class_docstr: This similarity function simply computes the dot product between each pair of vectors, with an
  optional scaling to reduce the variance of the output elements.
  
  Parameters
  ----------
  scale_output : ``bool``, optional
      If ``True``, we will scale the output by ``math.sqrt(tensor.size(-1))``, to reduce the
      variance in the result.
code: def __init__(self, scale_output=False):
      super(DotProductSimilarity, self).__init__()
      self._scale_output = scale_output
  
file_path: magnitude/pymagnitude/third_party/allennlp/modules/similarity_functions/dot_product.py
imports: from __future__ import absolute_import
  import math
  import torch
  from allennlp.modules.similarity_functions.similarity_function import SimilarityFunction
label_desc: Use image node_id 1 to create a new DotProductSimilarity object from inherited base classes: SimilarityFunction with example: obj = DotProductSimilarity(scale_output)