cogdl.layers.strategies_layers

Module Contents

Classes

GINConv

GNN

GNNPred

Pretrainer

Discriminator

InfoMaxTrainer

ContextPredictTrainer

MaskTrainer

SupervisedTrainer

Finetuner

class cogdl.layers.strategies_layers.GINConv(hidden_size, input_layer=None, edge_emb=None, edge_encode=None, pooling='sum', feature_concat=False)[source]

Bases: torch.nn.Module

forward(self, x, edge_index, edge_attr, self_loop_index=None, self_loop_type=None)[source]
aggr(self, x, edge_index, num_nodes)[source]
class cogdl.layers.strategies_layers.GNN(num_layers, hidden_size, JK='last', dropout=0.5, input_layer=None, edge_encode=None, edge_emb=None, num_atom_type=None, num_chirality_tag=None, concat=False)[source]

Bases: torch.nn.Module

forward(self, x, edge_index, edge_attr, self_loop_index=None, self_loop_type=None)[source]
class cogdl.layers.strategies_layers.GNNPred(num_layers, hidden_size, num_tasks, JK='last', dropout=0, graph_pooling='mean', input_layer=None, edge_encode=None, edge_emb=None, num_atom_type=None, num_chirality_tag=None, concat=True)[source]

Bases: torch.nn.Module

load_from_pretrained(self, path)[source]
forward(self, data, self_loop_index, self_loop_type)[source]
pool(self, x, batch)[source]
class cogdl.layers.strategies_layers.Pretrainer(args, transform=None)[source]

Bases: torch.nn.Module

get_dataset(self, dataset_name, transform=None)[source]
fit(self)[source]
class cogdl.layers.strategies_layers.Discriminator(hidden_size)[source]

Bases: torch.nn.Module

reset_parameters(self)[source]
forward(self, x, summary)[source]
class cogdl.layers.strategies_layers.InfoMaxTrainer(args)[source]

Bases: cogdl.layers.strategies_layers.Pretrainer

static add_args(parser)[source]
_train_step(self)[source]
class cogdl.layers.strategies_layers.ContextPredictTrainer(args)[source]

Bases: cogdl.layers.strategies_layers.Pretrainer

static add_args(parser)[source]
_train_step(self)[source]
get_cbow_pred(self, overlapped_rep, overlapped_context, neighbor_rep)[source]
get_skipgram_pred(self, overlapped_rep, overlapped_context_size, neighbor_rep)[source]
class cogdl.layers.strategies_layers.MaskTrainer(args)[source]

Bases: cogdl.layers.strategies_layers.Pretrainer

static add_args(parser)[source]
_train_step(self)[source]
class cogdl.layers.strategies_layers.SupervisedTrainer(args)[source]

Bases: cogdl.layers.strategies_layers.Pretrainer

static add_args(parser)[source]
split_data(self)[source]
_train_step(self)[source]
class cogdl.layers.strategies_layers.Finetuner(args)[source]

Bases: cogdl.layers.strategies_layers.Pretrainer

static add_args(parser)[source]
build_model(self, args)[source]
split_data(self)[source]
_train_step(self)[source]
_test_step(self, split='val')[source]
fit(self)[source]