Normalize embeddings matrix row-wise.

    Args:
      ord: normalization order. Possible values {1, 2, 'inf', '-inf'}

def normalize_words(self, ord=2, inplace=False):
    """Normalize embeddings matrix row-wise.

    Args:
      ord: normalization order. Possible values {1, 2, 'inf', '-inf'}
    """
    if ord == 2:
      ord = None # numpy uses this flag to indicate l2.
    vectors = self.vectors.T / np.linalg.norm(self.vectors, ord, axis=1)
    if inplace:
      self.vectors = vectors.T
      return self
    return Embedding(vectors=vectors.T, vocabulary=self.vocabulary)