class_docstr: Permutes the dimensions of a video.
class_docstr_tok: ["Permutes","the","dimensions","of","a","video","."]
docstr: Args:
      dims (Tuple[int]): The desired ordering of dimensions.
docstr_tok: ["Args",":","dims","(","Tuple","[","int","]",")",":","The","desired","ordering","of","dimensions","."]
code: def __init__(self, dims: Tuple[int]):
      """
      Args:
          dims (Tuple[int]): The desired ordering of dimensions.
      """
      assert (
          (d in dims) for d in range(len(dims))
      ), "dims must contain every dimension (0, 1, 2, ...)"
  
      super().__init__()
      self._dims = dims
  
imports: from typing import Callable, Dict, List, Optional, Tuple
  import pytorchvideo.transforms.functional
  import torch
  import torchvision.transforms
label_desc: Use image node_id 1 to create a new Permute object from inherited base classes: torch.nn with example: obj = Permute(dims)