diff --git a/configs/distill/cwd/README.md b/configs/distill/cwd/README.md
index 9033221ce..9328790cd 100644
--- a/configs/distill/cwd/README.md
+++ b/configs/distill/cwd/README.md
@@ -15,12 +15,12 @@ Knowledge distillation (KD) has been proven to be a simple and effective tool fo
### Segmentation
|Location|Dataset|Teacher|Student|mIoU|mIoU(T)|mIou(S)|Config | Download |
:--------:|:---------:|:---------:|:---------:|:---------:|:---------:|:---------:|:------:|:---------|
-| logits |cityscapes|[pspnet_r101](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py)|[pspnet_r18](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r18-d8_512x1024_80k_cityscapes.py)| 75.54 | 79.76 | 74.87 |[config]()|[teacher](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes/pspnet_r101-d8_512x1024_80k_cityscapes_20200606_112211-e1e1100f.pth) |[model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/distill/cwd/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k_mIoU-75.54_20211222-3a26ee1c.pth?versionId=CAEQHxiBgMCPxIKJ7xciIGU1N2JhYzgzYWE0YTRhYmRiZjVmMTA3MTA3NDk1ZWNl) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/distill/cwd/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k_20211212_205711.log.json?versionId=CAEQHxiBgMDZ_oOJ7xciIDJjYzIxYTYyODYzMzQzNDk5Mjg1NTIwMWFkODliMGFk)|
+| logits |cityscapes|[pspnet_r101](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py)|[pspnet_r18](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r18-d8_512x1024_80k_cityscapes.py)| 75.54 | 79.76 | 74.87 |[config]()|[teacher](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes/pspnet_r101-d8_512x1024_80k_cityscapes_20200606_112211-e1e1100f.pth) |[model](https://download.openmmlab.com/mmrazor/v0.1/distill/cwd/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k_mIoU-75.54_20211222-3a26ee1c.pth) | [log](https://download.openmmlab.com/mmrazor/v0.1/distill/cwd/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k_20211212_205711.log.json?)|
### Detection
|Location|Dataset|Teacher|Student|mAP|mAP(T)|mAP(S)|Config | Download |
:--------:|:---------:|:---------:|:---------:|:---------:|:---------:|:---------:|:------:|:---------|
-| cls head |COCO|[gfl_r101_2x](https://github.com/open-mmlab/mmdetection/tree/master/configs/gfl/gfl_r101_fpn_mstrain_2x_coco.py)|[gfl_r50_1x](https://github.com/open-mmlab/mmdetection/tree/master/configs/gfl/gfl_r50_fpn_1x_coco.py)| 41.9 | 44.7 | 40.2 |[config]()|[teacher](https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_r101_fpn_mstrain_2x_coco/gfl_r101_fpn_mstrain_2x_coco_20200629_200126-dd12f847.pth) |[model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/distill/cwd/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco_20211222-655dff39.pth?versionId=CAEQHxiBgMD7.uuI7xciIDY1MDRjYzlkN2ExOTRiY2NhNmU4NGJlMmExNjA2YzMy) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/distill/cwd/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco_20211212_205444.log.json?versionId=CAEQHxiBgID.o_WI7xciIDgyZjRjYTU4Y2ZjNjRjOGU5MTBlMTQ3ZjEyMTE4OTJl)|
+| cls head |COCO|[gfl_r101_2x](https://github.com/open-mmlab/mmdetection/tree/master/configs/gfl/gfl_r101_fpn_mstrain_2x_coco.py)|[gfl_r50_1x](https://github.com/open-mmlab/mmdetection/tree/master/configs/gfl/gfl_r50_fpn_1x_coco.py)| 41.9 | 44.7 | 40.2 |[config]()|[teacher](https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_r101_fpn_mstrain_2x_coco/gfl_r101_fpn_mstrain_2x_coco_20200629_200126-dd12f847.pth) |[model](https://download.openmmlab.com/mmrazor/v0.1/distill/cwd/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco_20211222-655dff39.pth) | [log](https://download.openmmlab.com/mmrazor/v0.1/distill/cwd/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco_20211212_205444.log.json)|
