def METHOD_NAME():
    return dict(
        seq_encoder=RnnSeqEncoder(
            trx_encoder=TrxEncoder(
                norm_embeddings=False,
                embeddings_noise=0.1,
                embeddings={
                    'mcc_code': {'in': 21, 'out': 3},
                    'trans_type': {'in': 11, 'out': 2},
                },
                numeric_values={'amount': 'log'},
            ),
            hidden_size=16,
            type='gru',
        ),
        optimizer_partial=partial(torch.optim.Adam, lr=0.004),
        lr_scheduler_partial=partial(torch.optim.lr_scheduler.StepLR, step_size=10, gamma=0.8),
    )