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changed config
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config/config_hparam.json

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@@ -1,28 +1,27 @@
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{
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"name": "biomarker_log",
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"name": "biomarker_log",
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"d_model_name" : "seyonec/PubChem10M_SMILES_BPE_450k",
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"p_model_name" : "Rostlab/prot_bert_bfd",
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"gpu_ids" : "4,5,6,7",
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"model_mode" : "train",
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"load_checkpoint" : "./checkpoint/bindingDB/epoch=33-step=13463.ckpt",
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"d_model_name": "seyonec/PubChem10M_SMILES_BPE_450k",
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"p_model_name": "Rostlab/prot_bert_bfd",
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"prot_maxlength" : 545,
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"layer_limit" : true,
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"gpu_ids": "1",
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"model_mode": "train",
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"load_checkpoint": "./checkpoint/bindingDB/epoch=33-step=13463.ckpt",
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"max_epoch": 50,
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"batch_size": 54,
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"num_workers": 16,
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"prot_maxlength": 545,
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"layer_limit": true,
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"task_name" : "davis",
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"lr": 5e-6,
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"layer_features" : [768, 32, 1],
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"dropout" : 0.1,
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"loss_fn" : "smooth",
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"max_epoch": 50,
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"batch_size": 54,
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"num_workers": 16,
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"traindata_rate" : 1.0,
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"pretrained": {"chem": true, "prot": true},
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"num_seed" : 9095
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}
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"task_name": "davis",
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"lr": 5e-6,
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"layer_features": [768, 32, 1],
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"dropout": 0.1,
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"loss_fn": "smooth",
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"traindata_rate": 1.0,
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"pretrained": { "chem": true, "prot": true },
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"num_seed": 9095
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}

train.py

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from sklearn.metrics import f1_score, roc_curve, precision_score, recall_score, auc
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from sklearn.metrics import roc_auc_score, average_precision_score
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from module.model import deleteEncodingLayers
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class BiomarkerDataset(Dataset):
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def __init__(self, list_IDs, labels, df_dti, d_tokenizer, p_tokenizer, prot_maxLength):

train_regression.py

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from utils.attention_flow import *
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from utils.emetric import regression_score
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from module.model import BApredictModel
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from module.model import BApredictModel, deleteEncodingLayers
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from module.datamodule import BAPredictDataModule
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import torch

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