code: def __call__(self, sample):
      sample["original"] = functional.to_tensor(sample["original"])
      sample["digit"] = torch.as_tensor(
          np.asarray(sample["digit"]), dtype=torch.int64
      )
      return sample
  
file_path: pyro/examples/cvae/mnist.py
imports: import numpy
  import torch
  from torch.utils.data import DataLoader, Dataset
  from torchvision.transforms import Compose, functional
  from pyro.contrib.examples.util import MNIST
label_desc: Use image node_id 1 for calling the ToTensor obj's underlying member method code with example usage: obj.__call__(sample) and returns: sample