You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Congrats on the great work! I am trying to develop a flow-matching version of your work, but I encounter some challenges when reproducing your work on Conditional Generation on Geometric Objects.
When I ran Sampling and evaluating commands, I encountered the following error for all data_id I tried.
[2024-05-08 23:53:49,959::evaluate::INFO] Vina Score: Mean: nan Median: nan
[2024-05-08 23:53:49,959::evaluate::INFO] Vina Min : Mean: nan Median: nan
Traceback (most recent call last):
File "/global/cfs/cdirs/mp54/jsliang/MLFF/conda_envs/eval/lib/python3.9/runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/global/cfs/cdirs/mp54/jsliang/MLFF/conda_envs/eval/lib/python3.9/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/global/cfs/cdirs/mp54/jsliang/LFM-3DG/AE_Geometry_and_Conditional_Latent_Diffusion/scripts/evaluate.py", line 154, in <module>
print_ring_ratio([r['chem_results']['ring_size'] for r in results], logger)
File "/global/cfs/cdirs/mp54/jsliang/LFM-3DG/AE_Geometry_and_Conditional_Latent_Diffusion/scripts/evaluate.py", line 34, in print_ring_ratio
logger.info(f'ring size: {ring_size} ratio: {n_mol / len(all_ring_sizes):.3f}')
ZeroDivisionError: division by zero
What I changed are:
the model used in sample_z because I do not have the folder ldm_2023_11_16__18_01_30 model.load_state_dict(torch.load('logs_diffusion/ldm_2023_11_16__18_01_30/checkpoints/30000.pt')['model'])
to model.load_state_dict(torch.load('../AE_geom_cond_weights_and_data/weight_diffusion.pt')['model'])
the version name from 'final-001' to 'final' in pl_pair_dataset.py to match the file name in https://github.com/guanjq/targetdiff#data def __init__(self, raw_path, transform=None, version='final'):
Can you help check what's wrong?
The text was updated successfully, but these errors were encountered:
Hi Authors,
Congrats on the great work! I am trying to develop a flow-matching version of your work, but I encounter some challenges when reproducing your work on Conditional Generation on Geometric Objects.
When I ran Sampling and evaluating commands, I encountered the following error for all data_id I tried.
What I changed are:
model.load_state_dict(torch.load('logs_diffusion/ldm_2023_11_16__18_01_30/checkpoints/30000.pt')['model'])
to
model.load_state_dict(torch.load('../AE_geom_cond_weights_and_data/weight_diffusion.pt')['model'])
def __init__(self, raw_path, transform=None, version='final'):
Can you help check what's wrong?
The text was updated successfully, but these errors were encountered: