class_docstr: MatchingHistogramUnit Class.
  
  :param bin_size: The number of bins of the matching histogram.
  :param embedding_matrix: The word embedding matrix applied to calculate
                           the matching histogram.
  :param normalize: Boolean, normalize the embedding or not.
  :param mode: The type of the historgram, it should be one of 'CH', 'NG',
               or 'LCH'.
  
  Examples:
      >>> embedding_matrix = np.array([[1.0, -1.0], [1.0, 2.0], [1.0, 3.0]])
      >>> text_left = [0, 1]
      >>> text_right = [1, 2]
      >>> histogram = MatchingHistogram(3, embedding_matrix, True, 'CH')
      >>> histogram.transform([text_left, text_right])
      [[3.0, 1.0, 1.0], [1.0, 2.0, 2.0]]
docstr: Normalize the embedding matrix.
docstr_tok: ["Normalize","the","embedding","matrix","."]
code: def _normalize_embedding(self):
      """Normalize the embedding matrix."""
      l2_norm = np.sqrt(
          (self._embedding_matrix * self._embedding_matrix).sum(axis=1)
      )
      self._embedding_matrix = (
          self._embedding_matrix / l2_norm[:, np.newaxis]
      )
  
imports: import numpy
  from .unit import Unit
label_desc: Use image node_id 2 for calling the MatchingHistogram obj's underlying member method code with example usage: obj._normalize_embedding() without return types