code: def test_forward_does_a_weighted_product(self):
      linear = LinearSimilarity(3, 1, combination="x,y")
      linear._weight_vector = Parameter(
          torch.FloatTensor([-0.3, 0.5, 2.0, -1.0])
      )
      linear._bias = Parameter(torch.FloatTensor([0.1]))
      a_vectors = torch.FloatTensor([[[1, 1, 1], [-1, -1, 0]]])
      b_vectors = torch.FloatTensor([[[0], [1]]])
      result = linear(a_vectors, b_vectors).data.numpy()
      assert result.shape == (
          1,
          2,
      )
      assert_almost_equal(result, [[2.3, -1.1]])
  
file_path: magnitude/pymagnitude/third_party/allennlp/tests/modules/similarity_functions/linear_test.py
imports: from __future__ import absolute_import
  import numpy
  from numpy.testing import assert_almost_equal
  import torch
  from torch.nn.parameter import Parameter
  from allennlp.common import Params
  from allennlp.modules.similarity_functions import LinearSimilarity
  from allennlp.common.testing import AllenNlpTestCase
label_desc: Use image node_id 2 for calling the TestLinearSimilarityFunction obj's underlying member method code with example usage: obj.test_forward_does_a_weighted_product() without return types