def process_args():
"""
Parse input arguments
:return:
"""
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"--model_path",
type=str,
default="../experiments/best_model/v2/iteration_71955.ckpt-71955",
help="pre-train best model")
parser.add_argument("--file_name",
type=str,
default="F:\\dataset\\cifar10\\train\\11093.png",
help="test image to class")
parser.add_argument('-c',
'--config',
metavar='C',
default='../config/cifar10_config.json',
help='The Configuration file')
args = parser.parse_args()
config = process_config(args.config)
return args, config
logger.info(
" Validation step {} : Validation Accuracy = {:.4f}".
format(step, mean_val_acc))
train_writer.close()
val_writer.close()
logger.info("Optimization finish!")
if __name__ == "__main__":
# capture the config path from the run arguments
# then process the json configuration file
try:
args = get_args()
config = process_config(args.config)
except:
print("missing or invalid arguments")
exit(0)
# create the experiments dirs
create_dirs([config.summary_dir, config.ckpt_dir])
# create logger info
global logger
logger = setup_logger("TF_cifar10", config.ckpt_dir, "train_cifar10_")
logger.info(config)
main(config)
logger.info("---------Train Finished !----------")