class_docstr: Computes attention between every entry in matrix_1 with every entry in matrix_2 using a dot
  product.
class_docstr_tok: ["Computes","attention","between","every","entry","in","matrix_1","with","every","entry","in","matrix_2","using","a","dot","product","."]
code: def forward(self, matrix_1, matrix_2):
      return matrix_1.bmm(matrix_2.transpose(2, 1))
  
imports: from __future__ import absolute_import
  import torch
  from allennlp.modules.matrix_attention.matrix_attention import MatrixAttention
label_desc: Use image node_id 1 for calling the DotProductMatrixAttention obj's underlying member method code with example usage: obj.forward(matrix_1, matrix_2) and returns: matrix_1