class_docstr: The attribute summarizer for the hybrid 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 hybrid model uses
          bidirectional GRU(a specific type of RNN) to take into account the context
          information. The default value is 'gru'.
      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 hybrid model performs word by word comparison
          over the raw input word embeddings (rather than the RNN hiddens states), hence
          this defaults to an Attention object with 'decomposable' as the attention
          mechanism on the raw input embeddings.
      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. A second layer of attention has been used for the
          aggregation. Please consult the paper for more information. The default value
          is 'concat-attention-with-rnn'.
      hidden_size (int): The hidden size to use for all 3 attribute summarization
          sub-modules (i.e., word contextualizer, word comparator, and word aggregator),
          if they are customized.
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code: def _init(
      self,
      word_contextualizer=None,
      word_comparator=None,
      word_aggregator=None,
      hidden_size=None,
  ):
      word_contextualizer = word_contextualizer or "gru"
      word_comparator = (
          word_comparator
          or dm.word_comparators.Attention(
              alignment_network="decomposable", raw_alignment=True
          )
      )
      word_aggregator = word_aggregator or "attention-with-rnn"
      super(Hybrid, 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 Hybrid obj's underlying member method code with example usage: obj._init(word_contextualizer, word_comparator, word_aggregator, hidden_size) without return types