config.py

import argparse 
import numpy as np 
 
 
def create_parser(): 
    """Creates a parser for command-line arguments. 
    """ 
    parser = argparse.ArgumentParser() 
 
    # Model hyper-parameters 
    parser.add_argument('--free_gpu_id', 
                        type=int, 
                        default=0, 
                        help='The selected gpu.') 
 
    parser.add_argument('--x_image_channel', type=int, default=2) 
    parser.add_argument('--y_image_channel', type=int, default=2) 
    parser.add_argument('--lstm_dim', type=int, default=50)  # For mask_CNN model 
    parser.add_argument('--fc1_dim', type=int, default=600)  # For mask_CNN model 
    parser.add_argument('--sf', type=int, default=-1, help='The spreading factor.') 
    parser.add_argument('--bw', type=int, default=125000, help='The bandwidth.') 
    parser.add_argument('--fs', type=int, default=1000000, help='The sampling rate.') 
    parser.add_argument( '--load_iters', type=int, default=-1, help= 'The number of iterations to load(will search for it by filename)')
    parser.add_argument('--batch_size', type=int, default=16, help='The number of images in a batch.') 
    parser.add_argument( '--num_workers', type=int, default=0, help='The number of threads to use for the DataLoader.') 
    parser.add_argument('--lr', type=float, default=0.0002, help='The learning rate')  
    parser.add_argument('--w_image', type=float, default=1024, help='The scaling factor for the imaging loss') 
    parser.add_argument('--beta1', type=float, default=0.5) 
    parser.add_argument('--beta2', type=float, default=0.999) 
    parser.add_argument('--data_dir', type=str, default='/data/djl/data0306/data', help='Choose the root path to rf signals.') 
    parser.add_argument("--snr", default=0, type=float)  # for train: -25:0, test: -40, 16 
    parser.add_argument( '--ratio_bt_train_and_test', type=float, default=0.8, help='The ratio between the train and the test dataset') 
    parser.add_argument('--checkpoint_dir', type=str, default='/data/djl/checkpoints/default') 
    parser.add_argument('--load', type=str, default='yes') 
    parser.add_argument('--log_step', type=int, default=100) 
    parser.add_argument('--test_step', type=int, default=500) 
    parser.add_argument( '--train_iters', type=int, default=10000, help= 'The number of training iterations to run (you can Ctrl-C out earlier if you want).') 
    parser.add_argument('--checkpoint_every', type=int, default=500) 
    parser.add_argument('--load_checkpoint_dir', type=str, default='/data/djl') 
    parser.add_argument('--model_ver', type=int, default=3) 
    parser.add_argument('--max_test_iters', type=int, default=50) 
    parser.add_argument('--terminate_acc', type=float, default=0.85) 
    parser.add_argument('--dechirp', type=str, default='True') 
    parser.add_argument('--out_channel', type=int, default=2) 
    parser.add_argument('--stft_mod', type=int, default=4) 
    parser.add_argument('--cxtoy', type=str, default='True') 
    parser.add_argument('--load_cxtoy', type=str, default='True') 
    parser.add_argument('--load_maskcnn', type=str, default='True') 
    parser.add_argument('--norm_factor', type=float, default=2) 
    parser.add_argument('--comp_channel', type=int, default=2) 
    parser.add_argument('--cxtoy_pretrain', type=str, default='False') 
    return parser