# 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()