class_docstr: __init__()
  
  The Word Aggregator.
  
  Takes a sequence of vectors and aggregates it into a single vector.
  `Refer this tutorial <https://nbviewer.jupyter.org/github/sidharthms/deepmatcher/blob/master/examples/matching_models.ipynb#2.1.3.-Word-Aggregator>`__
  for details. Sub-classes that implement various options for this module are defined in
  :mod:`deepmatcher.word_aggregators`.
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docstr: Create a word aggregator object.
  
  Args:
      arg (string or :mod:`deepmatcher.word_aggregators` or callable):
          Same as the `word_aggregator` argument to the constructor of
          :class:`AttrSummarizer`.
  **kwargs:
      Keyword arguments to the constructor of the WordAggregator sub-class.
      For details on what these can be, please refer to the documentation of the
      sub-classes in :mod:`deepmatcher.word_aggregators`.
code: def _create(cls, arg, **kwargs):
      r"""
      Create a word aggregator object.
  
      Args:
          arg (string or :mod:`deepmatcher.word_aggregators` or callable):
              Same as the `word_aggregator` argument to the constructor of
              :class:`AttrSummarizer`.
      **kwargs:
          Keyword arguments to the constructor of the WordAggregator sub-class.
          For details on what these can be, please refer to the documentation of the
          sub-classes in :mod:`deepmatcher.word_aggregators`.
      """
      assert arg is not None
      if isinstance(arg, six.string_types):
          parts = arg.split("-")
          if parts[
              -1
          ] == "pool" and dm.word_aggregators.Pool.supports_style(
              "-".join(parts[:-1])
          ):
              seq = []
              seq.append(
                  dm.modules.Lambda(lambda x1, x2: x1)
              )  # Ignore the context.
              seq.append(
                  dm.word_aggregators.Pool(style="-".join(parts[:-1]))
              )
  
              # Make lazy module.
              wa = dm.modules.LazyModuleFn(
                  lambda: dm.modules.MultiSequential(*seq)
              )
          elif arg == "attention-with-rnn":
              wa = dm.word_aggregators.AttentionWithRNN(**kwargs)
          else:
              raise ValueError("Unknown Word Aggregator name.")
      else:
          wa = _utils.get_module(WordAggregator, arg)
  
      wa.expect_signature("[AxBxC] -> [AxD]")
      return wa
  
imports: import copy
  import logging
  from collections import Mapping
  import dill
  import six
  import deepmatcher
  import torch
  import torch.nn
  from .None import _utils
  from ..data import MatchingDataset, MatchingIterator
  from ..runner import Runner
  from ..utils import Bunch, tally_parameters
label_desc: Use image node_id 1 for calling the WordAggregator obj's underlying member method code with example usage: obj._create(cls, arg) and returns: wa