code: def forward(
      self, image: Tensor, target: Optional[Dict[str, Tensor]] = None
  ) -> Tuple[Tensor, Optional[Dict[str, Tensor]]]:
      if isinstance(image, torch.Tensor):
          if image.ndimension() not in {2, 3}:
              raise ValueError(
                  f"image should be 2/3 dimensional. Got {image.ndimension()} dimensions."
              )
          elif image.ndimension() == 2:
              image = image.unsqueeze(0)
  
      if torch.rand(1) >= self.p:
          return image, target
  
      orig_w, orig_h = F.get_image_size(image)
  
      r = self.side_range[0] + torch.rand(1) * (
          self.side_range[1] - self.side_range[0]
      )
      canvas_width = int(orig_w * r)
      canvas_height = int(orig_h * r)
  
      r = torch.rand(2)
      left = int((canvas_width - orig_w) * r[0])
      top = int((canvas_height - orig_h) * r[1])
      right = canvas_width - (left + orig_w)
      bottom = canvas_height - (top + orig_h)
  
      if torch.jit.is_scripting():
          fill = 0
      else:
          fill = self._get_fill_value(F._is_pil_image(image))
  
      image = F.pad(image, [left, top, right, bottom], fill=fill)
      if isinstance(image, torch.Tensor):
          # PyTorch's pad supports only integers on fill. So we need to overwrite the colour
          v = torch.tensor(
              self.fill, device=image.device, dtype=image.dtype
          ).view(-1, 1, 1)
          image[..., :top, :] = image[..., :, :left] = image[
              ..., (top + orig_h) :, :
          ] = image[..., :, (left + orig_w) :] = v
  
      if target is not None:
          target["boxes"][:, 0::2] += left
          target["boxes"][:, 1::2] += top
  
      return image, target
  
imports: from typing import List, Tuple, Dict, Optional
  import torch
  import torchvision
  from torch import nn, Tensor
  from torchvision.transforms import functional
  from torchvision.transforms import transforms
label_desc: Use image node_id 3 for calling the RandomZoomOut obj's underlying member method code with example usage: obj.forward(image, target) and returns: image,  target, image,  target