Add pre-commit CI actions (#4982)

* define pre-commit

* add CI code

* configure

* apply pre-commit

* fstring

* apply MD

* pre-commit

* Update torch_utils.py

* Update print strings

* notes

* Cleanup code-format.yml

* Update setup.cfg

* Update .pre-commit-config.yaml

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

utils/torch_utils.py

@@ -123,7 +123,7 @@ def profile(input, ops, n=10, device=None):
                     y = m(x)
                     t[1] = time_sync()
                     try:
-                        _ = (sum([yi.sum() for yi in y]) if isinstance(y, list) else y).sum().backward()
+                        _ = (sum(yi.sum() for yi in y) if isinstance(y, list) else y).sum().backward()
                         t[2] = time_sync()
                     except Exception as e:  # no backward method
                         # print(e)  # for debug
@@ -223,7 +223,7 @@ def model_info(model, verbose=False, img_size=640):
     n_p = sum(x.numel() for x in model.parameters())  # number parameters
     n_g = sum(x.numel() for x in model.parameters() if x.requires_grad)  # number gradients
     if verbose:
-        print('%5s %40s %9s %12s %20s %10s %10s' % ('layer', 'name', 'gradient', 'parameters', 'shape', 'mu', 'sigma'))
+        print(f"{'layer':>5} {'name':>40} {'gradient':>9} {'parameters':>12} {'shape':>20} {'mu':>10} {'sigma':>10}")
         for i, (name, p) in enumerate(model.named_parameters()):
             name = name.replace('module_list.', '')
             print('%5g %40s %9s %12g %20s %10.3g %10.3g' %
@@ -270,7 +270,7 @@ def scale_img(img, ratio=1.0, same_shape=False, gs=32):  # img(16,3,256,416)
         s = (int(h * ratio), int(w * ratio))  # new size
         img = F.interpolate(img, size=s, mode='bilinear', align_corners=False)  # resize
         if not same_shape:  # pad/crop img
-            h, w = [math.ceil(x * ratio / gs) * gs for x in (h, w)]
+            h, w = (math.ceil(x * ratio / gs) * gs for x in (h, w))
         return F.pad(img, [0, w - s[1], 0, h - s[0]], value=0.447)  # value = imagenet mean