code: def __init__(
      self,
      tokenizer: Any,
      dataset: Any,
      tokens_in_batch: int = 1024,
      clean: bool = False,
      cache_ids: bool = False,
      max_seq_length: int = 512,
      min_seq_length: int = 1,
  ):
      self.tokenizer = tokenizer
      self.tokens_in_batch = tokens_in_batch
  
      ids = dataset_to_ids(dataset, tokenizer, cache_ids=cache_ids)
      if clean:
          ids = self.clean(
              ids, max_tokens=max_seq_length, min_tokens=min_seq_length
          )
      (
          self.batch_sent_ids,
          self.batch_elem_lengths,
      ) = self.pack_data_into_batches(ids)
      self.batches = self.pad_batches(ids)
  
imports: import io
  import json
  import logging
  import pickle
  from collections import OrderedDict
  from typing import Any
  import braceexpand
  import numpy
  import webdataset
  from torch.utils.data import IterableDataset
  from nemo.collections.nlp.data.data_utils.data_preprocessing import dataset_to_ids
  from nemo.core import Dataset
label_desc: Use image node_id 1 to create a new SentenceDataset object from inherited base classes: Dataset with example: obj = SentenceDataset(tokenizer, dataset, tokens_in_batch, clean, cache_ids, max_seq_length, min_seq_length)