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