logger.info("INFO: Starting inference...")
evaluator_engine.run(loader_test)
save_predictions(evaluator_engine,
os.path.splitext(m_cp_path)[0],
accumulate_predictions.state_dict)
if __name__ == "__main__":
parser = ArgumentParser()
parser.add_argument('-c',
'--config',
default=None,
type=str,
required=True,
help='config file path (default: None)')
parser.add_argument('--checkpoint',
default=None,
type=str,
help='Checkpoint to use for test')
args = parser.parse_args()
config = Experiment.load_from_path(args.config)
if args.checkpoint:
config.checkpoint = args.checkpoint
assert config, "Config could not be loaded."
main(config)
parser.add_argument('-c', '--config', default=None, type=str, required=True, help='config file path (default: None)')
parser.add_argument('--checkpoint', default=None, type=str, help='Checkpoint tag to reload')
parser.add_argument('--checkpoint_dir', default=None, type=str, help='Checkpoint directory to reload')
parser.add_argument('--suffix', default=None, type=str, help='Add to the name')
parser.add_argument('--epochs', default=None, type=int, help='Number of epochs')
parser.add_argument('--resume_from', default=None, type=int, help='Epoch to resume from, allows using checkpoints as initialisation')
args = parser.parse_args()
OVERLOADABLE = ['checkpoint', 'epochs', 'checkpoint_dir', 'resume_from']
overloaded = {}
for k, v in vars(args).items():
if (k in OVERLOADABLE) and (v is not None):
overloaded[k] = v
config = Experiment.load_from_path(args.config, overloaded, args.suffix)
assert config, "Config could not be loaded."
# Else load the saved config from the results dir or throw an error if one doesn't exist
if len(config.checkpoint) > 0:
logger.warning("WARNING: --config specifies resuming, overriding config with exising experiment config.")
# resume_config = Experiment(config.name, desc=config.desc, result_dir=config.result_dir).load()
# assert resume_config is not None, "No experiment {} exists, cannot resume training".format(config.name)
# config = resume_config
assert config, "Config could not be loaded for resume"
# If we have resume_from in the config but have it < 0 to start a fresh training run then throw and error if the directory already exists
elif config.overwrite is False:
assert not config.exists(), "Results directory {} already exists! Please specify a new experiment name or the remove old files.".format(config.result_path)
else:
empty_folder(config.result_path)