class_docstr: binarize by parsing a set of alignments and packing
  them in a tensor (see utils.parse_alignment)
code: def __init__(
      self,
      alignment_parser: tp.Callable[[str], torch.IntTensor],
  ) -> None:
      super().__init__()
      self.alignment_parser = alignment_parser
  
imports: import logging
  import os
  import typing
  from abc import ABC, abstractmethod
  from collections import Counter
  from dataclasses import dataclass
  from multiprocessing import Pool
  import torch
  from fairseq.data import Dictionary, indexed_dataset
  from fairseq.file_chunker_utils import Chunker, find_offsets
  from fairseq.file_io import PathManager
  from fairseq.tokenizer import tokenize_line
label_desc: Use image node_id 1 to create a new AlignmentDatasetBinarizer object from inherited base classes: Binarizer with example: obj = AlignmentDatasetBinarizer(alignment_parser)