code: def test_forward_does_a_bilinear_product(self):
      params = Params({"matrix_1_dim": 2, "matrix_2_dim": 2})
      bilinear = BilinearMatrixAttention.from_params(params)
      bilinear._weight_matrix = Parameter(
          torch.FloatTensor([[-0.3, 0.5], [2.0, -1.0]])
      )
      bilinear._bias = Parameter(torch.FloatTensor([0.1]))
      a_vectors = torch.FloatTensor([[[1, 1], [2, 2]]])
      b_vectors = torch.FloatTensor([[[1, 0], [0, 1]]])
      result = bilinear(a_vectors, b_vectors).detach().numpy()
      assert result.shape == (1, 2, 2)
      assert_almost_equal(result, [[[1.8, -0.4], [3.5, -0.9]]])
  
file_path: allennlp/tests/modules/matrix_attention/bilinear_matrix_attention_test.py
imports: from numpy.testing import assert_almost_equal
  import torch
  from torch.nn.parameter import Parameter
  from allennlp.common import Params
  from allennlp.modules.matrix_attention import BilinearMatrixAttention
  from allennlp.common.testing import AllenNlpTestCase
label_desc: Use image node_id 1 for calling the TestBilinearMatrixAttention obj's underlying member method code with example usage: obj.test_forward_does_a_bilinear_product() without return types