docstr: Get a batch with index. 
docstr_tok: ["Get","a","batch","with","index","."]
code: def __getitem__(self, key):
      """Get a batch with index."""
      if not isinstance(key, int):
          raise TypeError
      if key < 0 or key >= len(self.data):
          raise IndexError
      batch = self.data[key]
      batch_size = len(batch)
      batch = list(zip(*batch))
      assert len(batch) == 10
  
      # sort sentences by lens for easy RNN operations
      lens = [len(x) for x in batch[0]]
      batch, orig_idx = sort_all(batch, lens)
  
      # sort words by lens for easy char-RNN operations
      batch_words = [w for sent in batch[1] for w in sent]
      word_lens = [len(x) for x in batch_words]
      batch_words, word_orig_idx = sort_all([batch_words], word_lens)
      batch_words = batch_words[0]
      word_lens = [len(x) for x in batch_words]
  
      # convert to tensors
      words = batch[0]
      words = get_long_tensor(words, batch_size)
      words_mask = torch.eq(words, PAD_ID)
      wordchars = get_long_tensor(batch_words, len(word_lens))
      wordchars_mask = torch.eq(wordchars, PAD_ID)
  
      upos = get_long_tensor(batch[2], batch_size)
      xpos = get_long_tensor(batch[3], batch_size)
      ufeats = get_long_tensor(batch[4], batch_size)
      pretrained = get_long_tensor(batch[5], batch_size)
      sentlens = [len(x) for x in batch[0]]
      lemma = get_long_tensor(batch[6], batch_size)
      head = get_long_tensor(batch[7], batch_size)
      deprel = get_long_tensor(batch[8], batch_size)
      text = batch[9]
      return (
          words,
          words_mask,
          wordchars,
          wordchars_mask,
          upos,
          xpos,
          ufeats,
          pretrained,
          lemma,
          head,
          deprel,
          orig_idx,
          word_orig_idx,
          sentlens,
          word_lens,
          text,
      )
  
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 5 for calling the DataLoader obj's underlying member method code with example usage: obj.__getitem__(key) and returns: words,  words_mask,  wordchars,  wordchars_mask,  upos,  xpos,  ufeats,  pretrained,  lemma,  head,  deprel,  orig_idx,  word_orig_idx,  sentlens,  word_lens,  text