[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

tiatoolbox/models/architecture/vanilla.py

@@ -117,7 +117,7 @@ def _get_timm_architecture(
     Example:
         >>> model = _get_timm_architecture("UNI", pretrained=True)
         >>> print(model)
-    
+
     """
     if arch_name in [f"efficientnet_b{i}" for i in range(8)]:
         model = timm.create_model(arch_name, pretrained=pretrained)
@@ -298,7 +298,7 @@ def forward(self: CNNModel, imgs: torch.Tensor) -> torch.Tensor:
         Returns:
             torch.Tensor:
                 The output logits after passing through the model.
-        
+
         """
         feat = self.feat_extract(imgs)
         gap_feat = self.pool(feat)
@@ -319,7 +319,7 @@ def postproc(image: np.ndarray) -> np.ndarray:
         Returns:
             np.ndarray:
                 The post-processed image array.
-        
+
         """
         return _postproc(image=image)
 
@@ -345,7 +345,7 @@ def infer_batch(
         Example:
             >>> output = _infer_batch(model, batch_data, "cuda")
             >>> print(output)
-        
+
         """
         return _infer_batch(model=model, batch_data=batch_data, device=device)
 
@@ -386,7 +386,7 @@ class TimmModel(ModelABC):
         >>> model = TimmModel("UNI", pretrained=True)
         >>> output = model(torch.randn(1, 3, 224, 224))
         >>> print(output.shape)
-    
+
     """
 
     def __init__(
@@ -540,7 +540,7 @@ def forward(self: CNNBackbone, imgs: torch.Tensor) -> torch.Tensor:
         Returns:
             torch.Tensor:
                 The extracted features.
-        
+
         """
         feat = self.feat_extract(imgs)
         gap_feat = self.pool(feat)
@@ -572,7 +572,7 @@ def infer_batch(
         Example:
             >>> output = CNNBackbone.infer_batch(model, batch_data, "cuda")
             >>> print(output)
-        
+
         """
         return [_infer_batch(model=model, batch_data=batch_data, device=device)]
 
@@ -660,6 +660,6 @@ def infer_batch(
         Example:
             >>> output = TimmBackbone.infer_batch(model, batch_data, "cuda")
             >>> print(output)
-        
+
         """
         return [_infer_batch(model=model, batch_data=batch_data, device=device)]