opts.py

import argparse


def parse_opts():
    parser = argparse.ArgumentParser()
    parser.add_argument("--epoch", type=int, default=0, help="epoch to start training from")
    parser.add_argument("--n_epochs", type=int, default=200, help="number of epochs of training")
    parser.add_argument("--dataset_name", type=str, default="alice", help="name of the dataset")
    parser.add_argument("--batch_size", type=int, default=2, help="size of the batches")
    parser.add_argument("--lr", type=float, default=0.0002, help="adam: learning rate")
    parser.add_argument("--b1", type=float, default=0.5, help="adam: decay of first order momentum of gradient")
    parser.add_argument("--b2", type=float, default=0.999, help="adam: decay of first order momentum of gradient")
    parser.add_argument("--decay_epoch", type=int, default=100, help="epoch from which to start lr decay")
    parser.add_argument("--n_cpu", type=int, default=8, help="number of cpu threads to use during batch generation")
    parser.add_argument("--img_height", type=int, default=512, help="size of image height")
    parser.add_argument("--img_width", type=int, default=512, help="size of image width")
    parser.add_argument("--channels", type=int, default=3, help="number of image channels")
    parser.add_argument(
        "--sample_interval", type=int, default=3000, help="interval between sampling of images from generators"
    )
    parser.add_argument("--img_size", type=int, default=512, help="size of each image dimension")
    parser.add_argument("--checkpoint_interval", type=int, default=5, help="interval between model checkpoints")
    parser.add_argument("--output_path",type=str,default="pictures",help='Local path of images')
    parser.add_argument("--texture_path",type=str,default="train_data/",help='Local path of textures')
    parser.add_argument("--latent_dim", type=int, default=256, help="dimensionality of the latent space")
    parser.add_argument("--n_critic", type=int, default=5, help="number of training steps for discriminator per iter")
    parser.add_argument("--clip_value", type=float, default=0.01, help="lower and upper clip value for disc. weights")

    args = parser.parse_args()
    return args