Fix pylint: do not use bare 'except' (#5025)

models/tf.py

@@ -268,7 +268,7 @@ def parse_model(d, ch, model, imgsz):  # model_dict, input_channels(3)
         for j, a in enumerate(args):
             try:
                 args[j] = eval(a) if isinstance(a, str) else a  # eval strings
-            except:
+            except NameError:
                 pass
 
         n = max(round(n * gd), 1) if n > 1 else n  # depth gain

models/yolo.py

@@ -233,7 +233,7 @@ def parse_model(d, ch):  # model_dict, input_channels(3)
         for j, a in enumerate(args):
             try:
                 args[j] = eval(a) if isinstance(a, str) else a  # eval strings
-            except:
+            except NameError:
                 pass
 
         n = n_ = max(round(n * gd), 1) if n > 1 else n  # depth gain

train.py

@@ -499,7 +499,6 @@ def main(opt, callbacks=Callbacks()):
     # DDP mode
     device = select_device(opt.device, batch_size=opt.batch_size)
     if LOCAL_RANK != -1:
-        from datetime import timedelta
         assert torch.cuda.device_count() > LOCAL_RANK, 'insufficient CUDA devices for DDP command'
         assert opt.batch_size % WORLD_SIZE == 0, '--batch-size must be multiple of CUDA device count'
         assert not opt.image_weights, '--image-weights argument is not compatible with DDP training'

utils/general.py

@@ -152,7 +152,7 @@ def is_colab():
     try:
         import google.colab
         return True
-    except Exception as e:
+    except ImportError:
         return False
 
 
@@ -160,6 +160,7 @@ def is_pip():
     # Is file in a pip package?
     return 'site-packages' in Path(__file__).resolve().parts
 
+
 def is_ascii(s=''):
     # Is string composed of all ASCII (no UTF) characters? (note str().isascii() introduced in python 3.7)
     s = str(s)  # convert list, tuple, None, etc. to str
@@ -741,11 +742,11 @@ def print_mutation(results, hyp, save_dir, bucket):
         data = pd.read_csv(evolve_csv)
         data = data.rename(columns=lambda x: x.strip())  # strip keys
         i = np.argmax(fitness(data.values[:, :7]))  #
-        f.write(f'# YOLOv5 Hyperparameter Evolution Results\n' +
+        f.write('# YOLOv5 Hyperparameter Evolution Results\n' +
                 f'# Best generation: {i}\n' +
                 f'# Last generation: {len(data)}\n' +
-                f'# ' + ', '.join(f'{x.strip():>20s}' for x in keys[:7]) + '\n' +
-                f'# ' + ', '.join(f'{x:>20.5g}' for x in data.values[i, :7]) + '\n\n')
+                '# ' + ', '.join(f'{x.strip():>20s}' for x in keys[:7]) + '\n' +
+                '# ' + ', '.join(f'{x:>20.5g}' for x in data.values[i, :7]) + '\n\n')
         yaml.safe_dump(hyp, f, sort_keys=False)
 
     if bucket: