code: def _translate_x(video: torch.Tensor, factor: float, **kwargs):
      """
      Translate the video along the vertical axis.
  
      Args:
          video (torch.Tensor): Video tensor with shape (T, C, H, W).
          factor (float): How much (relative to the image size) to translate along the
              vertical axis.
      """
      _check_fill_arg(kwargs)
      translation_offset = factor * video.size(-1)
      return affine(
          video,
          [1, 0, translation_offset, 0, 1, 0],
          fill=kwargs["fill"],
          interpolation="bilinear",
      )
  
imports: from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import torch
  import torchvision
  from torch import Tensor
  from torchvision.transforms.functional import InterpolationMode
label_desc: Use image node_id 14 for calling a global function with example usage: _translate_x(video, factor) and returns: affine