def train(hparams, *args):
    """Train your awesome model.

    :param hparams: The arguments to run the model with.
    """
    # Initialize experiments and track all the hyperparameters
    exp = Experiment(
        name=hparams.test_tube_exp_name,
        # Location to save the metrics.
        save_dir=hparams.log_path,
        autosave=False,
    )
    exp.argparse(hparams)

    # Pretend to train.
    x = torch.rand((1, hparams.x_val))
    for train_step in range(0, 100):
        y = torch.rand((hparams.x_val, 1))
        out = x.mm(y)
        exp.log({'fake_err': out.item()})

    # Save exp when .
    exp.save()