ultralytics 8.3.8 replace contextlib with try for speed (#16782)

Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

ultralytics/nn/autobackend.py

@@ -1,7 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
 import ast
-import contextlib
 import json
 import platform
 import zipfile
@@ -45,8 +44,10 @@ def check_class_names(names):
 def default_class_names(data=None):
     """Applies default class names to an input YAML file or returns numerical class names."""
     if data:
-        with contextlib.suppress(Exception):
+        try:
             return yaml_load(check_yaml(data))["names"]
+        except:  # noqa E722
+            pass
     return {i: f"class{i}" for i in range(999)}  # return default if above errors
 
 
@@ -321,8 +322,10 @@ class AutoBackend(nn.Module):
             with open(w, "rb") as f:
                 gd.ParseFromString(f.read())
             frozen_func = wrap_frozen_graph(gd, inputs="x:0", outputs=gd_outputs(gd))
-            with contextlib.suppress(StopIteration):  # find metadata in SavedModel alongside GraphDef
+            try:  # find metadata in SavedModel alongside GraphDef
                 metadata = next(Path(w).resolve().parent.rglob(f"{Path(w).stem}_saved_model*/metadata.yaml"))
+            except StopIteration:
+                pass
 
         # TFLite or TFLite Edge TPU
         elif tflite or edgetpu:  # https://www.tensorflow.org/lite/guide/python#install_tensorflow_lite_for_python
@@ -345,10 +348,12 @@ class AutoBackend(nn.Module):
             input_details = interpreter.get_input_details()  # inputs
             output_details = interpreter.get_output_details()  # outputs
             # Load metadata
-            with contextlib.suppress(zipfile.BadZipFile):
+            try:
                 with zipfile.ZipFile(w, "r") as model:
                     meta_file = model.namelist()[0]
                     metadata = ast.literal_eval(model.read(meta_file).decode("utf-8"))
+            except zipfile.BadZipFile:
+                pass
 
         # TF.js
         elif tfjs:

ultralytics/nn/tasks.py

@@ -2,6 +2,7 @@
 
 import contextlib
 import pickle
+import re
 import types
 from copy import deepcopy
 from pathlib import Path
@@ -958,8 +959,10 @@ 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):
-                with contextlib.suppress(ValueError):
+                try:
                     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 {
@@ -1072,8 +1075,6 @@ def parse_model(d, ch, verbose=True):  # model_dict, input_channels(3)
 
 def yaml_model_load(path):
     """Load a YOLOv8 model from a YAML file."""
-    import re
-
     path = Path(path)
     if path.stem in (f"yolov{d}{x}6" for x in "nsmlx" for d in (5, 8)):
         new_stem = re.sub(r"(\d+)([nslmx])6(.+)?$", r"\1\2-p6\3", path.stem)
@@ -1100,11 +1101,10 @@ def guess_model_scale(model_path):
     Returns:
         (str): The size character of the model's scale, which can be n, s, m, l, or x.
     """
-    with contextlib.suppress(AttributeError):
-        import re
-
+    try:
         return re.search(r"yolo[v]?\d+([nslmx])", Path(model_path).stem).group(1)  # n, s, m, l, or x
-    return ""
+    except AttributeError:
+        return ""
 
 
 def guess_model_task(model):
@@ -1137,17 +1137,23 @@ def guess_model_task(model):
 
     # Guess from model cfg
     if isinstance(model, dict):
-        with contextlib.suppress(Exception):
+        try:
             return cfg2task(model)
+        except:  # noqa E722
+            pass
 
     # Guess from PyTorch model
     if isinstance(model, nn.Module):  # PyTorch model
         for x in "model.args", "model.model.args", "model.model.model.args":
-            with contextlib.suppress(Exception):
+            try:
                 return eval(x)["task"]
+            except:  # noqa E722
+                pass
         for x in "model.yaml", "model.model.yaml", "model.model.model.yaml":
-            with contextlib.suppress(Exception):
+            try:
                 return cfg2task(eval(x))
+            except:  # noqa E722
+                pass
 
         for m in model.modules():
             if isinstance(m, Segment):