class_docstr: USPS Dataset.
  
  Args:
      root (string): Root directory of dataset where dataset file exist.
      train (bool, optional): If True, resample from dataset randomly.
      download (bool, optional): If true, downloads the dataset
          from the internet and puts it in root directory.
          If dataset is already downloaded, it is not downloaded again.
      transform (callable, optional): A function/transform that takes in
          an PIL image and returns a transformed version.
          E.g, ``transforms.RandomCrop``
docstr: Load sample images from dataset.
docstr_tok: ["Load","sample","images","from","dataset","."]
code: def load_samples(self):
      """Load sample images from dataset."""
      filename = os.path.join(self.root, self.filename)
      f = gzip.open(filename, "rb")
      data_set = pickle.load(f, encoding="bytes")
      f.close()
      if self.train:
          images = data_set[0][0]
          labels = data_set[0][1]
          self.dataset_size = labels.shape[0]
      else:
          images = data_set[1][0]
          labels = data_set[1][1]
          self.dataset_size = labels.shape[0]
      return images, labels
  
file_path: pykale/kale/loaddata/usps.py
imports: import gzip
  import logging
  import os
  import pickle
  import urllib
  import numpy
  import torch
  import torch.utils.data
label_desc: Use image node_id 6 for calling the USPS obj's underlying member method code with example usage: obj.load_samples() and returns: images,  labels