7bc27fac82840ceb07b1afc76254b46840efedfe,tests/layers_tests.py,L1LossMaskedTests,test_in_out,#L1LossMaskedTests#,63

Before Change

        layer = L1LossMasked()
        dummy_input = T.autograd.Variable(T.ones(4, 8, 128).float())
        dummy_target = T.autograd.Variable(T.ones(4, 8, 128).float())
        dummy_length = T.autograd.Variable((T.ones(4) * 8).long())
        output = layer(dummy_input, dummy_target, dummy_length)
        assert output.shape[0] == 0
        assert len(output.shape) == 1
        assert output.data[0] == 0.0

        dummy_input = T.autograd.Variable(T.ones(4, 8, 128).float())
        dummy_target = T.autograd.Variable(T.zeros(4, 8, 128).float())
        dummy_length = T.autograd.Variable((T.ones(4) * 8).long())
        output = layer(dummy_input, dummy_target, dummy_length)
        assert output.data[0] == 1.0, "1.0 vs {}".format(output.data[0])

        dummy_input = T.autograd.Variable(T.ones(4, 8, 128).float())
        dummy_target = T.autograd.Variable(T.zeros(4, 8, 128).float())
        dummy_length = T.autograd.Variable((T.arange(5, 9)).long())
        mask = ((_sequence_mask(dummy_length).float() - 1.0)
                * 100.0).unsqueeze(2)
        output = layer(dummy_input + mask, dummy_target, dummy_length)

After Change

        layer = L1LossMasked()
        dummy_input = T.ones(4, 8, 128).float()
        dummy_target = T.ones(4, 8, 128).float()
        dummy_length = (T.ones(4) * 8).long()
        output = layer(dummy_input, dummy_target, dummy_length)
        assert output.item() == 0.0

        dummy_input = T.ones(4, 8, 128).float()

Instances