--- a
+++ b/tools/get_flops.py
@@ -0,0 +1,59 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+import argparse
+
+from mmcv import Config
+from mmcv.cnn import get_model_complexity_info
+
+from mmseg.models import build_segmentor
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='Train a segmentor')
+    parser.add_argument('config', help='train config file path')
+    parser.add_argument(
+        '--shape',
+        type=int,
+        nargs='+',
+        default=[2048, 1024],
+        help='input image size')
+    args = parser.parse_args()
+    return args
+
+
+def main():
+
+    args = parse_args()
+
+    if len(args.shape) == 1:
+        input_shape = (3, args.shape[0], args.shape[0])
+    elif len(args.shape) == 2:
+        input_shape = (3, ) + tuple(args.shape)
+    else:
+        raise ValueError('invalid input shape')
+
+    cfg = Config.fromfile(args.config)
+    cfg.model.pretrained = None
+    model = build_segmentor(
+        cfg.model,
+        train_cfg=cfg.get('train_cfg'),
+        test_cfg=cfg.get('test_cfg')).cuda()
+    model.eval()
+
+    if hasattr(model, 'forward_dummy'):
+        model.forward = model.forward_dummy
+    else:
+        raise NotImplementedError(
+            'FLOPs counter is currently not currently supported with {}'.
+            format(model.__class__.__name__))
+
+    flops, params = get_model_complexity_info(model, input_shape)
+    split_line = '=' * 30
+    print('{0}\nInput shape: {1}\nFlops: {2}\nParams: {3}\n{0}'.format(
+        split_line, input_shape, flops, params))
+    print('!!!Please be cautious if you use the results in papers. '
+          'You may need to check if all ops are supported and verify that the '
+          'flops computation is correct.')
+
+
+if __name__ == '__main__':
+    main()