code: def __iter__(self):
      random_starts = self.rng.randint(
          0,
          self.whole_seq.shape[0] - self.seq_length - 1,
          (self._size,),
      )
      for st in random_starts:
          seq = self.whole_seq[st : st + self.seq_length + 1]
          yield [seq[:-1], seq[1:]]
  
imports: import argparse
  import numpy
  import operator
  import os
  import sys
  from collections import Counter
  import tensorflow
  from tensorpack import *
  from tensorpack.tfutils import optimizer, summary
  from tensorpack.tfutils.gradproc import GlobalNormClip
label_desc: Use image node_id 3 for calling the CharRNNData obj's underlying member method code with example usage: obj.__iter__() without return types