code: def to_tensor(clip):
      """
      Convert tensor data type from uint8 to float, divide value by 255.0 and
      permute the dimensions of clip tensor
      Args:
          clip (torch.tensor, dtype=torch.uint8): Size is (T, H, W, C)
      Return:
          clip (torch.tensor, dtype=torch.float): Size is (C, T, H, W)
      """
      _is_tensor_video_clip(clip)
      if not clip.dtype == torch.uint8:
          raise TypeError(
              "clip tensor should have data type uint8. Got %s"
              % str(clip.dtype)
          )
      return clip.float().permute(3, 0, 1, 2) / 255.0
  
file_path: vision/torchvision/transforms/_functional_video.py
imports: import warnings
  import torch
label_desc: Use image node_id 6 for calling a global function with example usage: to_tensor(clip) and returns: unknown