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[CI]: Upgrade pre commit hooks in master (#8964)
* Upgrade the versions of pre-commit-hooks * Upgrade setup.cfg * Upgrade setup.cfg
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.pre-commit-config.yaml

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

docs/en/changelog.md

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

docs/en/tutorials/data_pipeline.md

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

mmdet/core/bbox/samplers/sampling_result.py

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from mmdet.core.bbox.samplers.random_sampler import RandomSampler
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rng = demodata.ensure_rng(rng)
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# make probabalistic?
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# make probabilistic?
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num = 32
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pos_fraction = 0.5
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neg_pos_ub = -1
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if gt_labels is None:
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add_gt_as_proposals = False
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else:
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add_gt_as_proposals = True # make probabalistic?
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add_gt_as_proposals = True # make probabilistic?
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sampler = RandomSampler(
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num,

mmdet/models/losses/focal_loss.py

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alpha=0.25,
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reduction='mean',
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avg_factor=None):
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r"""A warpper of cuda version `Focal Loss
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r"""A wrapper of cuda version `Focal Loss
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<https://arxiv.org/abs/1708.02002>`_.
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Args:

mmdet/models/losses/mse_loss.py

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@weighted_loss
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def mse_loss(pred, target):
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"""Warpper of mse loss."""
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"""Wrapper of mse loss."""
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return F.mse_loss(pred, target, reduction='none')
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setup.cfg

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

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