def __init__()

in grok/training.py [0:0]


    def __init__(self, hparams: Namespace) -> None:
        """
        :param hparams: An argparse.Namespace with parameters defined in
                        self.add_model_specific_args().
        """
        super().__init__()
        self.hparams = hparams  # type: ignore
        self.prepare_data()

        self.transformer = Transformer(
            hparams.n_layers,
            hparams.n_heads,
            hparams.d_model,
            hparams.dropout,
            hparams.max_context_len,
            len(self.train_dataset.tokenizer),
            hparams.non_linearity,
            weight_noise=self.hparams.weight_noise,
        )

        self.margin = torch.Tensor([0])
        self.next_epoch_to_eval = -1
        self.next_train_epoch_to_log = 0