def test_tuner_lr_find(tmp_path, use_hparams):
    """Test that lr_find updates the learning rate attribute."""
    seed_everything(1)

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

        def configure_optimizers(self):
            return torch.optim.SGD(self.parameters(), lr=self.hparams.lr if use_hparams else self.lr)

    before_lr = 1e-2
    model = CustomBoringModel(lr=before_lr)
    trainer = Trainer(default_root_dir=tmp_path, max_epochs=2)
    tuner = Tuner(trainer)
    tuner.lr_find(model, update_attr=True)

    after_lr = model.hparams.lr if use_hparams else model.lr

    assert after_lr is not None
    assert before_lr != after_lr, "Learning rate was not altered after running learning rate finder"
Test that lr_find updates the learning rate attribute.
tests/tests_pytorch/tuner/test_lr_finder.py