class_docstr: ``nn.Module`` wrapper for ``pytorchvideo.transforms.functional.uniform_crop``.
class_docstr_tok: ["``","nn.Module","``","wrapper","for","``","pytorchvideo.transforms.functional.uniform_crop","``","."]
docstr: Args:
      x (Dict[str, torch.Tensor]): video clip dict.
docstr_tok: ["Args",":","x","(","Dict","[","str",",","torch.Tensor","]",")",":","video","clip","dict","."]
code: def __call__(
      self, x: Dict[str, torch.Tensor]
  ) -> Dict[str, torch.Tensor]:
      """
      Args:
          x (Dict[str, torch.Tensor]): video clip dict.
      """
      x[
          self._video_key
      ] = pytorchvideo.transforms.functional.uniform_crop(
          x[self._video_key], self._size, x[self._aug_index_key]
      )
      return x
  
imports: from typing import Callable, Dict, List, Optional, Tuple
  import pytorchvideo.transforms.functional
  import torch
  import torchvision.transforms
label_desc: Use image node_id 2 for calling the UniformCropVideo obj's underlying member method code with example usage: obj.__call__(x) and returns: x