We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Localizer train cfg & test cfg ?


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `configs/_base_/models/bsn_tem.py`
Content:
```
1 # model settings
2 model = dict(
3     type='TEM',
4     temporal_dim=100,
5     boundary_ratio=0.1,
6     tem_feat_dim=400,
7     tem_hidden_dim=512,
8     tem_match_threshold=0.5)
9 # model training and testing settings
10 train_cfg = None
11 test_cfg = dict(average_clips='score')
12
```

Path: `configs/_base_/models/bsn_pem.py`
Content:
```
1 # model settings
2 model = dict(
3     type='PEM',
4     pem_feat_dim=32,
5     pem_hidden_dim=256,
6     pem_u_ratio_m=1,
7     pem_u_ratio_l=2,
8     pem_high_temporal_iou_threshold=0.6,
9     pem_low_temporal_iou_threshold=0.2,
10     soft_nms_alpha=0.75,
11     soft_nms_low_threshold=0.65,
12     soft_nms_high_threshold=0.9,
13     post_process_top_k=100)
14 # model training and testing settings
15 train_cfg = None
16 test_cfg = dict(average_clips='score')
17
```

Path: `configs/_base_/models/bmn_400x100.py`
Content:
```
1 # model settings
2 model = dict(
3     type='BMN',
4     temporal_dim=100,
5     boundary_ratio=0.5,
6     num_samples=32,
7     num_samples_per_bin=3,
8     feat_dim=400,
9     soft_nms_alpha=0.4,
10     soft_nms_low_threshold=0.5,
11     soft_nms_high_threshold=0.9,
12     post_process_top_k=100)
13 # model training and testing settings
14 train_cfg = None
15 test_cfg = dict(average_clips='score')
16
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/configs/_base_/models/bmn_400x100.py b/configs/_base_/models/bmn_400x100.py
--- a/configs/_base_/models/bmn_400x100.py
+++ b/configs/_base_/models/bmn_400x100.py
@@ -10,6 +10,3 @@
     soft_nms_low_threshold=0.5,
     soft_nms_high_threshold=0.9,
     post_process_top_k=100)
-# model training and testing settings
-train_cfg = None
-test_cfg = dict(average_clips='score')
diff --git a/configs/_base_/models/bsn_pem.py b/configs/_base_/models/bsn_pem.py
--- a/configs/_base_/models/bsn_pem.py
+++ b/configs/_base_/models/bsn_pem.py
@@ -11,6 +11,3 @@
     soft_nms_low_threshold=0.65,
     soft_nms_high_threshold=0.9,
     post_process_top_k=100)
-# model training and testing settings
-train_cfg = None
-test_cfg = dict(average_clips='score')
diff --git a/configs/_base_/models/bsn_tem.py b/configs/_base_/models/bsn_tem.py
--- a/configs/_base_/models/bsn_tem.py
+++ b/configs/_base_/models/bsn_tem.py
@@ -6,6 +6,3 @@
     tem_feat_dim=400,
     tem_hidden_dim=512,
     tem_match_threshold=0.5)
-# model training and testing settings
-train_cfg = None
-test_cfg = dict(average_clips='score')

