Update Actions with Lychee and GitHub Token (#12592)

* Add Ultralytics Actions

* Auto-format by Ultralytics actions

* Update format.yml

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

---------

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

utils/aws/resume.py

@@ -14,27 +14,27 @@ if str(ROOT) not in sys.path:
     sys.path.append(str(ROOT))  # add ROOT to PATH
 
 port = 0  # --master_port
-path = Path('').resolve()
-for last in path.rglob('*/**/last.pt'):
+path = Path("").resolve()
+for last in path.rglob("*/**/last.pt"):
     ckpt = torch.load(last)
-    if ckpt['optimizer'] is None:
+    if ckpt["optimizer"] is None:
         continue
 
     # Load opt.yaml
-    with open(last.parent.parent / 'opt.yaml', errors='ignore') as f:
+    with open(last.parent.parent / "opt.yaml", errors="ignore") as f:
         opt = yaml.safe_load(f)
 
     # Get device count
-    d = opt['device'].split(',')  # devices
+    d = opt["device"].split(",")  # devices
     nd = len(d)  # number of devices
     ddp = nd > 1 or (nd == 0 and torch.cuda.device_count() > 1)  # distributed data parallel
 
     if ddp:  # multi-GPU
         port += 1
-        cmd = f'python -m torch.distributed.run --nproc_per_node {nd} --master_port {port} train.py --resume {last}'
+        cmd = f"python -m torch.distributed.run --nproc_per_node {nd} --master_port {port} train.py --resume {last}"
     else:  # single-GPU
-        cmd = f'python train.py --resume {last}'
+        cmd = f"python train.py --resume {last}"
 
-    cmd += ' > /dev/null 2>&1 &'  # redirect output to dev/null and run in daemon thread
+    cmd += " > /dev/null 2>&1 &"  # redirect output to dev/null and run in daemon thread
     print(cmd)
     os.system(cmd)