DeepGraphLearning / DeepGraphLearning/PerturbDiff

RuntimeError: mat1 and mat2 shapes cannot be multiplied during sampling with finetuned_replogle.ckpt

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Description

Hello! I'm trying to run the sampling script using the provided finetuned_replogle.ckpt.

It seems this checkpoint was trained on 12626 genes, but script defaults to a 2000-gene space, causing a shape mismatch error:
RuntimeError: mat1 and mat2 shapes cannot be multiplied (128x4000 and 25252x512)

I tried changing the config to match 12626 genes:

data.pad_length=12626
model.hidden_num=[12626,512]
model.input_dim=12626
data.embed_key=X

However, the script still fails because 2000 is strictly hardcoded in several assert statements across the sampling codebase (e.g., sampling_generation_helpers.py line 58 and sampling_generation.py line 94).

How can I correctly run sampling for this finetuned checkpoint? Are there plans to make the gene dimension dynamic instead of hardcoded?

Thanks!

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Research direction

Start by reading the hardcoded dimension assertions in sampling_generation_helpers.py around line 58 and sampling_generation.py around line 94, then compare them with the finetuned_replogle.ckpt dimensions and the supplied sampling configuration. Done means sampling runs with the checkpoint and no 2000-gene shape mismatch.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
68/100

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