class_docstr: Version of fairseq.data.LanguagePairDataset which represents source
  and target sentences as sequences of words, each represented as a
  sequence of characters (with numberized indices for both words and
  characters).
  Right-padded only.
code: def __getitem__(self, i):
      example = self.get_src_maybe_with_weights(i)
      if self.tgt:
          example["target"] = self.tgt.get_tokens(i).long()
          example["target_chars_list"] = self.tgt.get_chars_list(i)
  
      return example
  
imports: from typing import Any, Dict
  import numpy
  import torch
  from fairseq import data, tokenizer
  from fvcore.common.file_io import PathManager
  from pytorch_translate import vocab_constants
  from pytorch_translate.data.dictionary import TAGS
label_desc: Use image node_id 2 for calling the LanguagePairCharDataset obj's underlying member method code with example usage: obj.__getitem__(i) and returns: example