code: def _transform(
      self, inpt: Any, params: Dict[str, Any]
  ) -> torch.Tensor:
      dims = self.dims[type(inpt)]
      if dims is None:
          return inpt.as_subclass(torch.Tensor)
      return inpt.transpose(*dims)
  
file_path: vision/torchvision/prototype/transforms/_misc.py
imports: import functools
  import warnings
  from collections import defaultdict
  from typing import Any, Dict, Optional, Sequence, Tuple, Type, TypeVar, Union
  import torch
  from torchvision import tv_tensors
  from torchvision.transforms.v2 import Transform
  from torchvision.transforms.v2._utils import is_pure_tensor
label_desc: Use image node_id 2 for calling the TransposeDimensions obj's underlying member method code with example usage: obj._transform(inpt, params) and returns: inpt, inpt