## Citation
diff --git a/configs/distill/cwd/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco.py b/configs/distill/cwd/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco.py
index 272fd3c91..e55b733cf 100644
--- a/configs/distill/cwd/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco.py
+++ b/configs/distill/cwd/cwd_cls_head_gfl_r101_fpn_gfl_r50_fpn_1x_coco.py
@@ -57,8 +57,11 @@
nms=dict(type='nms', iou_threshold=0.6),
max_per_img=100))
+checkpoint = 'https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_r101_fpn_mstrain_2x_coco/gfl_r101_fpn_mstrain_2x_coco_20200629_200126-dd12f847.pth' # noqa: E501
+
teacher = dict(
type='mmdet.GFL',
+ init_cfg=dict(type='Pretrained', checkpoint=checkpoint),
backbone=dict(
type='ResNet',
depth=101,
diff --git a/configs/distill/cwd/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k.py b/configs/distill/cwd/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k.py
index 0ff436c83..c3fd00b12 100644
--- a/configs/distill/cwd/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k.py
+++ b/configs/distill/cwd/cwd_cls_head_pspnet_r101_d8_pspnet_r18_d8_512x1024_cityscapes_80k.py
@@ -50,9 +50,12 @@
train_cfg=dict(),
test_cfg=dict(mode='whole'))
+checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes/pspnet_r101-d8_512x1024_80k_cityscapes_20200606_112211-e1e1100f.pth' # noqa: E501
+
# pspnet r101
teacher = dict(
type='mmseg.EncoderDecoder',
+ init_cfg=dict(type='Pretrained', checkpoint=checkpoint),
backbone=dict(
type='ResNetV1c',
depth=101,
diff --git a/configs/distill/wsld/README.md b/configs/distill/wsld/README.md
index 10f259b3b..8c9e78100 100644
--- a/configs/distill/wsld/README.md
+++ b/configs/distill/wsld/README.md
@@ -27,7 +27,7 @@ effectiveness of our method.
### Classification
|Location|Dataset|Teacher|Student|Acc|Acc(T)|Acc(S)|Config | Download |
:--------:|:---------:|:---------:|:---------:|:---------:|:---------:|:---------:|:------:|:---------|
-| cls head |ImageNet|[resnet34](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnet/resnet34_8xb32_in1k.py)|[resnet18](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnet/resnet18_8xb32_in1k.py)| 71.54 | 73.62 | 69.90 |[config](./wsld_cls_head_resnet34_resnet18_8xb32_in1k.py)|[teacher](https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth) |[model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/distill/wsld/wsld_cls_head_resnet34_resnet18_8xb32_in1k/wsld_cls_head_resnet34_resnet18_8xb32_in1k_acc-71.54_20211222-91f28cf6.pth?versionId=CAEQHxiBgMC6memK7xciIGMzMDFlYTA4YzhlYTRiMTNiZWU0YTVhY2I5NjVkMjY2) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/distill/wsld/wsld_cls_head_resnet34_resnet18_8xb32_in1k/wsld_cls_head_resnet34_resnet18_8xb32_in1k_20211221_181516.log.json?versionId=CAEQHxiBgIDLmemK7xciIGNkM2FiN2Y4N2E5YjRhNDE4NDVlNmExNDczZDIxN2E5)|
