def __init__(self, layers=args.layer, name="gcn"):
super(GCN, self).__init__(name=name)
with self._enter_variable_scope():
self._networks = []
if layers == 1:
self._networks.append(
GraphIndependent(
node_model_fn=dropout_fn))
self._networks.append(
EdgeBlock(
edge_model_fn=edge_model_fn,
use_edges=False,
use_receiver_nodes=True,
use_sender_nodes=False,
use_globals=False))
self._networks.append(
NodeBlock(
node_model_fn=make_linear_model,
use_received_edges=True,
use_sent_edges=False,
use_nodes=False,
use_globals=False))
else:
for layer in range(args.layer - 1):
self._networks.append(
GraphIndependent(
node_model_fn=dropout_fn))
self._networks.append(
EdgeBlock(
edge_model_fn=edge_model_fn,
use_edges=False,
use_receiver_nodes=True,
use_sender_nodes=False,
use_globals=False))
self._networks.append(
NodeBlock(
node_model_fn=make_linear_model,
use_received_edges=True,
use_sent_edges=False,
use_nodes=False,
use_globals=False))
self._networks.append(
GraphIndependent(
node_model_fn=dropout_fn))
self._networks.append(
EdgeBlock(
edge_model_fn=edge_model_fn,
use_edges=False,
use_receiver_nodes=True,
use_sender_nodes=False,
use_globals=False))
self._networks.append(
NodeBlock(
node_model_fn=final_layer,
use_received_edges=True,
use_sent_edges=False,
use_nodes=False,
use_globals=False))
def __init__(self, name="MLPGraphIndependent"):
super(MLPGraphIndependent, self).__init__(name=name)
with self._enter_variable_scope():
self._network = GraphIndependent(
edge_model_fn=make_mlp_model,
node_model_fn=make_mlp_model)
def _kg_encoder(self):
return GraphIndependent(self._edge_model, self._node_model, name='kg_encoder')