{"golden_diff": "diff --git a/configs/_base_/models/bmn_400x100.py b/configs/_base_/models/bmn_400x100.py\n--- a/configs/_base_/models/bmn_400x100.py\n+++ b/configs/_base_/models/bmn_400x100.py\n@@ -10,6 +10,3 @@\n     soft_nms_low_threshold=0.5,\n     soft_nms_high_threshold=0.9,\n     post_process_top_k=100)\n-# model training and testing settings\n-train_cfg = None\n-test_cfg = dict(average_clips='score')\ndiff --git a/configs/_base_/models/bsn_pem.py b/configs/_base_/models/bsn_pem.py\n--- a/configs/_base_/models/bsn_pem.py\n+++ b/configs/_base_/models/bsn_pem.py\n@@ -11,6 +11,3 @@\n     soft_nms_low_threshold=0.65,\n     soft_nms_high_threshold=0.9,\n     post_process_top_k=100)\n-# model training and testing settings\n-train_cfg = None\n-test_cfg = dict(average_clips='score')\ndiff --git a/configs/_base_/models/bsn_tem.py b/configs/_base_/models/bsn_tem.py\n--- a/configs/_base_/models/bsn_tem.py\n+++ b/configs/_base_/models/bsn_tem.py\n@@ -6,6 +6,3 @@\n     tem_feat_dim=400,\n     tem_hidden_dim=512,\n     tem_match_threshold=0.5)\n-# model training and testing settings\n-train_cfg = None\n-test_cfg = dict(average_clips='score')\n", "issue": "Localizer train cfg & test cfg ?\n\n", "before_files": [{"content": "# model settings\nmodel = dict(\n    type='TEM',\n    temporal_dim=100,\n    boundary_ratio=0.1,\n    tem_feat_dim=400,\n    tem_hidden_dim=512,\n    tem_match_threshold=0.5)\n# model training and testing settings\ntrain_cfg = None\ntest_cfg = dict(average_clips='score')\n", "path": "configs/_base_/models/bsn_tem.py"}, {"content": "# model settings\nmodel = dict(\n    type='PEM',\n    pem_feat_dim=32,\n    pem_hidden_dim=256,\n    pem_u_ratio_m=1,\n    pem_u_ratio_l=2,\n    pem_high_temporal_iou_threshold=0.6,\n    pem_low_temporal_iou_threshold=0.2,\n    soft_nms_alpha=0.75,\n    soft_nms_low_threshold=0.65,\n    soft_nms_high_threshold=0.9,\n    post_process_top_k=100)\n# model training and testing settings\ntrain_cfg = None\ntest_cfg = dict(average_clips='score')\n", "path": "configs/_base_/models/bsn_pem.py"}, {"content": "# model settings\nmodel = dict(\n    type='BMN',\n    temporal_dim=100,\n    boundary_ratio=0.5,\n    num_samples=32,\n    num_samples_per_bin=3,\n    feat_dim=400,\n    soft_nms_alpha=0.4,\n    soft_nms_low_threshold=0.5,\n    soft_nms_high_threshold=0.9,\n    post_process_top_k=100)\n# model training and testing settings\ntrain_cfg = None\ntest_cfg = dict(average_clips='score')\n", "path": "configs/_base_/models/bmn_400x100.py"}], "after_files": [{"content": "# model settings\nmodel = dict(\n    type='TEM',\n    temporal_dim=100,\n    boundary_ratio=0.1,\n    tem_feat_dim=400,\n    tem_hidden_dim=512,\n    tem_match_threshold=0.5)\n", "path": "configs/_base_/models/bsn_tem.py"}, {"content": "# model settings\nmodel = dict(\n    type='PEM',\n    pem_feat_dim=32,\n    pem_hidden_dim=256,\n    pem_u_ratio_m=1,\n    pem_u_ratio_l=2,\n    pem_high_temporal_iou_threshold=0.6,\n    pem_low_temporal_iou_threshold=0.2,\n    soft_nms_alpha=0.75,\n    soft_nms_low_threshold=0.65,\n    soft_nms_high_threshold=0.9,\n    post_process_top_k=100)\n", "path": "configs/_base_/models/bsn_pem.py"}, {"content": "# model settings\nmodel = dict(\n    type='BMN',\n    temporal_dim=100,\n    boundary_ratio=0.5,\n    num_samples=32,\n    num_samples_per_bin=3,\n    feat_dim=400,\n    soft_nms_alpha=0.4,\n    soft_nms_low_threshold=0.5,\n    soft_nms_high_threshold=0.9,\n    post_process_top_k=100)\n", "path": "configs/_base_/models/bmn_400x100.py"}]}