    def test_textual_representation_contains_activations(self):
        params = Params(
            {
                "input_dim": 2,
                "hidden_dims": 3,
                "activations": ["linear", "relu", "swish"],
                "num_layers": 3,
            }
        )
        feedforward = FeedForward.from_params(params)
        expected_text_representation = inspect.cleandoc(
            """
            FeedForward(
              (_activations): ModuleList(
                (0): LinearActivation()
                (1): ReLU()
                (2): SwishActivation()
              )
              (_linear_layers): ModuleList(
                (0): Linear(in_features=2, out_features=3, bias=True)
                (1): Linear(in_features=3, out_features=3, bias=True)
                (2): Linear(in_features=3, out_features=3, bias=True)
              )
              (_dropout): ModuleList(
                (0): Dropout(p=0.0, inplace=False)
                (1): Dropout(p=0.0, inplace=False)
                (2): Dropout(p=0.0, inplace=False)
              )
            )
            """
        )
        actual_text_representation = str(feedforward)

        assert actual_text_representation == expected_text_representation
FeedForward(
(_activations): ModuleList(
(0): LinearActivation()
(1): ReLU()
(2): SwishActivation()
)
(_linear_layers): ModuleList(
(0): Linear(in_features=2, out_features=3, bias=True)
(1): Linear(in_features=3, out_features=3, bias=True)
(2): Linear(in_features=3, out_features=3, bias=True)
)
(_dropout): ModuleList(
(0): Dropout(p=0.0, inplace=False)
(1): Dropout(p=0.0, inplace=False)
(2): Dropout(p=0.0, inplace=False)
)
)
tests/modules/feedforward_test.py