def __call__(self, data):
data.x = torch.zeros((data.num_nodes, 1), dtype=torch.float)
data = TwoMalkin()(data)
data = ConnectedThreeMalkin()(data)
data.x = degree(data.edge_index[0], data.num_nodes, dtype=torch.long)
data.x = one_hot(data.x, 136, torch.float)
return data
def __call__(self,data):
data.x = torch.zeros((data.num_nodes, 1), dtype=torch.float)
data = TwoMalkin()(data)
data = ConnectedThreeMalkin()(data)
data.x = degree(data.edge_index[0], data.num_nodes, dtype=torch.long)
data.x = F.one_hot(data.x//self.div, num_classes=(degrees[self.args.dataset])//self.div+1).to(torch.float)
return data
def __call__(self, data):
x = data.x
data.x = data.x[:, :5]
data = TwoMalkin()(data)
data = ConnectedThreeMalkin()(data)
data.x = x
return data
def __call__(self, data):
if data.x is None:
data.x = torch.zeros((data.num_nodes, 1), dtype=torch.float)
data = TwoMalkin()(data)
data = ConnectedThreeMalkin()(data)
data.x = degree(data.edge_index[0],
data.num_nodes,
dtype=torch.long)
data.x = F.one_hot(data.x,
num_classes=int(degrees[self.args.dataset])).to(
torch.float)
else:
x = data.x
data = TwoMalkin()(data)
data = ConnectedThreeMalkin()(data)
data.x = x
return data