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Update esmfold model not to use param_buffer_assignment #1324

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merged 3 commits into from
Sep 11, 2024
Merged

Update esmfold model not to use param_buffer_assignment #1324

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4a65d60
Update esmfold model not to use param_buffer_assignment
jiminha Sep 11, 2024
19763af
comment fix
jiminha Sep 11, 2024
4189d9c
Fix changes error
jiminha Sep 11, 2024
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3 changes: 3 additions & 0 deletions examples/protein-folding/run_esmfold.py
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Expand Up @@ -82,6 +82,9 @@ def convert_outputs_to_pdb(outputs):
test_protein = "MGAGASAEEKHSRELEKKLKEDAEKDARTVKLLLLGAGESGKSTIVKQMKIIHQDGYSLEECLEFIAIIYGNTLQSILAIVRAMTTLNIQYGDSARQDDARKLMHMADTIEEGTMPKEMSDIIQRLWKDSGIQACFERASEYQLNDSAGYYLSDLERLVTPGYVPTEQDVLRSRVKTTGIIETQFSFKDLNFRMFDVGGQRSERKKWIHCFEGVTCIIFIAALSAYDMVLVEDDEVNRMHESLHLFNSICNHRYFATTSIVLFLNKKDVFFEKIKKAHLSICFPDYDGPNTYEDAGNYIKVQFLELNMRRDVKEIYSHMTCATDTQNVKFVFDAVTDIIIKENLKDCGLF" # len = 350

tokenizer = AutoTokenizer.from_pretrained("facebook/esmfold_v1")
# Set _supports_param_buffer_assignment to False since facebook/esmfold_v1's encoder weights are float16.
# Without this fix, we will have the weights loaded with float16 on gaudi2,gaudi3 and runtime error on gaudi1
EsmForProteinFolding._supports_param_buffer_assignment = False
model = EsmForProteinFolding.from_pretrained("facebook/esmfold_v1", low_cpu_mem_usage=False)
model = model.to(device)

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