code: def _preprocess_svhn(raw, withlabel, scale, image_dtype, label_dtype):
      images = raw["x"].transpose(3, 2, 0, 1)
      images = images.astype(image_dtype)
      images *= scale / 255.0
  
      labels = raw["y"].astype(label_dtype).flatten()
      # labels go from 1-10, with the digit "0" having label 10.
      # Set "0" to be label 0 to restore expected ordering
      labels[labels == 10] = 0
  
      if withlabel:
          return tuple_dataset.TupleDataset(images, labels)
      else:
          return images
  
file_path: chainer/chainer/datasets/svhn.py
imports: import os
  import numpy
  import chainer
  from chainer.dataset import download
  from chainer.datasets import tuple_dataset
label_desc: Use image node_id 2 for calling a global function with example usage: _preprocess_svhn(raw, withlabel, scale, image_dtype, label_dtype) and returns: tuple_dataset, images