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moPPIt

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AlienChen commited on
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1 Parent(s): 2a6e516

Update moo.py

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  1. moo.py +3 -3
moo.py CHANGED
@@ -31,12 +31,12 @@ tokenizer = AutoTokenizer.from_pretrained("facebook/esm2_t33_650M_UR50D")
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  target_sequence = tokenizer(target, return_tensors='pt')['input_ids'].to(device)
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  # Load Models
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- solver = load_solver('/scratch/pranamlab/tong/checkpoints/MOG-DFM/ckpt/peptide/cnn_epoch200_lr0.0001_embed512_hidden256_loss3.1051.ckpt', vocab_size, device)
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- bindevaluator = load_bindevaluator('/scratch/pranamlab/tong/checkpoints/BindEvaluator/model_path/finetuned_BindEvaluator.ckpt', device)
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  motif_model = MotifModel(bindevaluator, target_sequence, motifs, penalty=args.motif_penalty)
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- affinity_predictor = load_affinity_predictor('/scratch/pranamlab/tong/checkpoints/MOG-DFM/classifier_ckpt/binding_affinity_unpooled.pt', device)
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  affinity_model = AffinityModel(affinity_predictor, target_sequence)
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  hemolysis_model = HemolysisModel(device=device)
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  nonfouling_model = NonfoulingModel(device=device)
 
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  target_sequence = tokenizer(target, return_tensors='pt')['input_ids'].to(device)
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  # Load Models
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+ solver = load_solver('./ckpt/peptide/cnn_epoch200_lr0.0001_embed512_hidden256_loss3.1051.ckpt', vocab_size, device)
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+ bindevaluator = load_bindevaluator('./classifier_ckpt/finetuned_BindEvaluator.ckpt', device)
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  motif_model = MotifModel(bindevaluator, target_sequence, motifs, penalty=args.motif_penalty)
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+ affinity_predictor = load_affinity_predictor('./classifier_ckpt/binding_affinity_unpooled.pt', device)
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  affinity_model = AffinityModel(affinity_predictor, target_sequence)
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  hemolysis_model = HemolysisModel(device=device)
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  nonfouling_model = NonfoulingModel(device=device)