def get_args():
parser = argparse.ArgumentParser()
parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')
parser.add_argument('--load', help='load model')
parser.add_argument('--sample',
action='store_true',
help='view generated examples')
parser.add_argument('--data', help='a jpeg directory')
parser.add_argument('--load-size',
help='size to load the original images',
type=int)
parser.add_argument('--crop-size',
help='crop the original images',
type=int)
args = parser.parse_args()
use_global_argument(args)
if args.gpu:
os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
return args
img = func([[z]])[0][0][:, :, ::-1]
img = (img + 1) * 128
imgs.append(img)
viz = next(build_patch_list(imgs, nr_row=1, nr_col=4, viz=True))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')
parser.add_argument('--load', help='load model')
parser.add_argument('--sample', action='store_true', help='run sampling')
parser.add_argument('--vec',
action='store_true',
help='run vec arithmetic demo')
parser.add_argument(
'--data', help='`image_align_celeba` directory of the celebA dataset')
args = parser.parse_args()
use_global_argument(args)
if args.gpu:
os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
if args.sample:
sample(args.load)
elif args.vec:
vec(args.load)
else:
assert args.data
config = get_config()
if args.load:
config.session_init = SaverRestore(args.load)
GANTrainer(config, g_vs_d=1).train()