class_docstr: A class to read TED talk dataset
      
class_docstr_tok: ["A","class","to","read","TED","talk","dataset"]
code: def __init__(
      self,
      corpus_path,
      delimiter="\t",
      target_token=True,
      bilingual=True,
      corpus_type="file",
      lang_dict={"source": ["fr"], "target": ["en"]},
      eval_lang_dict=None,
      zero_shot=False,
      detok=True,
  ):
      self.empty_line_flag = "NULL"
      self.corpus_path = corpus_path
      self.delimiter = delimiter
      self.bilingual = bilingual
      self.lang_dict = lang_dict
      self.lang_set = set()
      self.target_token = target_token
      self.zero_shot = zero_shot
      self.eval_lang_dict = eval_lang_dict
      self.corpus_type = corpus_type
      self.detok = detok
  
      for list_ in self.lang_dict.values():
          for lang in list_:
              self.lang_set.add(lang)
  
      self.data = dict()
      self.data["train"] = self.read_aligned_corpus(split_type="train")
      self.data["test"] = self.read_aligned_corpus(split_type="test")
      self.data["dev"] = self.read_aligned_corpus(split_type="dev")
  
imports: import itertools
  import os
  import csv
  from collections import defaultdict
  from six.moves import zip
  import io
  import wget
  import sys
  from subprocess import check_call, check_output
label_desc: Use image node_id 1 to create a new MultiLingualAlignedCorpusReader object from inherited base classes: object with example: obj = MultiLingualAlignedCorpusReader(corpus_path, delimiter, target_token, bilingual, corpus_type, lang_dict, eval_lang_dict, zero_shot, detok)