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test.py
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import argparse
import os
import os.path as osp
from mmengine.config import Config, DictAction
from mmengine.runner import Runner
def parse_args():
parser = argparse.ArgumentParser(
description='STL test (and eval) a model')
parser.add_argument(
'--config',
help='test config file path, this is not required in the test-best or test-last mode')
parser.add_argument(
'--checkpoint',
help='checkpoint file, this is not required in the test-best or test-last mode')
parser.add_argument(
'--work-dir',
help='the directory to save the file containing evaluation metrics')
parser.add_argument(
'--test-best', action='store_true', default=False,
help='test the best ckpt saved in the work-dir, cannot meanwhile be True with test-last')
parser.add_argument(
'--test-last', action='store_true', default=False,
help='test the last ckpt saved in the work-dir, cannot meanwhile be True with test-best')
parser.add_argument(
'--metric-only', action='store_true', default=False,
help='only calculate the metrics for the model without calculating complexity info'
)
parser.add_argument(
'--dump',
type=str,
help='dump predictions to a pickle file for offline evaluation')
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(
'--show-dir',
help='directory where the visualization images will be saved.')
parser.add_argument(
'--show',
action='store_true',
help='whether to display the prediction results in a window.')
parser.add_argument(
'--interval',
type=int,
default=1,
help='visualize per interval samples.')
parser.add_argument(
'--wait-time',
type=float,
default=2,
help='display time of every window. (second)')
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 merge_args(cfg, args):
"""Merge CLI arguments to config."""
# -------------------- visualization --------------------
if args.show or (args.show_dir is not None):
assert 'visualization' in cfg.default_hooks, \
'VisualizationHook is not set in the `default_hooks` field of ' \
'config. Please set `visualization=dict(type="VisualizationHook")`'
cfg.default_hooks.visualization.enable = True
cfg.default_hooks.visualization.show = args.show
cfg.default_hooks.visualization.wait_time = args.wait_time
cfg.default_hooks.visualization.out_dir = args.show_dir
cfg.default_hooks.visualization.interval = args.interval
# -------------------- Dump predictions --------------------
if args.dump is not None:
assert args.dump.endswith(('.pkl', '.pickle')), \
'The dump file must be a pkl file.'
dump_metric = dict(type='DumpResults', out_file_path=args.dump)
if isinstance(cfg.test_evaluator, (list, tuple)):
cfg.test_evaluator = list(cfg.test_evaluator)
cfg.test_evaluator.append(dump_metric)
else:
cfg.test_evaluator = [cfg.test_evaluator, dump_metric]
return cfg
def main():
args = parse_args()
config = getattr(args, 'config', None)
assert not (args.test_best and args.test_last)
if args.test_best:
for dir in os.listdir(args.work_dir):
if dir.startswith('bs') and dir.endswith('.py') and config == None:
config = osp.join(args.work_dir, dir)
if dir.endswith('.pth') and dir.startswith('best'):
checkpoint = osp.join(args.work_dir, dir)
elif args.test_last:
for dir in os.listdir(args.work_dir):
if dir.startswith('bs') and dir.endswith('.py') and config == None:
config = osp.join(args.work_dir, dir)
with open(osp.join(args.work_dir, 'last_checkpoint'), 'r') as fp:
checkpoint = fp.read()
else:
checkpoint = args.checkpoint
# load config
cfg = Config.fromfile(config)
cfg = merge_args(cfg, args)
cfg.launcher = args.launcher
if args.cfg_options is not None:
cfg.merge_from_dict(args.cfg_options)
# 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(config))[0])
cfg.load_from = checkpoint
if hasattr(cfg, 'visualizer'):
cfg.visualizer = None
# build the runner from config
runner = Runner.from_cfg(cfg)
# calculate the complexity info for the model
if not args.metric_only:
from tools.complexity_analysis import get_model_computational_metrics
params_and_flops, fps = get_model_computational_metrics(
runner.model, input_shape=(cfg.input_shape, (cfg.output_len, *cfg.input_shape[1:]))
)
runner.logger.info(params_and_flops)
runner.logger.info(f'fps: {fps}')
# start testing
runner.test()
if __name__ == '__main__':
main()