Ultralytics Code Refactor https://ultralytics.com/actions (#13153)

* Refactor code for speed and clarity

* Update dataloaders.py

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

---------

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

models/common.py

@@ -1066,6 +1066,9 @@ class Classify(nn.Module):
     def __init__(
         self, c1, c2, k=1, s=1, p=None, g=1, dropout_p=0.0
     ):  # ch_in, ch_out, kernel, stride, padding, groups, dropout probability
+        """Initializes YOLOv5 classification head with convolution, pooling, and dropout layers for input to output
+        channel transformation.
+        """
         super().__init__()
         c_ = 1280  # efficientnet_b0 size
         self.conv = Conv(c1, c_, k, s, autopad(k, p), g)

models/tf.py

@@ -612,6 +612,7 @@ class TFModel:
         iou_thres=0.45,
         conf_thres=0.25,
     ):
+        """Runs inference on input data, with an option for TensorFlow NMS."""
         y = []  # outputs
         x = inputs
         for m in self.model.layers:
@@ -730,6 +731,7 @@ def run(
     dynamic=False,  # dynamic batch size
 ):
     # PyTorch model
+    """Exports YOLOv5 model from PyTorch to TensorFlow and Keras formats, performing inference for validation."""
     im = torch.zeros((batch_size, 3, *imgsz))  # BCHW image
     model = attempt_load(weights, device=torch.device("cpu"), inplace=True, fuse=False)
     _ = model(im)  # inference