+| cls head |ImageNet|[resnet34](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnet/resnet34_8xb32_in1k.py)|[resnet18](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnet/resnet18_8xb32_in1k.py)| 71.54 | 73.62 | 69.90 |[config](./wsld_cls_head_resnet34_resnet18_8xb32_in1k.py)|[teacher](https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth) |[model](https://download.openmmlab.com/mmrazor/v0.1/distill/wsld/wsld_cls_head_resnet34_resnet18_8xb32_in1k/wsld_cls_head_resnet34_resnet18_8xb32_in1k_acc-71.54_20211222-91f28cf6.pth) | [log](https://download.openmmlab.com/mmrazor/v0.1/distill/wsld/wsld_cls_head_resnet34_resnet18_8xb32_in1k/wsld_cls_head_resnet34_resnet18_8xb32_in1k_20211221_181516.log.json)|
diff --git a/configs/distill/wsld/wsld_cls_head_resnet34_resnet18_8xb32_in1k.py b/configs/distill/wsld/wsld_cls_head_resnet34_resnet18_8xb32_in1k.py
index be4ec7246..06ac8c328 100644
--- a/configs/distill/wsld/wsld_cls_head_resnet34_resnet18_8xb32_in1k.py
+++ b/configs/distill/wsld/wsld_cls_head_resnet34_resnet18_8xb32_in1k.py
@@ -22,9 +22,12 @@
topk=(1, 5),
))
+checkpoint = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth' # noqa: E501
+
# teacher settings
teacher = dict(
type='mmcls.ImageClassifier',
+ init_cfg=dict(type='Pretrained', checkpoint=checkpoint),
backbone=dict(
type='ResNet',
depth=34,
diff --git a/configs/nas/darts/README.md b/configs/nas/darts/README.md
index 3eb4d38d3..bf28d670f 100644
--- a/configs/nas/darts/README.md
+++ b/configs/nas/darts/README.md
@@ -22,8 +22,8 @@ Dataset|Unroll|Config|Download|
Dataset|Params(M)|Flops(G)|Top-1 Acc|Top-5 Acc|Subnet|Config|Download|Remarks|
|:---------:|:---------:|:---------:|:---------:|:---------:|:---------:|:------:|:------:|:------:|
-|Cifar10|3.42 | 0.48 | 97.32 |99.94|[mutable](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_acc-97.32_20211222-e5727921_mutable_cfg.yaml?versionId=CAEQHxiBgMDn0ICL7xciIDAwNzUzZTU3ZjE4OTQ0MDg5YmZiMmYzYzExZTQ3YTRm)|[config](./darts_subnetnet_1xb96_cifar10.py)| [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_acc-97.32_20211222-e5727921.pth?versionId=CAEQHxiBgID20ICL7xciIDllOWZmNTliMzkwNzQ5YzdhODk2MzY1MWEyOTQ1Yjlk) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_20211222-e5727921.log.json?versionId=CAEQHxiBgMDz0ICL7xciIGRhMjk0NDU0OTVhZjQwMDg4N2ZkMDAzZDM1ZWU4N2Ri)|MMRazor searched
-|Cifar10|3.83 | 0.55 | 97.27 |99.98|[mutable](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_acc-97.27_20211222-17e42600_mutable_cfg.yaml?versionId=CAEQHxiBgICrnpmL7xciIGFmYzUxYjdmYWM1YzQ3N2I5NGU1MDE2ZjIxYmJhY2E0)|[config](./darts_subnetnet_1xb96_cifar10.py)| [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_acc-97.27_20211222-17e42600.pth?versionId=CAEQHxiBgIDQnpmL7xciIGQzOTRkMTViMDgzNzQ2MWI5MmUyNzIxZDk4OTUzZDgz) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_20211222-17e42600.log.json?versionId=CAEQHxiBgMDPnpmL7xciIDViYTVlYTIyYmQ2OTQ1ZDZhNTNhMjVkODA2NDRlMTI1)|official
+|Cifar10|3.42 | 0.48 | 97.32 |99.94|[mutable](https://download.openmmlab.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_acc-97.32_20211222-e5727921_mutable_cfg.yaml)|[config](./darts_subnetnet_1xb96_cifar10.py)| [model](https://download.openmmlab.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_acc-97.32_20211222-e5727921.pth) | [log](https://download.openmmlab.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_20211222-e5727921.log.json)|MMRazor searched
