code: def __init__(self, path, root, mean, crop_size, random=True):
      self.base = chainer.datasets.LabeledImageDataset(path, root)
      self.mean = mean.astype(np.float32)
      self.crop_size = crop_size
      self.random = random
  
file_path: chainer/chainerx_cc/examples/imagenet_py/image_dataset.py
imports: import random
  import chainer
  import numpy
label_desc: Use image node_id 1 to create a new PreprocessedDataset object from inherited base classes: chainer.dataset with example: obj = PreprocessedDataset(path, root, mean, crop_size, random)