code: def chunk_batches(self, data):
      batches, data_orig_idx = data_to_batches(
          data=data,
          batch_size=self.batch_size,
          eval_mode=self.eval,
          sort_during_eval=self.sort_during_eval,
          min_length_to_batch_separately=self.min_length_to_batch_separately,
      )
      # data_orig_idx might be None at train time, since we don't anticipate unsorting
      self.data_orig_idx = data_orig_idx
      return batches
  
imports: import random
  import logging
  import torch
  from stanza.models.common.bert_embedding import filter_data
  from stanza.models.common.data import map_to_ids, get_long_tensor, get_float_tensor, sort_all
  from stanza.models.common.vocab import PAD_ID, VOCAB_PREFIX, ROOT_ID, CompositeVocab, CharVocab
  from stanza.models.pos.vocab import WordVocab, XPOSVocab, FeatureVocab, MultiVocab
  from stanza.models.pos.xpos_vocab_factory import xpos_vocab_factory
  from stanza.models.common.doc import *
label_desc: Use image node_id 10 for calling the DataLoader obj's underlying member method code with example usage: obj.chunk_batches(data) and returns: batches