GOOD.networks.models.CoralGCNs

GCN implementation of the Deep Coral algorithm from “Deep CORAL: Correlation Alignment for Deep Domain Adaptation” paper

Classes

Coral_GCN(config)

The Graph Neural Network modified from the "Deep CORAL: Correlation Alignment for Deep Domain Adaptation" paper and "Semi-supervised Classification with Graph Convolutional Networks" paper.
class GOOD.networks.models.CoralGCNs.Coral_GCN(config: Union[CommonArgs, Munch])[source]

Bases: GNNBasic

The Graph Neural Network modified from the “Deep CORAL: Correlation Alignment for Deep Domain Adaptation” paper and “Semi-supervised Classification with Graph Convolutional Networks” paper.

Parameters

config (Union[CommonArgs, Munch]) – munchified dictionary of args (config.model.dim_hidden, config.model.model_layer, config.dataset.dim_node, config.dataset.num_classes)

forward(*args, **kwargs) → Tuple[Tensor, Tensor][source]

The Deep Coral-GCN model implementation.

Parameters

  • *args (list) – argument list for the use of arguments_read. Refer to arguments_read

  • **kwargs (dict) – key word arguments for the use of arguments_read. Refer to arguments_read

Returns (Tensor):

[label predictions, features]