Update tf.py

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

models/tf.py

@@ -1769,8 +1769,7 @@ def run(
     batch_size=1,  # batch size
     dynamic=False,  # dynamic batch size
 ):
-    # PyTorch model
-    """Def run(weights=ROOT / "yolov5s.pt", imgsz=(640, 640), batch_size=1, dynamic=False):"""
+    """
     Exports YOLOv5 model from PyTorch to TensorFlow/Keras formats and performs inference for validation.
 
     Args:
@@ -1793,6 +1792,7 @@ def run(
         - The function will load the PyTorch model, convert it to TensorFlow/Keras formats, and display the model
           summaries. It will also perform a dummy inference to validate the export.
     """
+
     # PyTorch model
     im = torch.zeros((batch_size, 3, *imgsz))  # BCHW image
     model = attempt_load(weights, device=torch.device("cpu"), inplace=True, fuse=False)
@@ -1808,21 +1808,6 @@ def run(
     im = keras.Input(shape=(*imgsz, 3), batch_size=None if dynamic else batch_size)
     keras_model = keras.Model(inputs=im, outputs=tf_model.predict(im))
     keras_model.summary()
-    """
-    im = torch.zeros((batch_size, 3, *imgsz))  # BCHW image
-    model = attempt_load(weights, device=torch.device("cpu"), inplace=True, fuse=False)
-    _ = model(im)  # inference
-    model.info()
-
-    # TensorFlow model
-    im = tf.zeros((batch_size, *imgsz, 3))  # BHWC image
-    tf_model = TFModel(cfg=model.yaml, model=model, nc=model.nc, imgsz=imgsz)
-    _ = tf_model.predict(im)  # inference
-
-    # Keras model
-    im = keras.Input(shape=(*imgsz, 3), batch_size=None if dynamic else batch_size)
-    keras_model = keras.Model(inputs=im, outputs=tf_model.predict(im))
-    keras_model.summary()
 
     LOGGER.info("PyTorch, TensorFlow and Keras models successfully verified.\nUse export.py for TF model export.")