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Thank you for your great effort on this.
And I was wondering if the model is possible for sampling linkers for larger molecules (like connecting 2 10-mer peptides).
I tried using existing model (I know it's not appropriate, I just want to check if the model can run without error) , the model raised NanError during sample_p_zs_given_zt_only_linker. Is it because the inputs contains too many atoms?
Thank you for you patient and help!
The text was updated successfully, but these errors were encountered:
I might have found the solution.
The DDPM class calls the GCL class, which uses the unsorted_segment_sum function to process node features.
Within this function, there is a normalization_factor. The default value for normalization_factor is set to 100, likely because the original model was applied to small molecules (is that right?).
However, when I use peptides as input, the large number of atoms causes an explosion in the second step of diffusion. When I tried setting the normalization_factor to a larger int the model no longer produced NaN errors.
Right?
Hi DiffLinker Team,
Thank you for your great effort on this.
And I was wondering if the model is possible for sampling linkers for larger molecules (like connecting 2 10-mer peptides).
I tried using existing model (I know it's not appropriate, I just want to check if the model can run without error) , the model raised NanError during
sample_p_zs_given_zt_only_linker
. Is it because the inputs contains too many atoms?Thank you for you patient and help!
The text was updated successfully, but these errors were encountered: