code: def erase(
      inpt: torch.Tensor,
      i: int,
      j: int,
      h: int,
      w: int,
      v: torch.Tensor,
      inplace: bool = False,
  ) -> torch.Tensor:
      """See :class:`~torchvision.transforms.v2.RandomErase` for details."""
      if torch.jit.is_scripting():
          return erase_image(
              inpt, i=i, j=j, h=h, w=w, v=v, inplace=inplace
          )
  
      _log_api_usage_once(erase)
  
      kernel = _get_kernel(erase, type(inpt))
      return kernel(inpt, i=i, j=j, h=h, w=w, v=v, inplace=inplace)
  
file_path: vision/torchvision/transforms/v2/functional/_augment.py
imports: import PIL.Image
  import torch
  from torchvision import tv_tensors
  from torchvision.transforms.functional import pil_to_tensor, to_pil_image
  from torchvision.utils import _log_api_usage_once
  from ._utils import _get_kernel, _register_kernel_internal
label_desc: Use image node_id 1 for calling a global function with example usage: erase(inpt, i, j, h, w, v, inplace) and returns: kernel, erase_image