# Path: awesome_gans/config.py
# def parse_args():
#     parser = ArgumentParser(description='Awesome-GANs Arguments')
# 
#     # dataset
#     parser.add_argument('--width', type=int, default=32, help='width of image')
#     parser.add_argument('--height', type=int, default=32, help='height of image')
#     parser.add_argument('--n_channels', type=int, default=3, help='number of channel of image')
#     parser.add_argument('--root_path', type=str, default='./', help='root path')
#     parser.add_argument(
#         '--dataset',
#         type=str,
#         default='cifar10',
#         choices=['mnist', 'cifar10', 'cifar100', 'div2k'],
#         help='type of dataset',
#     )
#     parser.add_argument('--mnist_path', type=str, default='mnist')
#     parser.add_argument('--fashion_mnist_path', type=str, default='fashion-mnist')
#     parser.add_argument('--cifar10_path', type=str, default='cifar10')
#     parser.add_argument('--cifar100_path', type=str, default='cifar100')
#     parser.add_argument('--celeba_path', type=str, default='CelebA')
#     parser.add_argument('--celeba_hq_path', type=str, default='CelebA-HQ')
#     parser.add_argument('--div2k_path', type=str, default='DIV2K')
#     parser.add_argument('--pix2pix_path', type=str, default='pix2pix')
#     parser.add_argument('--use_crop', type=bool, default=False, help='use image center crop')
#     parser.add_argument('--model_path', type=str, default='model')
#     parser.add_argument('--output_path', type=str, default='outputs')
# 
#     # misc
#     parser.add_argument('--mode', default='train', type=str, choices=['train', 'inference'])
#     parser.add_argument('--n_samples', default=100, type=int, help='number of image samples to generate')
#     parser.add_argument('--device', default='cuda', type=str, help='type of device', choices=['cpu', 'cuda'])
#     parser.add_argument('--n_threads', default=8, type=int, help='number of threads')
#     parser.add_argument('--seed', default=42, type=int, help='seed for reproducibility')
#     parser.add_argument('--log_interval', default=1000, type=int, help='intervals to log')
#     parser.add_argument('--save_interval', default=1000, type=int, help='intervals to save the model(s)')
#     parser.add_argument('--verbose', type=bool, default=True)
# 
#     return parser
# 
# Path: awesome_gans/utils.py
# def set_seed(seed: int):
#     random.seed(seed)
#     np.random.seed(seed)
#     os.environ['PYTHONHASHSEED'] = str(seed)
# 
#     tf.random.set_seed(seed)


from awesome_gans.config import parse_args
from awesome_gans.utils import set_seed


def main():
    config = parse_args()

    set_seed(config.seed)

    if config.mode == 'train':
        pass
    elif config.mode == 'inference':

# Path: awesome_gans/config.py
# def parse_args():
#     parser = ArgumentParser(description='Awesome-GANs Arguments')
# 
#     # dataset
#     parser.add_argument('--width', type=int, default=32, help='width of image')
#     parser.add_argument('--height', type=int, default=32, help='height of image')
#     parser.add_argument('--n_channels', type=int, default=3, help='number of channel of image')
#     parser.add_argument('--root_path', type=str, default='./', help='root path')
#     parser.add_argument(
#         '--dataset',
#         type=str,
#         default='cifar10',
#         choices=['mnist', 'cifar10', 'cifar100', 'div2k'],
#         help='type of dataset',
#     )
#     parser.add_argument('--mnist_path', type=str, default='mnist')
#     parser.add_argument('--fashion_mnist_path', type=str, default='fashion-mnist')
#     parser.add_argument('--cifar10_path', type=str, default='cifar10')
#     parser.add_argument('--cifar100_path', type=str, default='cifar100')
#     parser.add_argument('--celeba_path', type=str, default='CelebA')
#     parser.add_argument('--celeba_hq_path', type=str, default='CelebA-HQ')
#     parser.add_argument('--div2k_path', type=str, default='DIV2K')
#     parser.add_argument('--pix2pix_path', type=str, default='pix2pix')
#     parser.add_argument('--use_crop', type=bool, default=False, help='use image center crop')
#     parser.add_argument('--model_path', type=str, default='model')
#     parser.add_argument('--output_path', type=str, default='outputs')
# 
#     # misc
#     parser.add_argument('--mode', default='train', type=str, choices=['train', 'inference'])
#     parser.add_argument('--n_samples', default=100, type=int, help='number of image samples to generate')
#     parser.add_argument('--device', default='cuda', type=str, help='type of device', choices=['cpu', 'cuda'])
#     parser.add_argument('--n_threads', default=8, type=int, help='number of threads')
#     parser.add_argument('--seed', default=42, type=int, help='seed for reproducibility')
#     parser.add_argument('--log_interval', default=1000, type=int, help='intervals to log')
#     parser.add_argument('--save_interval', default=1000, type=int, help='intervals to save the model(s)')
#     parser.add_argument('--verbose', type=bool, default=True)
# 
#     return parser
# 
# Path: awesome_gans/utils.py
# def set_seed(seed: int):
#     random.seed(seed)
#     np.random.seed(seed)
#     os.environ['PYTHONHASHSEED'] = str(seed)
# 
#     tf.random.set_seed(seed)


# Path: awesome_gans/acgan/__main__.py
from awesome_gans.config import parse_args
from awesome_gans.utils import set_seed



def main():
    config = parse_args()

    set_seed(config.seed)

    if config.mode == 'train':
        pass
    elif config.mode == 'inference':

        pass