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)