code: def __next__(self) -> Batch:
      if self.batch_index == self.num_batches:
          raise StopIteration
      if self.num_generated_batches >= 0:
          batch = self._generated_batches[
              self.batch_index % len(self._generated_batches)
          ]
      else:
          batch = self._generate_batch()
      self.batch_index += 1
      return batch
  
file_path: torchrec/torchrec/datasets/random.py
imports: import itertools
  import sys
  from typing import cast, Iterator, List, Optional
  import torch
  from torch.utils.data.dataset import IterableDataset
  from torchrec.datasets.utils import Batch
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
label_desc: Use image node_id 3 for calling the _RandomRecBatch obj's underlying member method code with example usage: obj.__next__() and returns: batch