class_docstr: ``nn.Module`` wrapper for
  ``pytorchvideo.transforms.functional.uniform_temporal_subsample_repeated``.
class_docstr_tok: ["``","nn.Module","``","wrapper","for","``","pytorchvideo.transforms.functional.uniform_temporal_subsample_repeated","``","."]
code: def __init__(self, frame_ratios: Tuple[int], temporal_dim: int = -3):
      super().__init__()
      self._frame_ratios = frame_ratios
      self._temporal_dim = temporal_dim
  
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 UniformTemporalSubsampleRepeated object from inherited base classes: torch.nn with example: obj = UniformTemporalSubsampleRepeated(frame_ratios, temporal_dim)