torchcell.models.hetero_cell_bipartite_dango_gi.GeneInteractionDango

class GeneInteractionDango(gene_num: int, hidden_channels: int, num_layers: int, gene_multigraph: GeneMultiGraph, dropout: float = 0.1, norm: str = 'layer', activation: str = 'relu', gene_encoder_config: dict[str, Any] | None = None, local_predictor_config: dict[str, Any] | None = None)

Bases: Module

Full DANGO model: gene embeddings, hetero conv encoder, and interaction head.

forward_single(data: HeteroData | Batch) → Tensor

Encode one graph (or batch) into gene embeddings through the conv stack.

forward(cell_graph: HeteroData, batch: HeteroData) → tuple[Tensor, dict[str, Tensor]]

Predict gene interactions from the wildtype graph and perturbed batch.

property num_parameters: dict[str, int]

Return trainable parameter counts broken down by model component.