32 lines (27 with data), 1.9 kB

def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument('--hyperparams', help='hyperparams .json file to load')
    parser.add_argument('--box_optunity', default='/home/zhihuan/Documents/20181115_Multiomic_AutoEncoder/experiments/mac/hyperparams_box_constraints.json', help='Filename to box constraints dictionary pickle file')
    parser.add_argument('--dataset_dir', default='/home/zhihuan/Documents/20181115_Multiomic_AutoEncoder/Datasets_Multiomics/BRCA/Data_Preprocessing/Processed', help="datasets")
    parser.add_argument('--num_epochs', type=int, default=100, help="Number of epochs to train for. Default: 300")
    parser.add_argument('--measure_while_training', action='store_true', default=False, help='disables measure while training (make program faster)')
    parser.add_argument('--batch_size', type=int, default=256, help="Number of batches to train/test for. Default: 256")
    parser.add_argument('--dataset', type=int, default=2, help="1: RNAseq only; 2. miRNAseq only; 3. RNAseq+miRNAseq; 4. RNAseq+miRNAseq+CNV+TMB; 5. All + Clinical")
    parser.add_argument('--nocuda', action='store_true', default=False, help='disables CUDA training')
    parser.add_argument('--verbose', default=1, type=int)
    parser.add_argument('--results_dir', default='/home/zhihuan/Documents/20181115_Multiomic_AutoEncoder/experiments/mac/Results/20181128_data_583_new_train_test_sigmoid', help="results dir")
    return parser.parse_args()

if __name__=='__main__':
    torch.cuda.empty_cache()
    args = parse_args()
    
    # model file
    lambda_1 = 0#1e4
    dropout_rate, lambda_2, lambda_3 = 0, 0, 0
    num_epochs = args.num_epochs
    batch_size = args.batch_size
    learning_rate_range = 10**np.arange(-5,-1,0.3)
    cuda = True
    verbose = 0
    measure_while_training = True
    
    dropout_rate = 0
    lambda_2 = 1e-5 # L1