sccross.models.sccross.SCCROSSModel.compile

SCCROSSModel.compile(lam_data=1.0, lam_kl=1.0, lam_graph=0.02, lam_align=0.05, lam_sup=0.02, normalize_u=False, domain_weight=None, lr=0.001, **kwargs)[source]

Prepare model for training

Parameters

  • lam_data (float) – Data weight

  • lam_kl (float) – KL weight

  • lam_graph (float) – Graph weight

  • lam_align (float) – Adversarial alignment weight

  • lam_sup (float) – Cell type supervision weight

  • normalize_u (bool) – Whether to L2 normalize cell embeddings before decoder

  • domain_weight (Optional[Mapping[str, float]]) – Relative domain weight (indexed by domain name)

  • lr (float) – Learning rate

  • **kwargs – Additional keyword arguments passed to trainer

Return type

None