Remove redundant code (open-mmlab#310)

* resolve comments

* update changelog

* remove redundant code

* update

tools/test.py

@@ -7,6 +7,7 @@
 import torch
 from mmcv import Config, DictAction
 from mmcv.cnn import fuse_conv_bn
+from mmcv.fileio.io import file_handlers
 from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
 from mmcv.runner import get_dist_info, init_dist, load_checkpoint
 from mmcv.runner.fp16_utils import wrap_fp16_model
@@ -92,17 +93,6 @@ def parse_args():
     return args
 
 
-def merge_configs(cfg1, cfg2):
-    # Merge cfg2 into cfg1
-    # Overwrite cfg1 if repeated, ignore if value is None.
-    cfg1 = {} if cfg1 is None else cfg1.copy()
-    cfg2 = {} if cfg2 is None else cfg2
-    for k, v in cfg2.items():
-        if v:
-            cfg1[k] = v
-    return cfg1
-
-
 def main():
     args = parse_args()
 
@@ -113,19 +103,27 @@ def main():
     # Load output_config from cfg
     output_config = cfg.get('output_config', {})
     # Overwrite output_config from args.out
-    output_config = merge_configs(output_config, dict(out=args.out))
+    output_config = Config._merge_a_into_b(dict(out=args.out), output_config)
 
     # Load eval_config from cfg
     eval_config = cfg.get('eval_config', {})
     # Overwrite eval_config from args.eval
-    eval_config = merge_configs(eval_config, dict(metrics=args.eval))
+    eval_config = Config._merge_a_into_b(dict(metrics=args.eval), eval_config)
     # Add options from args.eval_options
-    eval_config = merge_configs(eval_config, args.eval_options)
+    eval_config = Config._merge_a_into_b(args.eval_options, eval_config)
 
     assert output_config or eval_config, \
         ('Please specify at least one operation (save or eval the '
          'results) with the argument "--out" or "--eval"')
 
+    if output_config:
+        out = output_config['out']
+        # make sure the dirname of the output path exists
+        mmcv.mkdir_or_exist(osp.dirname(out))
+        _, suffix = osp.splitext(out)
+        assert suffix in file_handlers, \
+            'The format of the output file should be json, pickle or yaml'
+
     # set cudnn benchmark
     if cfg.get('cudnn_benchmark', False):
         torch.backends.cudnn.benchmark = True
@@ -146,8 +144,6 @@ def main():
         distributed = True
         init_dist(args.launcher, **cfg.dist_params)
 
-    # create work_dir
-    mmcv.mkdir_or_exist(osp.abspath(cfg.work_dir))
     # build the dataloader
     dataset = build_dataset(cfg.data.test, dict(test_mode=True))
     dataloader_setting = dict(