config_filename = os.path.expanduser("~/.hypergan/configs/"+config_name+".json")
print("Saving config to ", config_filename)
hc.Selector().save(config_filename, config)
class TwoImageInput():
def create(self, args):
self.inputsa = hg.inputs.image_loader.ImageLoader(args.batch_size)
After Change
from hypergan.samplers.random_walk_sampler import RandomWalkSampler
arg_parser = ArgumentParser("Align two unaligned distributions. One is black and white of image.")
arg_parser.add_image_arguments()
args = arg_parser.parse_args()
width, height, channels = parse_size(args.size)
config = lookup_config(args)
save_file = "save/model.ckpt"
if args.action == "search":
config = AlignedRandomSearch({}).random_config()
if args.config_list is not None:
lines = tuple(open(args.config_list, "r"))
config_file = random.choice(lines).strip()
config = hg.configuration.Configuration.load(config_file+".json")
random_config = AlignedRandomSearch({}).random_config()
config["generator"]=random_config["generator"]
config["discriminator"]=random_config["discriminator"]
// TODO Other search terms?
print("config list chosen", config_file)
