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sail's Introduction

Hi, You can call me JCChan 👋

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sail's Issues

Potential bug in the CoMPT attention implementation

Hi,

Thanks for open sourcing your wonderful work, "Learning Attributed Graph Representations with Communicative Message Passing Transformer." I found a potential bug in your in_scores cross-attention computation. It seems problematic when the edge feature matrix is not symmetric.

Please see my reproduction at:
https://colab.research.google.com/drive/1LLMc9Ue47MoHrTDqJgM-rMMLUacgXM_R?usp=sharing

And by einsum definition, the Eq. (8) and your code seem inconsistent. I could understand the Eq. (8), where the broadcast of node/token embedding for M_i is along the column axis. But your code implementation is not the same as such.

out_scores = torch.einsum('b h m d, b h m n d -> b h m n', query, key) / math.sqrt(d)
in_scores = torch.einsum('b h m d, b h m n d -> b h n m', query, key) / math.sqrt(d)

image

Any help is appreciated.

Many thank,
Qi

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