code: def test_gated_sum_can_run_forward(self):
      a = torch.FloatTensor([1, 2, 3, 4, 5])
      b = -a + 0.1
      weight_value = 2
      gate_value = torch.sigmoid(torch.FloatTensor([1]))
      expected = gate_value * a + (1 - gate_value) * b
  
      with torch.no_grad():  # because we want to change the weight
          gated_sum = GatedSum(a.size(-1))
          gated_sum._gate.weight *= 0
          gated_sum._gate.weight += weight_value
          gated_sum._gate.bias *= 0
  
          out = gated_sum(a, b)
          numpy.testing.assert_almost_equal(
              expected.data.numpy(), out.data.numpy(), decimal=5
          )
  
      with pytest.raises(ValueError):
          GatedSum(a.size(-1))(a, b.unsqueeze(0))
  
      with pytest.raises(ValueError):
          GatedSum(100)(a, b)
  
file_path: allennlp/tests/modules/gated_sum_test.py
imports: import pytest
  import torch
  import numpy
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.modules import GatedSum
label_desc: Use image node_id 1 for calling the TestGatedSum obj's underlying member method code with example usage: obj.test_gated_sum_can_run_forward() without return types