class_docstr: A fake dataset that returns randomly generated images and returns them as PIL images
  
  Args:
      size (int, optional): Size of the dataset. Default: 1000 images
      image_size(tuple, optional): Size if the returned images. Default: (3, 224, 224)
      num_classes(int, optional): Number of classes in the dataset. Default: 10
      transform (callable, optional): A function/transform that takes in a PIL image
          and returns a transformed version. E.g, ``transforms.RandomCrop``
      target_transform (callable, optional): A function/transform that takes in the
          target and transforms it.
      random_offset (int): Offsets the index-based random seed used to
          generate each image. Default: 0
docstr: Args:
      index (int): Index
  
  Returns:
      tuple: (image, target) where target is class_index of the target class.
code: def __getitem__(self, index: int) -> Tuple[Any, Any]:
      """
      Args:
          index (int): Index
  
      Returns:
          tuple: (image, target) where target is class_index of the target class.
      """
      # create random image that is consistent with the index id
      if index >= len(self):
          raise IndexError(
              f"{self.__class__.__name__} index out of range"
          )
      rng_state = torch.get_rng_state()
      torch.manual_seed(index + self.random_offset)
      img = torch.randn(*self.image_size)
      target = torch.randint(
          0, self.num_classes, size=(1,), dtype=torch.long
      )[0]
      torch.set_rng_state(rng_state)
  
      # convert to PIL Image
      img = transforms.ToPILImage()(img)
      if self.transform is not None:
          img = self.transform(img)
      if self.target_transform is not None:
          target = self.target_transform(target)
  
      return img, target.item()
  
file_path: vision/torchvision/datasets/fakedata.py
imports: from typing import Any, Callable, Optional, Tuple
  import torch
  from ..None import transforms
  from .vision import VisionDataset
label_desc: Use image node_id 2 for calling the FakeData obj's underlying member method code with example usage: obj.__getitem__(index) and returns: img,  target