cleaning broken strings

src/pl_bolts/models/detection/faster_rcnn/faster_rcnn_module.py

@@ -95,8 +95,8 @@ def __init__(
                     import warnings
 
                     warnings.warn(
-                        "You would need to load the pretrained state_dict yourself if you are "
-                        "providing backbone of type torch.nn.Module / pl.LightningModule."
+                        "You would need to load the pretrained state_dict yourself if you are"
+                        " providing backbone of type torch.nn.Module / pl.LightningModule."
                     )
             else:
                 backbone_model = create_fasterrcnn_backbone(

src/pl_bolts/models/detection/yolo/darknet_network.py

@@ -242,7 +242,7 @@ def _read_config(self, config_file: Iterable[str]) -> List[Dict[str, Any]]:
         def convert(key: str, value: str) -> Union[str, int, float, List[Union[str, int, float]]]:
             """Converts a value to the correct type based on key."""
             if key not in variable_types:
-                warn("Unknown YOLO configuration variable: " + key)
+                warn(f"Unknown YOLO configuration variable: {key}")
                 return value
             if key in list_variables:
                 return [variable_types[key](v) for v in value.split(",")]

src/pl_bolts/models/gans/srgan/srgan_module.py

@@ -200,8 +200,8 @@ def cli_main(args=None):
     generator_checkpoint = Path(f"model_checkpoints/srresnet-{args.dataset}-scale_factor={args.scale_factor}.pt")
     if not generator_checkpoint.exists():
         warn(
-            "No generator checkpoint found. Training generator from scratch. \
-            Use srresnet_module.py to pretrain the generator."
+            "No generator checkpoint found. Training generator from scratch."
+            " Use srresnet_module.py to pretrain the generator."
         )
         generator_checkpoint = None
 

src/pl_bolts/optimizers/lr_scheduler.py

@@ -73,7 +73,7 @@ def get_lr(self) -> List[float]:
         """Compute learning rate using chainable form of the scheduler."""
         if not self._get_lr_called_within_step:
             warnings.warn(
-                "To get the last learning rate computed by the scheduler, " "please use `get_last_lr()`.",
+                "To get the last learning rate computed by the scheduler; please use `get_last_lr()`.",
                 UserWarning,
             )
 

src/pl_bolts/utils/pretrained_weights.py

@@ -5,10 +5,10 @@
 from pl_bolts.utils.stability import under_review
 
 vae_imagenet2012 = (
-    "https://pl-bolts-weights.s3.us-east-2.amazonaws.com/" "vae/imagenet_06_22_2019/checkpoints/epoch%3D63.ckpt"
+    "https://pl-bolts-weights.s3.us-east-2.amazonaws.com/vae/imagenet_06_22_2019/checkpoints/epoch%3D63.ckpt"
 )
 
-cpcv2_resnet18 = "https://pl-bolts-weights.s3.us-east-2.amazonaws.com/" "cpc/resnet18-v6/epoch%3D85.ckpt"
+cpcv2_resnet18 = "https://pl-bolts-weights.s3.us-east-2.amazonaws.com/cpc/resnet18-v6/epoch%3D85.ckpt"
 urls = {"vae-imagenet2012": vae_imagenet2012, "CPC_v2-resnet18": cpcv2_resnet18}