vincentwi / school Goto Github PK

num_layers = 2
num_out_heads = 6
hiddens = [256]
heds = [4] 
activations = [F.elu]
fdrop = [0]
adrop = [0]
nslope = [0.2]
losses = [nn.CrossEntropyLoss()]
optimizers = [torch.optim.Adam]

heads = ([h] * num_layers) + [num_out_heads]
model = GAT(
    g=train_dataset.graph, 
    num_layers=num_layers, 
    in_dim=n_features,
    num_hidden=size, 
    num_classes=n_classes, 
    heads=heads,
    activation=a, 
    feat_drop=f, 
    attn_drop=attn,    
    negative_slope=n, 
    residual=True
).to(device)