class_docstr: Flip the video clip along the horizonal direction with a given probability
  Args:
      p (float): probability of the clip being flipped. Default value is 0.5
class_docstr_tok: ["Flip","the","video","clip","along","the","horizonal","direction","with","a","given","probability","Args",":","p","(","float",")",":","probability","of","the","clip","being","flipped",".","Default","value","is","0.5"]
docstr: Args:
      clip (torch.tensor): Size is (C, T, H, W)
  Return:
      clip (torch.tensor): Size is (C, T, H, W)
docstr_tok: ["Args",":","clip","(","torch.tensor",")",":","Size","is","(","C",",","T",",","H",",","W",")","Return",":","clip","(","torch.tensor",")",":","Size","is","(","C",",","T",",","H",",","W",")"]
code: def __call__(self, clip):
      """
      Args:
          clip (torch.tensor): Size is (C, T, H, W)
      Return:
          clip (torch.tensor): Size is (C, T, H, W)
      """
      if random.random() < self.p:
          clip = F.hflip(clip)
      return clip
  
imports: import numbers
  import random
  from torchvision.transforms import RandomCrop, RandomResizedCrop
  import lavis.processors.functional_video
label_desc: Use image node_id 2 for calling the RandomHorizontalFlipVideo obj's underlying member method code with example usage: obj.__call__(clip) and returns: clip