+|Cifar10|3.83 | 0.55 | 97.27 |99.98|[mutable](https://download.openmmlab.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_acc-97.27_20211222-17e42600_mutable_cfg.yaml)|[config](./darts_subnetnet_1xb96_cifar10.py)| [model](https://download.openmmlab.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_acc-97.27_20211222-17e42600.pth) | [log](https://download.openmmlab.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_20211222-17e42600.log.json)|official
## Citation
diff --git a/configs/nas/darts/darts_subnetnet_1xb96_cifar10.py b/configs/nas/darts/darts_subnet_1xb96_cifar10.py
similarity index 90%
rename from configs/nas/darts/darts_subnetnet_1xb96_cifar10.py
rename to configs/nas/darts/darts_subnet_1xb96_cifar10.py
index 8134ad59f..1e979578f 100644
--- a/configs/nas/darts/darts_subnetnet_1xb96_cifar10.py
+++ b/configs/nas/darts/darts_subnet_1xb96_cifar10.py
@@ -28,6 +28,9 @@
cal_acc=True),
)
+# FIXME: you may replace this with the mutable_cfg searched by yourself
+mutable_cfg = 'https://download.openmmlab.com/mmrazor/v0.1/nas/darts/darts_subnetnet_1xb96_cifar10/darts_subnetnet_1xb96_cifar10_acc-97.32_20211222-e5727921_mutable_cfg.yaml' # noqa: E501
+
algorithm = dict(
type='Darts',
architecture=dict(type='MMClsArchitecture', model=model),
@@ -69,7 +72,8 @@
)),
),
retraining=True,
- unroll=False)
+ unroll=False,
+ mutable_cfg=mutable_cfg)
data = dict(workers_per_gpu=8)
diff --git a/configs/nas/detnas/README.md b/configs/nas/detnas/README.md
index 60fb57a91..4a66866c2 100644
--- a/configs/nas/detnas/README.md
+++ b/configs/nas/detnas/README.md
@@ -38,7 +38,7 @@ python ./tools/mmdet/search_mmdet.py \
python ./tools/mmcls/train_mmcls.py \
configs/nas/detnas/detnas_subnet_shufflenetv2_8xb128_in1k.py \
--work-dir $WORK_DIR \
- --cfg-options algorithm.mutable_cfg=$STEP3_SUBNET_YAML
+ --cfg-options algorithm.mutable_cfg=$STEP3_SUBNET_YAML # or modify the config directly
```
### Step 5: Subnet fine-tuning on COCO
@@ -46,13 +46,13 @@ python ./tools/mmcls/train_mmcls.py \
python ./tools/mmdet/train_mmdet.py \
configs/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco.py \
--work-dir $WORK_DIR \
- --cfg-options algorithm.mutable_cfg=$STEP3_SUBNET_YAML load_from=$STEP4_CKPT
+ --cfg-options algorithm.mutable_cfg=$STEP3_SUBNET_YAML load_from=$STEP4_CKPT # or modify the config directly
```
## Results and models
|Dataset| Supernet | Subnet |Params(M)| Flops(G) | mAP | Config | Download | Remarks|
|:---------------:|:---------------:|:-----------:|:-----------:|:-----------:|:--------------:|:------:|:--------:|:--------:|
-|COCO| FRCNN-ShuffleNetV2| [mutable](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco_bbox_backbone_flops-0.34M_mAP-37.5_20211222-67fea61f_mutable_cfg.yaml?versionId=CAEQHxiBgMDU3taI7xciIDUzMmM4MTg4YTgwZDRhYjY4NjA3M2NkZDA0NWExNmY1) | 3.35(backbone)|0.34(backbone) | 37.5 |[config](./detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco.py)|[pretrain](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco/detnas_subnet_shufflenetv2_8xb128_in1k_acc-74.08_20211223-92e9b66a.pth?versionId=CAEQHxiBgICBxuuL7xciIGEyNzZkZmRmZmM5NzRjNDViOTNjOWZkNjk0OWYyYTdm) |[model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco_bbox_backbone_flops-0.34M_mAP-37.5_20211222-67fea61f.pth?versionId=CAEQHxiBgIDd3taI7xciIDIxYmUzMDE4ZmZmMjQ4ZGNiNzI1YjcxOGM4OGM5NDZl) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco_bbox_backbone_flops-0.34M_mAP-37.5_20211222-67fea61f.log.json?versionId=CAEQHxiBgMCSq9mM7xciIDViODRmMDE1Yjk1MDQwMTViMDBmYzZlMjg0OTJjYTlh)|MMRazor searched
+|COCO| FRCNN-ShuffleNetV2| [mutable](https://download.openmmlab.com/mmrazor/v0.1/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco_bbox_backbone_flops-0.34M_mAP-37.5_20211222-67fea61f_mutable_cfg.yaml) | 3.35(backbone)|0.34(backbone) | 37.5 |[config](./detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco.py)|[pretrain](https://download.openmmlab.com/mmrazor/v0.1/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco/detnas_subnet_shufflenetv2_8xb128_in1k_acc-74.08_20211223-92e9b66a.pth) |[model](https://download.openmmlab.com/mmrazor/v0.1/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco_bbox_backbone_flops-0.34M_mAP-37.5_20211222-67fea61f.pth) | [log](https://download.openmmlab.com/mmrazor/v0.1/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco_bbox_backbone_flops-0.34M_mAP-37.5_20211222-67fea61f.log.json)|MMRazor searched
**Note**:
diff --git a/configs/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco.py b/configs/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco.py
index be40b5535..dc929cc88 100644
--- a/configs/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco.py
+++ b/configs/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco.py
@@ -1,3 +1,6 @@
_base_ = ['./detnas_supernet_frcnn_shufflenetv2_fpn_1x_coco.py']
-algorithm = dict(retraining=True)
+# FIXME: you may replace this with the mutable_cfg searched by yourself
+mutable_cfg = 'https://download.openmmlab.com/mmrazor/v0.1/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco_bbox_backbone_flops-0.34M_mAP-37.5_20211222-67fea61f_mutable_cfg.yaml' # noqa: E501
+
+algorithm = dict(retraining=True, mutable_cfg=mutable_cfg)
diff --git a/configs/nas/detnas/detnas_subnet_shufflenetv2_8xb128_in1k.py b/configs/nas/detnas/detnas_subnet_shufflenetv2_8xb128_in1k.py
index 3e373ec08..9486cba6f 100644
--- a/configs/nas/detnas/detnas_subnet_shufflenetv2_8xb128_in1k.py
+++ b/configs/nas/detnas/detnas_subnet_shufflenetv2_8xb128_in1k.py
@@ -1,3 +1,8 @@
_base_ = [
'../spos/spos_subnet_shufflenetv2_8xb128_in1k.py',
]
+
+# FIXME: you may replace this with the mutable_cfg searched by yourself
+mutable_cfg = 'https://download.openmmlab.com/mmrazor/v0.1/nas/detnas/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco/detnas_subnet_frcnn_shufflenetv2_fpn_1x_coco_bbox_backbone_flops-0.34M_mAP-37.5_20211222-67fea61f_mutable_cfg.yaml' # noqa: E501
+
+algorithm = dict(mutable_cfg=mutable_cfg)
diff --git a/configs/nas/spos/README.md b/configs/nas/spos/README.md
index 68075cf88..a21272fdb 100644
--- a/configs/nas/spos/README.md
+++ b/configs/nas/spos/README.md
@@ -36,14 +36,14 @@ python ./tools/mmcls/search_mmcls.py \
python ./tools/mmcls/train_mmcls.py \
configs/nas/spos/spos_subnet_shufflenetv2_8xb128_in1k.py \
--work-dir $WORK_DIR \
- --cfg-options algorithm.mutable_cfg=$STEP2_SUBNET_YAML
+ --cfg-options algorithm.mutable_cfg=$STEP2_SUBNET_YAML # or modify the config directly
```
## Results and models
| Dataset | Supernet | Subnet | Params(M) | Flops(G) | Top-1 (%) | Top-5 (%) | Config | Download | Remarks |
| :------: |:----------------------:| :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------: | :------: | :-------: | :-------: | :----------------------------------------------: |:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------:|
