def test_suggestion_parameters_work(tmp_path):
    """Test that default skipping does not alter results in basic case."""
    seed_everything(1)

    class CustomBoringModel(BoringModel):
        def __init__(self, lr):
            super().__init__()
            self.lr = lr

        def configure_optimizers(self):
            return torch.optim.SGD(self.parameters(), lr=self.lr)

    # logger file to get meta
    model = CustomBoringModel(lr=1e-2)
    trainer = Trainer(default_root_dir=tmp_path, max_epochs=3)
    tuner = Tuner(trainer)
    lr_finder = tuner.lr_find(model)
    lr1 = lr_finder.suggestion(skip_begin=10)  # default
    lr2 = lr_finder.suggestion(skip_begin=70)  # way too high, should have an impact

    assert lr1 is not None
    assert lr2 is not None
    assert lr1 != lr2, "Skipping parameter did not influence learning rate"
Test that default skipping does not alter results in basic case.
tests/tests_pytorch/tuner/test_lr_finder.py