class_docstr: A class for sampling training batches with a controlled composition
  of sequences.
class_docstr_tok: ["A","class","for","sampling","training","batches","with","a","controlled","composition","of","sequences","."]
code: def __iter__(self) -> Iterator[List[int]]:
      for batch_idx in range(len(self)):
          batch = self._sample_batch(batch_idx)
          yield batch
  
file_path: pytorch3d/pytorch3d/implicitron/dataset/scene_batch_sampler.py
imports: import warnings
  from collections import Counter
  from dataclasses import dataclass, field
  from typing import Dict, Iterable, Iterator, List, Sequence, Tuple
  import numpy
  from torch.utils.data.sampler import Sampler
  from .dataset_base import DatasetBase
label_desc: Use image node_id 3 for calling the SceneBatchSampler obj's underlying member method code with example usage: obj.__iter__() without return types