关于理解节点和边索引的澄清
通过访问 data 对象的属性， 我如何知道哪个节点功能属于哪个节点？ 如果我理解正确的话，data.x 包含节点功能。 通过运行下面的 for 循环，我可以访问这些功能 但我怎么知道它是属于节点 0 还是节点 9 呢？
from torch_geometric.data import Data
edge_index = torch.tensor([[0, 1, 1, 2, 1, 9],
[1, 0, 2, 1, 8, 1]
], dtype=torch.long)
x = torch.tensor([[-5,7], [0,5], [0,9], [10,9]], dtype=torch.float)
data = Data(x=x, edge_index=edge_index)
for item in range(0, data.x.shape[0]):
print(item, data.x[item], data.edge_index.t()[item])
By accessing the data object's properties,
how would I know which node feature belongs to what node?
If I understand it correctly data.x holds the node features.
By running for loop below I can access the features
but how would I know that if it belongs to node 0 or node 9 for an example?
from torch_geometric.data import Data
edge_index = torch.tensor([[0, 1, 1, 2, 1, 9],
[1, 0, 2, 1, 8, 1]
], dtype=torch.long)
x = torch.tensor([[-5,7], [0,5], [0,9], [10,9]], dtype=torch.float)
data = Data(x=x, edge_index=edge_index)
for item in range(0, data.x.shape[0]):
print(item, data.x[item], data.edge_index.t()[item])
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在您的代码中，通过定义
x，Pytorch Geometric 推断（根据x的形状）存在四个节点。这是在文档中指定的:您还指定了直到节点 9 的节点的边。如果您尝试在此代码上运行任何模型，我怀疑它会产生错误，因为预计只会出现四个节点。这是因为它将尝试访问 x 的第 9 个元素，这将返回索引错误。
最佳实践是定义存在的节点数量。如文档中所述：
In your code, by defining
xas you have, Pytorch Geometric infers (from the shape ofx) that four nodes exist. This is specified in the documentation:You have also specified edges for nodes up to node 9. If you try to run any models on this code, I suspect it would produce an error as there are only four nodes expected to be present. This is because it will try to access the 9th element of
xwhich will return an index error.The best practice is to define the number of nodes present. As stated in the documentation: