional[int] = None,
         optimizer: Optional[Optimizer] = Adam(),
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,

pypots/classification/grud/model.py

@@ -186,7 +186,7 @@ def __init__(
         rnn_hidden_size: int,
         batch_size: int = 32,
         epochs: int = 100,
-        patience: int = None,
+        patience: Optional[int] = None,
         optimizer: Optional[Optimizer] = Adam(),
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,

pypots/classification/raindrop/model.py

@@ -393,7 +393,7 @@ def __init__(
         static=False,
         batch_size=32,
         epochs=100,
-        patience: int = None,
+        patience: Optional[int] = None,
         optimizer: Optional[Optimizer] = Adam(),
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,

pypots/clustering/base.py

@@ -166,7 +166,7 @@ def __init__(
         n_clusters: int,
         batch_size: int,
         epochs: int,
-        patience: int,
+        patience: Optional[int] = None,
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,
         saving_path: str = None,

pypots/clustering/crli/model.py

@@ -50,7 +50,9 @@ def __init__(
             n_steps, rnn_hidden_size * 2, n_features, decoder_fcn_output_dims, device
         )  # fully connected network is included in Decoder
         self.kmeans = KMeans(
-            n_clusters=n_clusters
+            n_clusters=n_clusters,
+            n_init=10,  # FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the
+            # value of `n_init` explicitly to suppress the warning.
         )  # TODO: implement KMean with torch for gpu acceleration
 
         self.n_clusters = n_clusters

pypots/clustering/vader/model.py

@@ -343,7 +343,7 @@ def __init__(
         batch_size: int = 32,
         epochs: int = 100,
         pretrain_epochs: int = 10,
-        patience: int = None,
+        patience: Optional[int] = None,
         optimizer: Optional[Optimizer] = Adam(),
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,
@@ -462,7 +462,7 @@ def _train_model(
                             "Now quit to let you check your model training.\n"
                             "Please raise an issue https://github.com/WenjieDu/PyPOTS/issues if you have questions."
                         )
-                        exit()
+                        raise RuntimeError
                     else:
                         reg_covar *= 2
 

pypots/forecasting/base.py

@@ -165,7 +165,7 @@ def __init__(
         # n_forecasting_steps: int,
         batch_size: int,
         epochs: int,
-        patience: int,
+        patience: Optional[int] = None,
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,
         saving_path: str = None,

pypots/imputation/base.py

@@ -173,7 +173,7 @@ def __init__(
         self,
         batch_size: int,
         epochs: int,
-        patience: int,
+        patience: Optional[int] = None,
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,
         saving_path: str = None,

pypots/imputation/brits/model.py

@@ -411,7 +411,7 @@ def __init__(
         rnn_hidden_size: int,
         batch_size: int = 32,
         epochs: int = 100,
-        patience: int = None,
+        patience: Optional[int] = None,
         optimizer: Optional[Optimizer] = Adam(),
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,

pypots/imputation/gpvae/model.py

@@ -297,7 +297,7 @@ def __init__(
         window_size: int = 3,
         batch_size: int = 32,
         epochs: int = 100,
-        patience: int = None,
+        patience: Optional[int] = None,
         optimizer: Optional[Optimizer] = Adam(),
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,

pypots/imputation/mrnn/model.py

@@ -169,7 +169,7 @@ def __init__(
         rnn_hidden_size: int,
         batch_size: int = 32,
         epochs: int = 100,
-        patience: int = None,
+        patience: Optional[int] = None,
         optimizer: Optional[Optimizer] = Adam(),
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,

pypots/imputation/transformer/model.py

@@ -227,7 +227,7 @@ def __init__(
         MIT_weight: int = 1,
         batch_size: int = 32,
         epochs: int = 100,
-        patience: int = None,
+        patience: Optional[int] = None,
         optimizer: Optional[Optimizer] = Adam(),
         num_workers: int = 0,
         device: Optional[Union[str, torch.device, list]] = None,