430beec651fe14e4f0f032cbc27e18a9ca415d90,examples/cora.py,,,#,11

Before Change

train_mask = torch.arange(0, n - 1000, out=torch.LongTensor())
test_mask = torch.arange(n - 500, n, out=torch.LongTensor())

if torch.cuda.is_available():
    input, adj, target = input.cuda(), adj.cuda(), target.cuda()
    train_mask, test_mask = train_mask.cuda(), test_mask.cuda()

input, target = Variable(input), Variable(target)


class Net(nn.Module):

After Change

dataset = Cora(path, transform=TargetIndegreeAdj())
data = dataset[0].cuda().to_variable()
train_mask = torch.arange(0, data.num_nodes - 1000).long()
test_mask = torch.arange(data.num_nodes - 500, data.num_nodes).long()


class Net(nn.Module):
    def __init__(self):

Instances