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您好,我这里有一批节点特征矩阵,大小为[B,N,C],B是批处理个数,N是节点个数,C是特征维度数;还有一批邻接矩阵[B,N,N]。由于我的邻接矩阵太过稠密,我在使用PYG复现的GraphUNet时显存不足,因为它是用邻接列表存储节点连接关系的。 但是现在我想使用邻接矩阵的形式,请问如何进行批训练呢?
The text was updated successfully, but these errors were encountered:
Try this one: https://pytorch.org/docs/stable/generated/torch.sparse.mm.html
Change the adjacency matrix to sparse and do matrix multiplication with sparse.mm.
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您好,我这里有一批节点特征矩阵,大小为[B,N,C],B是批处理个数,N是节点个数,C是特征维度数;还有一批邻接矩阵[B,N,N]。由于我的邻接矩阵太过稠密,我在使用PYG复现的GraphUNet时显存不足,因为它是用邻接列表存储节点连接关系的。
但是现在我想使用邻接矩阵的形式,请问如何进行批训练呢?
The text was updated successfully, but these errors were encountered: