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[Refactor]: change config content (open-mmlab#8635)
* repair config content * update * replace metafile Name * update tests
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‎configs/albu_example/README.md‎

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| Backbone | Style | Lr schd | Mem (GB) | Inf time (fps) | box AP | mask AP | Config | Download |
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| :------: | :-----: | :-----: | :------: | :------------: | :----: | :-----: | :--------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| R-50 | pytorch | 1x | 4.4 | 16.6 | 38.0 | 34.5 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/albu_example/mask_rcnn_r50_fpn_albu_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/albu_example/mask_rcnn_r50_fpn_albu_1x_coco/mask_rcnn_r50_fpn_albu_1x_coco_20200208-ab203bcd.pth) \| [log](https://download.openmmlab.com/mmdetection/v2.0/albu_example/mask_rcnn_r50_fpn_albu_1x_coco/mask_rcnn_r50_fpn_albu_1x_coco_20200208_225520.log.json) |
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| R-50 | pytorch | 1x | 4.4 | 16.6 | 38.0 | 34.5 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/albu_example/mask-rcnn_r50_fpn_albu-1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/albu_example/mask_rcnn_r50_fpn_albu_1x_coco/mask_rcnn_r50_fpn_albu_1x_coco_20200208-ab203bcd.pth) \| [log](https://download.openmmlab.com/mmdetection/v2.0/albu_example/mask_rcnn_r50_fpn_albu_1x_coco/mask_rcnn_r50_fpn_albu_1x_coco_20200208_225520.log.json) |
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## Citation
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‎configs/albu_example/mask-rcnn_r50_fpn_albu-1x_coco.py‎

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_base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
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_base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
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albu_train_transforms = [
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dict(

‎configs/atss/atss_r101_fpn_8xb8-amp-lsj-200e_coco.py‎

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_base_ = './atss_r50_fpn_lsj_200e_8x8_fp16_coco.py'
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_base_ = './atss_r50_fpn_8xb8-amp-lsj-200e_coco.py'
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model = dict(
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backbone=dict(

‎configs/atss/atss_r18_fpn_8xb8-amp-lsj-200e_coco.py‎

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_base_ = './atss_r50_fpn_lsj_200e_8x8_fp16_coco.py'
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_base_ = './atss_r50_fpn_8xb8-amp-lsj-200e_coco.py'
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model = dict(
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backbone=dict(

‎configs/atss/atss_r50_fpn_8xb8-amp-lsj-200e_coco.py‎

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_base_ = '../common/lsj_200e_coco_detection.py'
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_base_ = '../common/lsj-200e_coco-detection.py'
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image_size = (1024, 1024)
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batch_augments = [dict(type='BatchFixedSizePad', size=image_size)]

‎configs/autoassign/README.md‎

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## Results and Models
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| Backbone | Style | Lr schd | Mem (GB) | box AP | Config | Download |
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| :------: | :---: | :-----: | :------: | :----: | :-------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| R-50 | caffe | 1x | 4.08 | 40.4 | [config](./autoassign_r50_caffe_fpn_8x2_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/autoassign/auto_assign_r50_fpn_1x_coco/auto_assign_r50_fpn_1x_coco_20210413_115540-5e17991f.pth) \| [log](https://download.openmmlab.com/mmdetection/v2.0/autoassign/auto_assign_r50_fpn_1x_coco/auto_assign_r50_fpn_1x_coco_20210413_115540-5e17991f.log.json) |
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| Backbone | Style | Lr schd | Mem (GB) | box AP | Config | Download |
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| :------: | :---: | :-----: | :------: | :----: | :---------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| R-50 | caffe | 1x | 4.08 | 40.4 | [config](./autoassign_r50-caffe_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/autoassign/auto_assign_r50_fpn_1x_coco/auto_assign_r50_fpn_1x_coco_20210413_115540-5e17991f.pth) \| [log](https://download.openmmlab.com/mmdetection/v2.0/autoassign/auto_assign_r50_fpn_1x_coco/auto_assign_r50_fpn_1x_coco_20210413_115540-5e17991f.log.json) |
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**Note**:
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‎configs/autoassign/metafile.yml‎

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Version: v2.12.0
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Models:
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- Name: autoassign_r50_caffe_fpn_8x2_1x_coco
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- Name: autoassign_r50-caffe_fpn_1x_coco
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In Collection: AutoAssign
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Config: configs/autoassign/autoassign_r50_caffe_fpn_8x2_1x_coco.py
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Config: configs/autoassign/autoassign_r50-caffe_fpn_1x_coco.py
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Metadata:
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Training Memory (GB): 4.08
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Epochs: 12

‎configs/carafe/README.md‎

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| Method | Backbone | Style | Lr schd | Test Proposal Num | Inf time (fps) | Box AP | Mask AP | Config | Download |
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| :--------------------: | :------: | :-----: | :-----: | :---------------: | :------------: | :----: | :-----: | :------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| Faster R-CNN w/ CARAFE | R-50-FPN | pytorch | 1x | 1000 | 16.5 | 38.6 | 38.6 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/carafe/faster_rcnn_r50_fpn_carafe_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/carafe/faster_rcnn_r50_fpn_carafe_1x_coco/faster_rcnn_r50_fpn_carafe_1x_coco_bbox_mAP-0.386_20200504_175733-385a75b7.pth) \| [log](https://download.openmmlab.com/mmdetection/v2.0/carafe/faster_rcnn_r50_fpn_carafe_1x_coco/faster_rcnn_r50_fpn_carafe_1x_coco_20200504_175733.log.json) |
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| Faster R-CNN w/ CARAFE | R-50-FPN | pytorch | 1x | 1000 | 16.5 | 38.6 | 38.6 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/carafe/faster-rcnn_r50_fpn-carafe_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/carafe/faster_rcnn_r50_fpn_carafe_1x_coco/faster_rcnn_r50_fpn_carafe_1x_coco_bbox_mAP-0.386_20200504_175733-385a75b7.pth) \| [log](https://download.openmmlab.com/mmdetection/v2.0/carafe/faster_rcnn_r50_fpn_carafe_1x_coco/faster_rcnn_r50_fpn_carafe_1x_coco_20200504_175733.log.json) |
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| - | - | - | - | 2000 | | | | | |
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| Mask R-CNN w/ CARAFE | R-50-FPN | pytorch | 1x | 1000 | 14.0 | 39.3 | 35.8 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/carafe/mask_rcnn_r50_fpn_carafe_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/carafe/mask_rcnn_r50_fpn_carafe_1x_coco/mask_rcnn_r50_fpn_carafe_1x_coco_bbox_mAP-0.393__segm_mAP-0.358_20200503_135957-8687f195.pth) \| [log](https://download.openmmlab.com/mmdetection/v2.0/carafe/mask_rcnn_r50_fpn_carafe_1x_coco/mask_rcnn_r50_fpn_carafe_1x_coco_20200503_135957.log.json) |
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| Mask R-CNN w/ CARAFE | R-50-FPN | pytorch | 1x | 1000 | 14.0 | 39.3 | 35.8 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/carafe/mask-rcnn_r50_fpn-carafe_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/carafe/mask_rcnn_r50_fpn_carafe_1x_coco/mask_rcnn_r50_fpn_carafe_1x_coco_bbox_mAP-0.393__segm_mAP-0.358_20200503_135957-8687f195.pth) \| [log](https://download.openmmlab.com/mmdetection/v2.0/carafe/mask_rcnn_r50_fpn_carafe_1x_coco/mask_rcnn_r50_fpn_carafe_1x_coco_20200503_135957.log.json) |
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| - | - | - | - | 2000 | | | | | |
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## Implementation

‎configs/carafe/faster-rcnn_r50_fpn-carafe_1x_coco.py‎

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_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
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_base_ = '../faster_rcnn/faster-rcnn_r50_fpn_1x_coco.py'
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model = dict(
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data_preprocessor=dict(pad_size_divisor=64),
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neck=dict(

‎configs/carafe/mask-rcnn_r50_fpn-carafe_1x_coco.py‎

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_base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
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_base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
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model = dict(
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data_preprocessor=dict(pad_size_divisor=64),
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neck=dict(

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