class_docstr: World representation for the Atis SQL domain. This class has a ``SqlTableContext`` which holds the base
  grammars, it then augments this grammar with the entities that are detected from utterances.
  
  Parameters
  ----------
  utterances: ``List[str]``
      A list of utterances in the interaction, the last element in this list is the
      current utterance that we are interested in.
class_docstr_tok: ["World","representation","for","the","Atis","SQL","domain",".","This","class","has","a","``","SqlTableContext","``","which","holds","the","base","grammars",",","it","then","augments","this","grammar","with","the","entities","that","are","detected","from","utterances",".","Parameters","--","--","--","--","--","utterances",":","``","List","[","str","]","``","A","list","of","utterances","in","the","interaction",",","the","last","element","in","this","list","is","the","current","utterance","that","we","are","interested","in","."]
code: def __eq__(self, other):
      if isinstance(self, other.__class__):
          return all(
              [
                  self.valid_actions == other.valid_actions,
                  numpy.array_equal(
                      self.linking_scores, other.linking_scores
                  ),
                  self.utterances == other.utterances,
                  self.grammar_str == other.grammar_str,
              ]
          )
      return False
  
file_path: magnitude/pymagnitude/third_party/allennlp/semparse/worlds/atis_world.py
imports: from __future__ import absolute_import
  from copy import deepcopy
  import numpy
  from parsimonious.grammar import Grammar
  from allennlp.semparse.contexts.atis_tables import *
  from allennlp.semparse.contexts.sql_table_context import SqlTableContext, SqlVisitor, generate_one_of_string, format_action
  from allennlp.data.tokenizers import Token, WordTokenizer
label_desc: Use image node_id 7 for calling the AtisWorld obj's underlying member method code with example usage: obj.__eq__(other) and returns: False, all