def METHOD_NAME(self) -> None:
    attribution = torch.tensor([0.1, 0.2, 0.3, 0.4])
    input_data = torch.rand(1, 2)
    expected_modified = [100 * x for x in (attribution / attribution.max())]
    contribution_frac = torch.rand(1).item()
    feature = TextFeature(
        name=self.FEATURE_NAME,
        baseline_transforms=None,
        input_transforms=None,
        visualization_transform=None,
    )
    feature_output = feature.visualize(attribution, input_data, contribution_frac)
    expected_feature_output = FeatureOutput(
        name=self.FEATURE_NAME,
        base=input_data,
        modified=expected_modified,
        type="text",
        contribution=contribution_frac,
    )
    self.assertEqual(expected_feature_output, feature_output)