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View Code? Open in Web Editor NEW[ICLR 2024] The implementation for the paper "Space Group Constrained Crystal Generation"
[ICLR 2024] The implementation for the paper "Space Group Constrained Crystal Generation"
Thank you for open sourcing your code!
However, I notice that DiffCSP-PP does not provide prediction code. Can I use DiffCSP-PP trained weight files for prediction using DiffCSP code?
Or will you open source the prediction code for DiffCSP-PP in the future?
Hello,In the DiffCSP-PP-main/diffcsp/pl_modules/diffusion.py , within the def sample module, what is the role of diff_ratio, and has it always been 1?
Dear team,
I am trying to replicate the results by using the same training script for dataset=perov_5 following instructions here.
When loading the model in a Jupyter notebook, I get the following error message:
RuntimeError: Error(s) in loading state_dict for CSPDiffusion:
size mismatch for decoder.csp_layer_0.edge_mlp.0.weight: copying a param with shape torch.Size([512, 1798]) from checkpoint, the shape in current model is torch.Size([512, 1801]).
size mismatch for decoder.csp_layer_1.edge_mlp.0.weight: copying a param with shape torch.Size([512, 1798]) from checkpoint, the shape in current model is torch.Size([512, 1801]).
size mismatch for decoder.csp_layer_2.edge_mlp.0.weight: copying a param with shape torch.Size([512, 1798]) from checkpoint, the shape in current model is torch.Size([512, 1801]).
size mismatch for decoder.csp_layer_3.edge_mlp.0.weight: copying a param with shape torch.Size([512, 1798]) from checkpoint, the shape in current model is torch.Size([512, 1801]).
size mismatch for decoder.csp_layer_4.edge_mlp.0.weight: copying a param with shape torch.Size([512, 1798]) from checkpoint, the shape in current model is torch.Size([512, 1801]).
size mismatch for decoder.csp_layer_5.edge_mlp.0.weight: copying a param with shape torch.Size([512, 1798]) from checkpoint, the shape in current model is torch.Size([512, 1801]).
size mismatch for decoder.lattice_out.weight: copying a param with shape torch.Size([6, 512]) from checkpoint, the shape in current model is torch.Size([9, 512]).
Hi , would you please share a complete list of requirement.txt, i find the installation is very difficult now .
res = dict(traj[0])
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