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utils/dataloaders.py

@@ -355,9 +355,9 @@ class LoadImages:
             self._new_video(videos[0])  # new video
         else:
             self.cap = None
-        assert (
-            self.nf > 0
-        ), f"No images or videos found in {p}. Supported formats are:\nimages: {IMG_FORMATS}\nvideos: {VID_FORMATS}"
+        assert self.nf > 0, (
+            f"No images or videos found in {p}. Supported formats are:\nimages: {IMG_FORMATS}\nvideos: {VID_FORMATS}"
+        )
 
     def __iter__(self):
         """Initializes iterator by resetting count and returns the iterator object itself."""

utils/general.py

@@ -495,9 +495,9 @@ def check_file(file, suffix=""):
             assert Path(file).exists() and Path(file).stat().st_size > 0, f"File download failed: {url}"  # check
         return file
     elif file.startswith("clearml://"):  # ClearML Dataset ID
-        assert (
-            "clearml" in sys.modules
-        ), "ClearML is not installed, so cannot use ClearML dataset. Try running 'pip install clearml'."
+        assert "clearml" in sys.modules, (
+            "ClearML is not installed, so cannot use ClearML dataset. Try running 'pip install clearml'."
+        )
         return file
     else:  # search
         files = []

utils/loggers/clearml/clearml_utils.py

@@ -41,11 +41,9 @@ def construct_dataset(clearml_info_string):
     with open(yaml_filenames[0]) as f:
         dataset_definition = yaml.safe_load(f)
 
-    assert set(
-        dataset_definition.keys()
-    ).issuperset(
-        {"train", "test", "val", "nc", "names"}
-    ), "The right keys were not found in the yaml file, make sure it at least has the following keys: ('train', 'test', 'val', 'nc', 'names')"
+    assert set(dataset_definition.keys()).issuperset({"train", "test", "val", "nc", "names"}), (
+        "The right keys were not found in the yaml file, make sure it at least has the following keys: ('train', 'test', 'val', 'nc', 'names')"
+    )
 
     data_dict = {
         "train": (

utils/torch_utils.py

@@ -121,9 +121,9 @@ def select_device(device="", batch_size=0, newline=True):
         os.environ["CUDA_VISIBLE_DEVICES"] = "-1"  # force torch.cuda.is_available() = False
     elif device:  # non-cpu device requested
         os.environ["CUDA_VISIBLE_DEVICES"] = device  # set environment variable - must be before assert is_available()
-        assert torch.cuda.is_available() and torch.cuda.device_count() >= len(
-            device.replace(",", "")
-        ), f"Invalid CUDA '--device {device}' requested, use '--device cpu' or pass valid CUDA device(s)"
+        assert torch.cuda.is_available() and torch.cuda.device_count() >= len(device.replace(",", "")), (
+            f"Invalid CUDA '--device {device}' requested, use '--device cpu' or pass valid CUDA device(s)"
+        )
 
     if not cpu and not mps and torch.cuda.is_available():  # prefer GPU if available
         devices = device.split(",") if device else "0"  # range(torch.cuda.device_count())  # i.e. 0,1,6,7