class_docstr: Reads data in the "machine-readable derivation" format of the CCGbank dataset.
  (see https://catalog.ldc.upenn.edu/docs/LDC2005T13/CCGbankManual.pdf, section D.2)
  
  In particular, it pulls out the leaf nodes, which are represented as
  
      (<L ccg_category modified_pos original_pos token predicate_arg_category>)
  
  The tarballed version of the dataset contains many files worth of this data,
  in files /data/AUTO/xx/wsj_xxxx.auto
  
  This dataset reader expects a single text file. Accordingly, if you're using that dataset,
  you'll need to first concatenate some of those files into a training set, a validation set,
  and a test set.
  
  Parameters
  ----------
  token_indexers : ``Dict[str, TokenIndexer]``, optional (default=``{"tokens": SingleIdTokenIndexer()}``)
      We use this to define the input representation for the text.  See :class:`TokenIndexer`.
      Note that the `output` tags will always correspond to single token IDs based on how they
      are pre-tokenised in the data file.
  lazy : ``bool``, optional, (default = ``False``)
      Whether or not instances can be consumed lazily.
class_docstr_tok: ["Reads","data","in","the","``","machine-readable","derivation","''","format","of","the","CCGbank","dataset",".","(","see","https",":","\/\/catalog.ldc.upenn.edu\/docs\/LDC2005T13\/CCGbankManual.pdf",",","section","D.2",")","In","particular",",","it","pulls","out","the","leaf","nodes",",","which","are","represented","as","(","<","L","ccg_category","modified_pos","original_pos","token","predicate_arg_category",">",")","The","tarballed","version","of","the","dataset","contains","many","files","worth","of","this","data",",","in","files","\/data\/AUTO\/xx\/wsj_xxxx.auto","This","dataset","reader","expects","a","single","text","file",".","Accordingly",",","if","you","'re","using","that","dataset",",","you","'ll","need","to","first","concatenate","some","of","those","files","into","a","training","set",",","a","validation","set",",","and","a","test","set",".","Parameters","--","--","--","--","--","token_indexers",":","``","Dict","[","str",",","TokenIndexer","]","``",",","optional","(","default=","``","{","``","tokens","''",":","SingleIdTokenIndexer","(",")","}","``",")","We","use","this","to","define","the","input","representation","for","the","text",".","See",":","class",":","`","TokenIndexer","`",".","Note","that","the","`","output","`","tags","will","always","correspond","to","single","token","IDs","based","on","how","they","are","pre-tokenised","in","the","data","file",".","lazy",":","``","bool","``",",","optional",",","(","default","=","``","False","``",")","Whether","or","not","instances","can","be","consumed","lazily","."]
code: def __init__(self, token_indexers=None, lazy=False):
      super(CcgBankDatasetReader, self).__init__(lazy=lazy)
      self._token_indexers = token_indexers or {
          "tokens": SingleIdTokenIndexer()
      }
  
file_path: magnitude/pymagnitude/third_party/allennlp/data/dataset_readers/ccgbank.py
imports: from __future__ import with_statement
  from __future__ import absolute_import
  import logging
  import re
  from allennlp.common.file_utils import cached_path
  from allennlp.data.dataset_readers.dataset_reader import DatasetReader
  from allennlp.data.fields import Field, TextField, SequenceLabelField
  from allennlp.data.instance import Instance
  from allennlp.data.token_indexers import TokenIndexer, SingleIdTokenIndexer
  from allennlp.data.tokenizers import Token
  from io import open
label_desc: Use image node_id 1 to create a new CcgBankDatasetReader object from inherited base classes: DatasetReader with example: obj = CcgBankDatasetReader(token_indexers, lazy)