def main():
# parse command line and run
parser = utils.prepare_parser()
parser = utils.add_sample_parser(parser)
config = vars(parser.parse_args())
print(config)
run(config)
def get_config(args):
parser = utils.prepare_parser()
parser = utils.add_sample_parser(parser)
config = vars(parser.parse_args())
resolution = utils.imsize_dict[args.dataset]
attn_dict = {128: '64', 256: '128', 512: '64'}
dim_z_dict = {128: 120, 256: 140, 512: 128}
# See: https://github.com/ajbrock/BigGAN-PyTorch/blob/master/scripts/sample_BigGAN_bs256x8.sh.
config["resolution"] = resolution
config["n_classes"] = utils.nclass_dict[args.dataset]
config["G_activation"] = utils.activation_dict["inplace_relu"]
config["D_activation"] = utils.activation_dict["inplace_relu"]
config["G_attn"] = attn_dict[resolution]
config["D_attn"] = "64"
config["G_ch"] = 96
config["D_ch"] = 96
config["hier"] = True
config["dim_z"] = dim_z_dict[resolution]
config["shared_dim"] = 128
config["G_shared"] = True
config = utils.update_config_roots(config)
config["skip_init"] = True
config["no_optim"] = True
config["device"] = "cuda"
return config
def main():
# parse command line and run
parser = utils.prepare_parser()
parser = utils.add_sample_parser(parser)
config = vars(parser.parse_args())
# print("reached_main")
# for item in config:
# print(item, config[item])
run(config)
def main():
# parse command line and run
parser = utils.prepare_parser()
parser = utils.add_sample_parser(parser)
config = vars(parser.parse_args())
print(config)
if config['sample_multiple']:
suffixes = config['load_weights'].split(',')
for suffix in suffixes:
config['load_weights'] = suffix
run(config)
else:
run(config)
def main():
parser = utils.prepare_parser()
parser = utils.add_sample_parser(parser)
config = vars(parser.parse_args())
print(config)
run(config)
