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# Copyright (c) OpenMMLab. All rights reserved.
import argparse
import logging
import os
import os.path as osp
from types import FunctionType
from mmengine import print_log
from mmengine.config import Config, DictAction
from mmengine.registry import RUNNERS
from mmengine.runner import Runner
from xtuner.configs import cfgs_name_path
from xtuner.model.utils import guess_load_checkpoint
from xtuner.registry import MAP_FUNC
from mmengine.model import is_model_wrapper
def parse_args():
parser = argparse.ArgumentParser(description='Test model')
parser.add_argument('config', help='config file name or path.')
parser.add_argument('--checkpoint', default=None, help='checkpoint file')
parser.add_argument(
'--work-dir',
help='the directory to save the file containing evaluation metrics')
parser.add_argument(
'--cfg-options',
nargs='+',
action=DictAction,
help='override some settings in the used config, the key-value pair '
'in xxx=yyy format will be merged into config file. If the value to '
'be overwritten is a list, it should be like key="[a,b]" or key=a,b '
'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" '
'Note that the quotation marks are necessary and that no white space '
'is allowed.')
parser.add_argument(
'--deepspeed',
default=None,
help='Dummy option'
)
parser.add_argument(
'--launcher',
choices=['none', 'pytorch', 'slurm', 'mpi'],
default='none',
help='job launcher')
parser.add_argument('--local_rank', '--local-rank', type=int, default=0)
args = parser.parse_args()
if 'LOCAL_RANK' not in os.environ:
os.environ['LOCAL_RANK'] = str(args.local_rank)
return args
def register_function(cfg_dict):
if isinstance(cfg_dict, dict):
for key, value in dict.items(cfg_dict):
if isinstance(value, FunctionType):
value_str = str(value)
if value_str not in MAP_FUNC:
MAP_FUNC.register_module(module=value, name=value_str)
cfg_dict[key] = value_str
else:
register_function(value)
elif isinstance(cfg_dict, (list, tuple)):
for value in cfg_dict:
register_function(value)
def main():
args = parse_args()
if args.deepspeed is not None:
print_log("Deepspeed is not adopted during inference, Skipped.", level=logging.WARN)
# parse config
if not osp.isfile(args.config):
try:
args.config = cfgs_name_path[args.config]
except KeyError:
raise FileNotFoundError(f'Cannot find {args.config}')
# load config
cfg = Config.fromfile(args.config)
cfg.launcher = args.launcher
if args.cfg_options is not None:
cfg.merge_from_dict(args.cfg_options)
# register FunctionType object in cfg to `MAP_FUNC` Registry and
# change these FunctionType object to str
register_function(cfg._cfg_dict)
# work_dir is determined in this priority: CLI > segment in file > filename
if args.work_dir is not None:
# update configs according to CLI args if args.work_dir is not None
cfg.work_dir = args.work_dir
elif cfg.get('work_dir', None) is None:
# use config filename as default work_dir if cfg.work_dir is None
cfg.work_dir = osp.join('./work_dirs',
osp.splitext(osp.basename(args.config))[0])
# build the runner from config
if 'runner_type' not in cfg:
# build the default runner
runner = Runner.from_cfg(cfg)
else:
# build customized runner from the registry
# if 'runner_type' is set in the cfg
runner = RUNNERS.build(cfg)
if args.checkpoint is not None:
state_dict = guess_load_checkpoint(args.checkpoint)
if is_model_wrapper(runner.model):
runner.model.module.load_state_dict(state_dict, strict=False)
else:
runner.model.load_state_dict(state_dict, strict=False)
runner.logger.info(f'Load checkpoint from {args.checkpoint}')
else:
Warning("No checkpoint !!!")
# start testing
runner.test()
if __name__ == '__main__':
main()