prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  Wrong class number for LVIS 1.0 dataset
  **Checklist**
  1. I have searched related issues but cannot get the expected help.
  2. The bug has not been fixed in the latest version.
  
  **Describe the bug**
  Wrong class number for LVIS 1.0 dataset
  
  **Reproduction**
  1. What command or script did you run?
  N.A.
  2. Did you make any modifications on the code or config? Did you understand what you have modified?
  Nope
  3. What dataset did you use?
  LVIS1.0
  
  **Environment**
  N.A.
  
  **Error traceback**
  N.A.
  
  **Bug fix**
  For the config file for LVIS1.0 dataset, the class number should be 1203 instead of 1230 as indicated on the official website:
  https://www.lvisdataset.org/dataset
  
  https://github.com/open-mmlab/mmdetection/blob/9596b9a4c916ae601f9a8a641c3a0ea47265abec/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py#L8
  
  
  --- 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/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py`
  Content:
  ```
  1 _base_ = [
  2     '../_base_/models/mask_rcnn_r50_fpn.py',
  3     '../_base_/datasets/lvis_v1_instance.py',
  4     '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
  5 ]
  6 model = dict(
  7     roi_head=dict(
  8         bbox_head=dict(num_classes=1230), mask_head=dict(num_classes=1230)))
  9 test_cfg = dict(
  10     rcnn=dict(
  11         score_thr=0.0001,
  12         # LVIS allows up to 300
  13         max_per_img=300))
  14 img_norm_cfg = dict(
  15     mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
  16 train_pipeline = [
  17     dict(type='LoadImageFromFile'),
  18     dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
  19     dict(
  20         type='Resize',
  21         img_scale=[(1333, 640), (1333, 672), (1333, 704), (1333, 736),
  22                    (1333, 768), (1333, 800)],
  23         multiscale_mode='value',
  24         keep_ratio=True),
  25     dict(type='RandomFlip', flip_ratio=0.5),
  26     dict(type='Normalize', **img_norm_cfg),
  27     dict(type='Pad', size_divisor=32),
  28     dict(type='DefaultFormatBundle'),
  29     dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']),
  30 ]
  31 data = dict(train=dict(dataset=dict(pipeline=train_pipeline)))
  32
  ```
  --- 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()
  
  ```
  
golden_diff: diff --git a/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py b/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py
  --- a/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py
  +++ b/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py
  @@ -5,7 +5,7 @@
   ]
   model = dict(
       roi_head=dict(
  -        bbox_head=dict(num_classes=1230), mask_head=dict(num_classes=1230)))
  +        bbox_head=dict(num_classes=1203), mask_head=dict(num_classes=1203)))
   test_cfg = dict(
       rcnn=dict(
           score_thr=0.0001,
  
verification_info: {"golden_diff": "diff --git a/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py b/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py\n--- a/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py\n+++ b/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py\n@@ -5,7 +5,7 @@\n ]\n model = dict(\n     roi_head=dict(\n-        bbox_head=dict(num_classes=1230), mask_head=dict(num_classes=1230)))\n+        bbox_head=dict(num_classes=1203), mask_head=dict(num_classes=1203)))\n test_cfg = dict(\n     rcnn=dict(\n         score_thr=0.0001,\n", "issue": "Wrong class number for LVIS 1.0 dataset\n**Checklist**\r\n1. I have searched related issues but cannot get the expected help.\r\n2. The bug has not been fixed in the latest version.\r\n\r\n**Describe the bug**\r\nWrong class number for LVIS 1.0 dataset\r\n\r\n**Reproduction**\r\n1. What command or script did you run?\r\nN.A.\r\n2. Did you make any modifications on the code or config? Did you understand what you have modified?\r\nNope\r\n3. What dataset did you use?\r\nLVIS1.0\r\n\r\n**Environment**\r\nN.A.\r\n\r\n**Error traceback**\r\nN.A.\r\n\r\n**Bug fix**\r\nFor the config file for LVIS1.0 dataset, the class number should be 1203 instead of 1230 as indicated on the official website:\r\nhttps://www.lvisdataset.org/dataset\r\n\r\nhttps://github.com/open-mmlab/mmdetection/blob/9596b9a4c916ae601f9a8a641c3a0ea47265abec/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py#L8\r\n\n", "before_files": [{"content": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/lvis_v1_instance.py',\n    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'\n]\nmodel = dict(\n    roi_head=dict(\n        bbox_head=dict(num_classes=1230), mask_head=dict(num_classes=1230)))\ntest_cfg = dict(\n    rcnn=dict(\n        score_thr=0.0001,\n        # LVIS allows up to 300\n        max_per_img=300))\nimg_norm_cfg = dict(\n    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)\ntrain_pipeline = [\n    dict(type='LoadImageFromFile'),\n    dict(type='LoadAnnotations', with_bbox=True, with_mask=True),\n    dict(\n        type='Resize',\n        img_scale=[(1333, 640), (1333, 672), (1333, 704), (1333, 736),\n                   (1333, 768), (1333, 800)],\n        multiscale_mode='value',\n        keep_ratio=True),\n    dict(type='RandomFlip', flip_ratio=0.5),\n    dict(type='Normalize', **img_norm_cfg),\n    dict(type='Pad', size_divisor=32),\n    dict(type='DefaultFormatBundle'),\n    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']),\n]\ndata = dict(train=dict(dataset=dict(pipeline=train_pipeline)))\n", "path": "configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py"}], "after_files": [{"content": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/lvis_v1_instance.py',\n    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'\n]\nmodel = dict(\n    roi_head=dict(\n        bbox_head=dict(num_classes=1203), mask_head=dict(num_classes=1203)))\ntest_cfg = dict(\n    rcnn=dict(\n        score_thr=0.0001,\n        # LVIS allows up to 300\n        max_per_img=300))\nimg_norm_cfg = dict(\n    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)\ntrain_pipeline = [\n    dict(type='LoadImageFromFile'),\n    dict(type='LoadAnnotations', with_bbox=True, with_mask=True),\n    dict(\n        type='Resize',\n        img_scale=[(1333, 640), (1333, 672), (1333, 704), (1333, 736),\n                   (1333, 768), (1333, 800)],\n        multiscale_mode='value',\n        keep_ratio=True),\n    dict(type='RandomFlip', flip_ratio=0.5),\n    dict(type='Normalize', **img_norm_cfg),\n    dict(type='Pad', size_divisor=32),\n    dict(type='DefaultFormatBundle'),\n    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']),\n]\ndata = dict(train=dict(dataset=dict(pipeline=train_pipeline)))\n", "path": "configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py"}]}