class_docstr: The attribute summarizer for the attention-based model.
  
  Args:
      word_contextualizer (string or :class:`~deepmatcher.WordContextualizer` or callable): The
          word contextualizer module (refer to :class:`~deepmatcher.WordContextualizer` for
          details) to use for attribute summarization. The attention model does not take
          word context information into account, hence this defaults to None.
      word_comparator (string or :class:`~deepmatcher.WordComparator` or callable): The word
          comparator module (refer to :class:`~deepmatcher.WordComparator` for details) to use
          for attribute summarization. The attention model performs word by word
          comparison with the decomposable attention mechanism, hence this defaults to
          'decomposable-attention'.
      word_aggregator (string or :class:`~deepmatcher.WordAggregator` or callable): The word
          aggregator module (refer to :class:`~deepmatcher.WordAggregator` for details) to use
          for attribute summarization. The Attention model performs the aggregation by
          summing over the comparison results from the word comparator, divided by the
          length of the input sequence (to get constant variance through the network
          flow). Hence this defaults to 'divsqrt-pool'.
      hidden_size (int): The hidden size to use for the word comparator. This value
          will also be used as the hidden size for the other 2 attribute summarization
          sub-modules (i.e., word contextualizer, and word aggregator), if they are
          customized. If not specified, the hidden size for each component will be set
          to be the same as its input size. E.g. if the word embedding dimension is 300
          and hidden_size is None, the word contextualizer's hidden size will be 300.
class_docstr_tok: ["The","attribute","summarizer","for","the","attention-based","model",".","Args",":","word_contextualizer","(","string","or",":","class",":","`","~deepmatcher.WordContextualizer","`","or","callable",")",":","The","word","contextualizer","module","(","refer","to",":","class",":","`","~deepmatcher.WordContextualizer","`","for","details",")","to","use","for","attribute","summarization",".","The","attention","model","does","not","take","word","context","information","into","account",",","hence","this","defaults","to","None",".","word_comparator","(","string","or",":","class",":","`","~deepmatcher.WordComparator","`","or","callable",")",":","The","word","comparator","module","(","refer","to",":","class",":","`","~deepmatcher.WordComparator","`","for","details",")","to","use","for","attribute","summarization",".","The","attention","model","performs","word","by","word","comparison","with","the","decomposable","attention","mechanism",",","hence","this","defaults","to","'decomposable-attention","'",".","word_aggregator","(","string","or",":","class",":","`","~deepmatcher.WordAggregator","`","or","callable",")",":","The","word","aggregator","module","(","refer","to",":","class",":","`","~deepmatcher.WordAggregator","`","for","details",")","to","use","for","attribute","summarization",".","The","Attention","model","performs","the","aggregation","by","summing","over","the","comparison","results","from","the","word","comparator",",","divided","by","the","length","of","the","input","sequence","(","to","get","constant","variance","through","the","network","flow",")",".","Hence","this","defaults","to","'divsqrt-pool","'",".","hidden_size","(","int",")",":","The","hidden","size","to","use","for","the","word","comparator",".","This","value","will","also","be","used","as","the","hidden","size","for","the","other","2","attribute","summarization","sub-modules","(","i.e.",",","word","contextualizer",",","and","word","aggregator",")",",","if","they","are","customized",".","If","not","specified",",","the","hidden","size","for","each","component","will","be","set","to","be","the","same","as","its","input","size",".","E.g",".","if","the","word","embedding","dimension","is","300","and","hidden_size","is","None",",","the","word","contextualizer","'s","hidden","size","will","be","300","."]
code: def _init(
      self,
      word_contextualizer=None,
      word_comparator=None,
      word_aggregator=None,
      hidden_size=None,
  ):
      word_comparator = word_comparator or "decomposable-attention"
      word_aggregator = word_aggregator or "divsqrt-pool"
      super(Attention, self)._init(
          word_contextualizer=word_contextualizer,
          word_comparator=word_comparator,
          word_aggregator=word_aggregator,
          hidden_size=hidden_size,
      )
  
file_path: deepmatcher/deepmatcher/models/attr_summarizers.py
imports: import deepmatcher
label_desc: Use image node_id 1 for calling the Attention obj's underlying member method code with example usage: obj._init(word_contextualizer, word_comparator, word_aggregator, hidden_size) without return types