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Hi,
I want to run the sample file on the provided model under the fast_molvae directory. But I found that the size of vocabulary in the mose directory may not match with the provided model. And I got the error below. The size of the learned embedding in the mode is 800 which indicates that that model is built on a vocab of size 800.
I'm not sure whether the problem is because of vocabulary, but if it is, can you provide that vocab file?
Thanks.
le.py\", line 845, in load_state_dict
self.__class__.__name__, \"\n\t\".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for JTNNVAE:
size mismatch for jtnn.embedding.weight: copying a param with shape torch.Size([531, 450]) from checkpoint, the shape in current model is torch.Size([800, 450]).
size mismatch for decoder.embedding.weight: copying a param with shape torch.Size([531, 450]) from checkpoint, the shape in current model is torch.Size([800, 450]).
size mismatch for decoder.W_o.bias: copying a param with shape torch.Size([531]) from checkpoint, the shape in current model is torch.Size([800]).
size mismatch for decoder.W_o.weight: copying a param with shape torch.Size([531, 450]) from checkpoint, the shape in current model is torch.Size([800, 450]).
The text was updated successfully, but these errors were encountered:
Hi,
I want to run the sample file on the provided model under the fast_molvae directory. But I found that the size of vocabulary in the mose directory may not match with the provided model. And I got the error below. The size of the learned embedding in the mode is 800 which indicates that that model is built on a vocab of size 800.
I'm not sure whether the problem is because of vocabulary, but if it is, can you provide that vocab file?
Thanks.
The text was updated successfully, but these errors were encountered: