cogdl.models.nn.pyg_deepergcn

Module Contents

Classes

GENConv

DeepGCNLayer

DeeperGCN

class cogdl.models.nn.pyg_deepergcn.GENConv(in_feat, out_feat, aggr='softmax_sg', beta=1.0, p=1.0, learn_beta=False, learn_p=False, use_msg_norm=False, learn_msg_scale=True)[source]

Bases: torch.nn.Module

message_norm(self, x, msg)[source]
forward(self, x, edge_index, edge_attr=None)[source]
class cogdl.models.nn.pyg_deepergcn.DeepGCNLayer(in_feat, out_feat, conv, connection='res', activation='relu', dropout=0.0, checkpoint_grad=False)[source]

Bases: torch.nn.Module

forward(self, x, edge_index)[source]
class cogdl.models.nn.pyg_deepergcn.DeeperGCN(in_feat, hidden_size, out_feat, num_layers, connection='res+', activation='relu', dropout=0.0, aggr='max', beta=1.0, p=1.0, learn_beta=False, learn_p=False, learn_msg_scale=True, use_msg_norm=False)[source]

Bases: cogdl.models.BaseModel

static add_args(parser)[source]

Add model-specific arguments to the parser.

classmethod build_model_from_args(cls, args)[source]

Build a new model instance.

forward(self, x, edge_index, edge_attr=None)[source]
loss(self, x, edge_index, y, x_mask)[source]
predict(self, x, edge_index)[source]
static get_trainer(taskType: Any, args)[source]