Comments (5)
@airparkchen hi, i get the same error and fix it. You can modify the code at class 'EfficientMultiheadAttention' from mit.py to "out = self.attn(query=x_q.permute(1,0,2), key=x_kv.permute(1,0,2), value=x_kv.permute(1,0,2), need_weights=False)[0].permute(1,0,2)". This error may a code bug or caused by the version of pytorch. You can obtain the correct input dimensions from torch.nn.MultiheadAttention.
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Sorry for late response. The error seems to be caused by the version of mmsegmentation or invalid input data type or shape. Have you tried to reinstall mmsegmentation with recommended version and checked the input?
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Thanks for your response!
I have tried reinstall and using the demo picture(Tzionas_dataset-02-1-rgb-100.png)
still get the same error.
btw
at first i'm using your "[environment.yml]" to create a anaconda envirnment
but i got an" ImportError: DLL load failed " error from "mmcv-full"
so i upgrade "mmcv-full" to 1.4.0
and check the torch cuda version is compare to mine .
are these might be a reason i got the "UnboundLocalError: " which i mention at the beginning?
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@binghui-z Sorry for late response.
Error Fixed!!
Thank you so much!!
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@airparkchen hi, i get the same error and fix it. You can modify the code at class 'EfficientMultiheadAttention' from mit.py to "out = self.attn(query=x_q.permute(1,0,2), key=x_kv.permute(1,0,2), value=x_kv.permute(1,0,2), need_weights=False)[0].permute(1,0,2)". This error may a code bug or caused by the version of pytorch. You can obtain the correct input dimensions from torch.nn.MultiheadAttention.
Thanks!
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