def __init_

def init()

in train_mnist.py [0:0]
31 lines of code
1 McCabe index (conditional complexity)

    def __init__(self):
        parser = argparse.ArgumentParser()
        parser.add_argument('--dataroot', default='./data', help='path to dataset')
        parser.add_argument('--workers', type=int, default=2, help='number of data loading workers')
        parser.add_argument('--batchSize', type=int, default=100, help='input batch size')
        parser.add_argument('--printFreq', type=int, default=50, help='# updates before each print')

        parser.add_argument('--model', type=str, default='dcgan', choices=['dcgan', 'wgan', 'wgan_gp'],
                            help='model type of GAN model')
        parser.add_argument('--n_critic', type=int, default=5, help='number of critic updates per generator update (wgan/wgan_gp)')
        parser.add_argument('--gp_lambda', type=int, default=10, help='weight for gradient penalty (wgan_gp)')
        parser.add_argument('--clip', type=float, default=0.01, help='weight clip range (wgan)')

        parser.add_argument('--nz', type=int, default=100, help='size of the latent z vector')
        parser.add_argument('--ngf', type=int, default=64)
        parser.add_argument('--ndf', type=int, default=64)
        parser.add_argument('--nc', type=int, default=1)
        parser.add_argument('--niter', type=int, default=200, help='number of epochs to train for')
        parser.add_argument('--lrD', type=float, default=0.0001, help='learning rate, default=0.0002')
        parser.add_argument('--lrG', type=float, default=None, help='learning rate, default=0.0002 -- same as lrD')
        parser.add_argument('--beta1', type=float, default=0.5, help='beta1 for adam. default=0.5')
        parser.add_argument('--beta2', type=float, default=0.999, help='beta1 for adam. default=0.999')
        parser.add_argument('--optimizer', type=str, default='adam', choices=['adam', 'extraadam', 'sgd', 'rmsprop'],
                            help='training optimizer')

        parser.add_argument('--ngpu', type=int, default=1, help='number of GPUs to use')
        parser.add_argument('--netG', default='', help="path to netG (to continue training)")
        parser.add_argument('--netD', default='', help="path to netD (to continue training)")
        parser.add_argument('--dnorm', default='spectral', choices=['batch', 'spectral', 'none', 'instance', 'layer'], help="Discriminator normalization")
        parser.add_argument('--exp_dir', type=str, default='EXP', help='directory of experiment')
        parser.add_argument('--exp_name', type=str, default='debug', help='directory of experiment')
        parser.add_argument('--manualSeed', type=int, help='manual seed')
        parser.add_argument('--compute_eig', type=int, choices=[0, 1], default=0)
        self.parser = parser
def __init__()

def init()