-| ImageNet | ShuffleNetV2 | [mutable](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/spos/spos_shufflenetv2_subnet_8xb128_in1k/spos_shufflenetv2_subnet_8xb128_in1k_flops_0.33M_acc_73.87_20211222-454627be_mutable_cfg.yaml?versionId=CAEQHxiBgICw5b6I7xciIGY5MjVmNWFhY2U5MjQzN2M4NDViYzI2YWRmYWE1YzQx) | 3.35 | 0.33 | 73.87 | 91.6 | [config](./spos_subnet_shufflenetv2_8xb128_in1k.py) | [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/spos/spos_shufflenetv2_subnet_8xb128_in1k/spos_shufflenetv2_subnet_8xb128_in1k_flops_0.33M_acc_73.87_20211222-1f0a0b4d.pth?versionId=CAEQHxiBgIDK5b6I7xciIDM1YjIwZjQxN2UyMDRjYjA5YTM5NTBlMGNhMTdkNjI2) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/nas/spos/spos_shufflenetv2_subnet_8xb128_in1k/spos_shufflenetv2_subnet_8xb128_in1k_flops_0.33M_acc_73.87_20211222-1f0a0b4d.log.json?versionId=CAEQHxiBgIDr9cuL7xciIDBmOTZiZGUyYjRiMDQ5NzhhZjY0NWUxYmUzNDlmNTg5) | MMRazor searched |
+| ImageNet | ShuffleNetV2 | [mutable](https://download.openmmlab.com/mmrazor/v0.1/nas/spos/spos_shufflenetv2_subnet_8xb128_in1k/spos_shufflenetv2_subnet_8xb128_in1k_flops_0.33M_acc_73.87_20211222-454627be_mutable_cfg.yaml) | 3.35 | 0.33 | 73.87 | 91.6 | [config](./spos_subnet_shufflenetv2_8xb128_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v0.1/nas/spos/spos_shufflenetv2_subnet_8xb128_in1k/spos_shufflenetv2_subnet_8xb128_in1k_flops_0.33M_acc_73.87_20211222-1f0a0b4d.pth) | [log](https://download.openmmlab.com/mmrazor/v0.1/nas/spos/spos_shufflenetv2_subnet_8xb128_in1k/spos_shufflenetv2_subnet_8xb128_in1k_flops_0.33M_acc_73.87_20211222-1f0a0b4d.log.json) | MMRazor searched |
| ImageNet | MobileNet-ProxylessGPU | [mutable](https://download.openmmlab.com/mmrazor/v0.1/nas/spos/spos_mobilenet_subnet/spos_angelnas_flops_0.49G_acc_75.98_20220307-54f4698f_mutable_cfg.yaml) | 5.94 | 0.49* | 75.98 | 92.77 | [config](./spos_mobilenet_for_check_ckpt_from_anglenas.py) | | [AngleNAS](https://github.com/megvii-model/AngleNAS) searched |
**Note**:
diff --git a/configs/nas/spos/spos_subnet_mobilenet_proxyless_gpu_8xb128_in1k.py b/configs/nas/spos/spos_subnet_mobilenet_proxyless_gpu_8xb128_in1k.py
index 198a9c053..54d5ff5fb 100644
--- a/configs/nas/spos/spos_subnet_mobilenet_proxyless_gpu_8xb128_in1k.py
+++ b/configs/nas/spos/spos_subnet_mobilenet_proxyless_gpu_8xb128_in1k.py
@@ -2,7 +2,10 @@
'./spos_supernet_mobilenet_proxyless_gpu_8xb128_in1k.py',
]
-algorithm = dict(retraining=True)
+# FIXME: you may replace this with the mutable_cfg searched by yourself
+mutable_cfg = 'https://download.openmmlab.com/mmrazor/v0.1/nas/spos/spos_mobilenet_subnet/spos_angelnas_flops_0.49G_acc_75.98_20220307-54f4698f_mutable_cfg.yaml' # noqa: E501
+
+algorithm = dict(retraining=True, mutable_cfg=mutable_cfg)
evaluation = dict(interval=10000, metric='accuracy')
checkpoint_config = dict(interval=30000)
diff --git a/configs/nas/spos/spos_subnet_shufflenetv2_8xb128_in1k.py b/configs/nas/spos/spos_subnet_shufflenetv2_8xb128_in1k.py
index e849579fe..110ee047b 100644
--- a/configs/nas/spos/spos_subnet_shufflenetv2_8xb128_in1k.py
+++ b/configs/nas/spos/spos_subnet_shufflenetv2_8xb128_in1k.py
@@ -2,7 +2,10 @@
'./spos_supernet_shufflenetv2_8xb128_in1k.py',
]
-algorithm = dict(retraining=True)
+# FIXME: you may replace this with the mutable_cfg searched by yourself
+mutable_cfg = 'https://download.openmmlab.com/mmrazor/v0.1/nas/spos/spos_shufflenetv2_subnet_8xb128_in1k/spos_shufflenetv2_subnet_8xb128_in1k_flops_0.33M_acc_73.87_20211222-454627be_mutable_cfg.yaml' # noqa: E501
