def __init__(self, in_features, out_features, hids=[], acts=[], K=2, dropout=None, weight_decay=5e-5, lr=0.2, bias=False): super().__init__() if hids or acts: raise RuntimeError( f"Arguments 'hids' and 'acts' are not supported to use in SGC (PyG backend)." ) # assert dropout, "unused" conv = SGConv(in_features, out_features, bias=bias, K=K, cached=True, add_self_loops=True) self.conv = conv self.compile(loss=nn.CrossEntropyLoss(), optimizer=optim.Adam(conv.parameters(), lr=lr, weight_decay=weight_decay), metrics=[Accuracy()])
def __init__(self, in_channels, out_channels, hiddens=[], activations=[], K=2, dropout=0.5, weight_decay=5e-5, lr=0.2, use_bias=False): super().__init__() if hiddens or activations: raise RuntimeError( f"Arguments 'hiddens' and 'activations' are not supported to use in SGC (PyG backend)." ) conv = SGConv(in_channels, out_channels, bias=use_bias, K=K, cached=True, add_self_loops=True) self.conv = conv self.dropout = Dropout(dropout) self.compile(loss=torch.nn.CrossEntropyLoss(), optimizer=optim.Adam(conv.parameters(), lr=lr, weight_decay=weight_decay), metrics=[Accuracy()])