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Batching for GCNConv Layer #9637
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I'm not sure about this, but I think in the case of GCNConv you can batch your data and it accepts any input shape as well as the node_dim attribute is set correctly (by default to -2). So you can use for example a tensor of [BxL, N, F] and it will operate with the nodes on N for each BxL element. |
The issue doesn't seem to be the tensor itself, but the adjacency matrix. It is specified in the |
📚 Describe the documentation issue
It is unclear what to do in regards to batching when using a custom feature map and adjacency matrix. For instance, the docs help when dealing with the batching from the dataloader perspective, but not with a custom approach. I am dealing with a case when I am trying to use
GCNConv
inside of an existing model based on latent features (ie, not from the dataloader). It is unclear what to do with the batch dimension in this case for the adjacency matrix and/or feature map. needs to be clarifiedSuggest a potential alternative/fix
Show an example when using
GCNConv
or other graph convolution layers outside of the pre-defined dataloading.The text was updated successfully, but these errors were encountered: