File size: 1,393 Bytes
46b9840 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | import os
import torch
class ArgsConfig:
def __init__(self) -> None:
self.batch_size = 192
self.embedding_size = 480
self.epochs = 50
self.kflod = 5
self.max_len = 40
self.lr = 1.5e-3
self.weight_decay = 0
self.is_autocast = False
self.info_bottleneck = False
self.dropout = 0.6
self.IB_beta = 1e-3
self.model_name = 'DeepPD_C' #
self.exp_nums = 0.0
self.aa_dict = 'esm' # 'protbert' /'esm'/ None
self.info = f"" #对当前训练做的补充说明
# self.data_c_dir = './data/GPMDB_Homo_sapiens_20190115/sorted_GPMDB_Homo_0.025_0.9.csv'
# self.data_c1_dir = './data/GPMDB_Homo_sapiens_20190115/sorted_GPMDB_Homo_0.025.csv'
# self.data_homo_dir = './data/PepFormer/Homo_0.9.csv'
# self.data_mus_dir = './data/PepFormer/Mus_0.9.csv'
# self.log_dir = './result/logs'
# self.save_dir = './result/model_para'
# self.tensorboard_log_dir = './tensorboard'
self.ems_path = './DeepPD/ESM2/esm2_t12_35M_UR50D.pt'
self.esm_layer_idx = 12
# self.save_para_dir = os.path.join(self.save_dir,self.model_name)
self.random_seed = 2023
self.num_classes = 21
self.split_size = 0.8
self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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