class_docstr: Convert a tensor or an ndarray to PIL Image
  
  This transform does not support torchscript.
  
  Converts a torch.*Tensor of shape C x H x W or a numpy ndarray of shape
  H x W x C to a PIL Image while adjusting the value range depending on the ``mode``.
  
  Args:
      mode (`PIL.Image mode`_): color space and pixel depth of input data (optional).
          If ``mode`` is ``None`` (default) there are some assumptions made about the input data:
  
          - If the input has 4 channels, the ``mode`` is assumed to be ``RGBA``.
          - If the input has 3 channels, the ``mode`` is assumed to be ``RGB``.
          - If the input has 2 channels, the ``mode`` is assumed to be ``LA``.
          - If the input has 1 channel, the ``mode`` is determined by the data type (i.e ``int``, ``float``,
            ``short``).
  
  .. _PIL.Image mode: https://pillow.readthedocs.io/en/latest/handbook/concepts.html#concept-modes
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code: def _transform(
      self,
      inpt: Union[torch.Tensor, PIL.Image.Image, np.ndarray],
      params: Dict[str, Any],
  ) -> PIL.Image.Image:
      return F.to_pil_image(inpt, mode=self.mode)
  
file_path: vision/torchvision/transforms/v2/_type_conversion.py
imports: from typing import Any, Dict, Optional, Union
  import numpy
  import PIL.Image
  import torch
  from torchvision import tv_tensors
  from torchvision.transforms.v2 import functional, Transform
  from torchvision.transforms.v2._utils import is_pure_tensor
label_desc: Use image node_id 2 for calling the ToPILImage obj's underlying member method code with example usage: obj._transform(inpt, params) and returns: F