Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

RAM usage exceeds capacity when loading sciplex chemical dataset. #4

Open
RapidsAIpk opened this issue Apr 29, 2024 · 0 comments
Open

Comments

@RapidsAIpk
Copy link

When attempting to load the SCIPLEX chemical dataset using the perturbnet_sciplex_example_notebook.ipynb file, my system's RAM becomes fully utilized and the process is killed. My system has 64 GB of RAM, but it appears that loading this dataset exceeds its capacity.

This issue occurs during the execution of the notebook, specifically when loading the SCIPLEX chemical dataset. Despite having sufficient RAM, the process is unable to complete due to excessive memory consumption. The error comes in the following line of code:

(2) load models

generation scvi

adata_train = adata[idx_to_train, :].copy()
adata_train = adata_train[kept_indices, :].copy()

scvi.data.setup_anndata(adata_train, layer = "counts")
scvi_model_cinn = scvi.model.SCVI.load(path_scvi_model_cinn, adata_train, use_cuda = False)
scvi_model_de = scvi_predictive_z(scvi_model_cinn)

device = 'cuda' if torch.cuda.is_available() else 'cpu'

ChemicalVAE

model_chemvae = ChemicalVAE(n_char = data_chem_onehot.shape[2], max_len = data_chem_onehot.shape[1]).to(device)
model_chemvae.load_state_dict(torch.load(path_chemvae_model, map_location = device))
model_chemvae.eval()

I would like to request assistance in understanding the system requirements for running PerturbNet and resolving this issue to successfully load the SCIPLEX chemical dataset without exhausting the available RAM.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant