class HetGraphSAGE(torch.nn.Module): def __init__(self, nfeat1, nfeat2, nhid, out_dim, gamma=0.5, drop_rate=0): super().__init__() self.Linear1 = nn.Linear(nfeat1, nhid) self.Linear2 = nn.Linear(nfeat2, nhid) self.SAGE1 = SAGEConvLayer(nhid, nhid) self.SAGE1_2 = SAGEConvLayer(nhid, nhid) self.SAGE2 = SAGEConvLayer(nhid, nhid) self.SAGE2_2 = SAGEConvLayer(nhid, nhid) self.outLinear = nn.Linear(nhid, out_dim) self.gamma = gamma self.dropout = drop_rate这里的out_dim不用自己赋值吗
时间: 2023-12-14 18:03:14 浏览: 95
torch_cluster-1.5.9-cp39-cp39-win_amd64whl.zip
是的,您需要为`out_dim`赋一个值,否则会报错。`out_dim`是输出层的维度,通常需要根据具体的任务进行设置。在实例化模型时,您可以将`out_dim`作为参数传递给模型。例如:
```
model = HetGraphSAGE(nfeat1, nfeat2, nhid, out_dim, gamma, drop_rate)
```
其中`nfeat1`和`nfeat2`是输入特征的维度,`nhid`是隐藏层维度,`gamma`是SAGEConvLayer中的参数,`drop_rate`是dropout的概率,`out_dim`是您指定的输出维度。
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