3f0f8ca3bda791ceba269ad98a9677180abbc9f0,examples/node2vec.py,,,#,66

Before Change

        return F.log_softmax(x, dim=1)

classifier = Classifier().to(dev)
optimizer_c = torch.optim.Adam(classifier.parameters(), lr=0.001)

def train_classifier():
    classifier.train()
    optimizer_c.zero_grad()

After Change

    return loss.item()


for epoch in range(1, 51):
    loss = train()

// class Classifier(torch.nn.Module):
//     def __init__(self):
//         super(Classifier, self).__init__()
//         self.lin1 = torch.nn.Linear(feature_dim, feature_dim)

Instances