[CI]: Upgrade pre commit hooks in master (#8964)

* Upgrade the versions of pre-commit-hooks

* Upgrade setup.cfg

* Upgrade setup.cfg

.pre-commit-config.yaml

@@ -1,18 +1,18 @@
 repos:
   - repo: https://github.com/PyCQA/flake8
-    rev: 3.8.3
+    rev: 5.0.4
     hooks:
       - id: flake8
   - repo: https://github.com/PyCQA/isort
     rev: 5.10.1
     hooks:
       - id: isort
   - repo: https://github.com/pre-commit/mirrors-yapf
-    rev: v0.30.0
+    rev: v0.32.0
     hooks:
       - id: yapf
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v3.1.0
+    rev: v4.3.0
     hooks:
       - id: trailing-whitespace
       - id: check-yaml
@@ -25,7 +25,7 @@ repos:
       - id: mixed-line-ending
         args: ["--fix=lf"]
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.1.0
+    rev: v2.2.1
     hooks:
       - id: codespell
   - repo: https://github.com/executablebooks/mdformat

docs/en/changelog.md

@@ -639,7 +639,7 @@ Thanks @Boyden, @onnkeat, @st9007a, @vealocia, @yhcao6, @DapangpangX, @yellowdol
 - Support [PVT](https://arxiv.org/abs/2102.12122) and [PVTv2](https://arxiv.org/abs/2106.13797) (#5780)
 - Support [SOLO](https://arxiv.org/abs/1912.04488) (#5832)
 - Support large scale jittering and New Mask R-CNN baselines (#6132)
-- Add a general data structrue for the results of models (#5508)
+- Add a general data structure for the results of models (#5508)
 - Added a base class for one-stage instance segmentation (#5904)
 - Speed up `YOLOv3` inference (#5991)
 - Release Swin Transformer pre-trained models (#6100)

docs/en/tutorials/data_pipeline.md

@@ -195,5 +195,5 @@ For each operation, we list the related dict fields that are added/updated/remov
 
    To visualize the output of your augmentation pipeline, `tools/misc/browse_dataset.py`
    can help the user to browse a detection dataset (both images and bounding box annotations)
-   visually, or save the image to a designated directory. More detials can refer to
+   visually, or save the image to a designated directory. More details can refer to
    [useful_tools](../useful_tools.md)

mmdet/core/bbox/samplers/sampling_result.py

@@ -117,7 +117,7 @@ def random(cls, rng=None, **kwargs):
         from mmdet.core.bbox.samplers.random_sampler import RandomSampler
         rng = demodata.ensure_rng(rng)
 
-        # make probabalistic?
+        # make probabilistic?
         num = 32
         pos_fraction = 0.5
         neg_pos_ub = -1
@@ -141,7 +141,7 @@ def random(cls, rng=None, **kwargs):
         if gt_labels is None:
             add_gt_as_proposals = False
         else:
-            add_gt_as_proposals = True  # make probabalistic?
+            add_gt_as_proposals = True  # make probabilistic?
 
         sampler = RandomSampler(
             num,

mmdet/models/losses/focal_loss.py

@@ -117,7 +117,7 @@ def sigmoid_focal_loss(pred,
                        alpha=0.25,
                        reduction='mean',
                        avg_factor=None):
-    r"""A warpper of cuda version `Focal Loss
+    r"""A wrapper of cuda version `Focal Loss
     <https://arxiv.org/abs/1708.02002>`_.
 
     Args:

mmdet/models/losses/mse_loss.py

@@ -8,7 +8,7 @@
 
 @weighted_loss
 def mse_loss(pred, target):
-    """Warpper of mse loss."""
+    """Wrapper of mse loss."""
     return F.mse_loss(pred, target, reduction='none')
 
 

setup.cfg

@@ -18,4 +18,4 @@ SPLIT_BEFORE_EXPRESSION_AFTER_OPENING_PAREN = true
 [codespell]
 skip = *.ipynb
 quiet-level = 3
-ignore-words-list = patten,nd,ty,mot,hist,formating,winn,gool,datas,wan,confids,TOOD,tood,ba
+ignore-words-list = patten,nd,ty,mot,hist,formating,winn,gool,datas,wan,confids,TOOD,tood,ba,warmup,nam