clean unnecessary custom_imports (#1068)

tools/analysis_tools/get_flops.py

@@ -62,10 +62,6 @@ def main():
     cfg = Config.fromfile(args.config)
     if args.cfg_options is not None:
         cfg.merge_from_dict(args.cfg_options)
-    # import modules from string list.
-    if cfg.get('custom_imports', None):
-        from mmcv.utils import import_modules_from_strings
-        import_modules_from_strings(**cfg['custom_imports'])
 
     model = build_model(
         cfg.model,

tools/misc/browse_dataset.py

@@ -55,10 +55,6 @@ def build_data_cfg(config_path, skip_type, cfg_options):
     cfg = Config.fromfile(config_path)
     if cfg_options is not None:
         cfg.merge_from_dict(cfg_options)
-    # import modules from string list.
-    if cfg.get('custom_imports', None):
-        from mmcv.utils import import_modules_from_strings
-        import_modules_from_strings(**cfg['custom_imports'])
     # extract inner dataset of `RepeatDataset` as `cfg.data.train`
     # so we don't need to worry about it later
     if cfg.data.train['type'] == 'RepeatDataset':

tools/test.py

@@ -117,10 +117,6 @@ def main():
     cfg = Config.fromfile(args.config)
     if args.cfg_options is not None:
         cfg.merge_from_dict(args.cfg_options)
-    # import modules from string list.
-    if cfg.get('custom_imports', None):
-        from mmcv.utils import import_modules_from_strings
-        import_modules_from_strings(**cfg['custom_imports'])
     # set cudnn_benchmark
     if cfg.get('cudnn_benchmark', False):
         torch.backends.cudnn.benchmark = True

tools/train.py

@@ -97,10 +97,6 @@ def main():
     cfg = Config.fromfile(args.config)
     if args.cfg_options is not None:
         cfg.merge_from_dict(args.cfg_options)
-    # import modules from string list.
-    if cfg.get('custom_imports', None):
-        from mmcv.utils import import_modules_from_strings
-        import_modules_from_strings(**cfg['custom_imports'])
 
     # set cudnn_benchmark
     if cfg.get('cudnn_benchmark', False):