Ultralytics Refactor https://ultralytics.com/actions (#17701)

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

ultralytics/nn/tasks.py

@@ -960,10 +960,8 @@ def parse_model(d, ch, verbose=True):  # model_dict, input_channels(3)
         m = getattr(torch.nn, m[3:]) if "nn." in m else globals()[m]  # get module
         for j, a in enumerate(args):
             if isinstance(a, str):
-                try:
+                with contextlib.suppress(ValueError):
                     args[j] = locals()[a] if a in locals() else ast.literal_eval(a)
-                except ValueError:
-                    pass
         n = n_ = max(round(n * depth), 1) if n > 1 else n  # depth gain
         if m in {
             Classify,
@@ -1141,24 +1139,16 @@ def guess_model_task(model):
 
     # Guess from model cfg
     if isinstance(model, dict):
-        try:
+        with contextlib.suppress(Exception):
             return cfg2task(model)
-        except Exception:
-            pass
-
     # Guess from PyTorch model
     if isinstance(model, nn.Module):  # PyTorch model
         for x in "model.args", "model.model.args", "model.model.model.args":
-            try:
+            with contextlib.suppress(Exception):
                 return eval(x)["task"]
-            except Exception:
-                pass
         for x in "model.yaml", "model.model.yaml", "model.model.model.yaml":
-            try:
+            with contextlib.suppress(Exception):
                 return cfg2task(eval(x))
-            except Exception:
-                pass
-
         for m in model.modules():
             if isinstance(m, Segment):
                 return "segment"