+
+algorithm = dict(retraining=True, mutable_cfg=mutable_cfg)
runner = dict(max_iters=300000)
find_unused_parameters = False
diff --git a/configs/pruning/autoslim/README.md b/configs/pruning/autoslim/README.md
index 84d3b7e5f..fdd15d073 100644
--- a/configs/pruning/autoslim/README.md
+++ b/configs/pruning/autoslim/README.md
@@ -48,15 +48,15 @@ python ./tools/model_converters/split_checkpoint.py \
python ./tools/mmcls/test_mmcls.py \
configs/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k.py \
your_splitted_checkpoint_path --metrics accuracy \
- --cfg-options algorithm.channel_cfg=configs/pruning/autoslim/AUTOSLIM_MBV2_530M_OFFICIAL.yaml
+ --cfg-options algorithm.channel_cfg=configs/pruning/autoslim/AUTOSLIM_MBV2_530M_OFFICIAL.yaml # or modify the config directly
## Results and models
### Subnet retrain
| Supernet | Params(M) | Flops(G) | Top-1 (%) | Top-5 (%) | Config | Download | Subnet | Remark |
| :----------------- | :-------: | -------: | :-------: | :-------: | :----: | :------: | :-------------: | :----: |
-| MobileNet v2(x1.5) | 6.5 | 0.53 | 74.23 | 91.74 | [config](./autoslim_mbv2_subnet_8xb256_in1k.py) | [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.53M_acc-74.23_20211222-e5208bbd.pth?versionId=CAEQHxiBgICYsIaI7xciIDE1MGIxM2Q5NDk1NjRlOTFiMjgwOTRmYzJlMDBmZDY0) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1kautoslim_mbv2_subnet_8xb256_in1k_paper_channel_cfg.log.json?versionId=CAEQHxiBgMCjj9SL7xciIDFmYmM4NTExZmIzNjRmNmQ4MmMyZWI4YzJmMmM2MDdl) | [channel](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.53M_acc-74.23_20211222-e5208bbd_channel_cfg.yaml?versionId=CAEQHxiBgMDwr4aI7xciIDQ2MmRhMDFhNGMyODQyYmU5ZTIyOTcxMmRlN2RmYjg2) | official channel cfg |
-| MobileNet v2(x1.5) | 5.77 | 0.32 | 72.73 | 90.83 | [config](./autoslim_mbv2_subnet_8xb256_in1k.py) | [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.32M_acc-72.73_20211222-b5b0b33c.pth?versionId=CAEQHxiBgMCasIaI7xciIDEzN2FkZjZkNWMwYjRiOTg5NTY0MzY0ODk5ODE2N2Yz) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1kautoslim_mbv2_subnet_8xb256_in1k_paper_channel_cfg.log.json?versionId=CAEQHxiBgMCjj9SL7xciIDFmYmM4NTExZmIzNjRmNmQ4MmMyZWI4YzJmMmM2MDdl) | [channel](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.32M_acc-72.73_20211222-b5b0b33c_channel_cfg.yaml?versionId=CAEQHxiCgMDwr4aI7xciIDhjMmUzZjlmZTJjODQzMDRhMmQxMzkyM2MwOTZhNjE3) | official channel cfg |
-| MobileNet v2(x1.5) | 4.13 |0.22 | 71.39 | 90.08 | [config](./autoslim_mbv2_subnet_8xb256_in1k.py) | [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.22M_acc-71.39_20211222-43117c7b.pth?versionId=CAEQHxiBgICRsIaI7xciIDVlY2MxMTkwZjg0ODQ3M2I5NTJmYjFiNDk1MDEwNjAy) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1kautoslim_mbv2_subnet_8xb256_in1k_paper_channel_cfg.log.json?versionId=CAEQHxiBgMCjj9SL7xciIDFmYmM4NTExZmIzNjRmNmQ4MmMyZWI4YzJmMmM2MDdl) | [channel](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.22M_acc-71.39_20211222-43117c7b_channel_cfg.yaml.?versionId=CAEQHxiBgIDzr4aI7xciIDViNGY0ZDA1ODkxZTRkMGFhNTg2M2FlZmQyZTFiMDgx) | official channel cfg |
+| MobileNet v2(x1.5) | 6.5 | 0.53 | 74.23 | 91.74 | [config](./autoslim_mbv2_subnet_8xb256_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.53M_acc-74.23_20211222-e5208bbd.pth) | [log](https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1kautoslim_mbv2_subnet_8xb256_in1k_paper_channel_cfg.log.json) | [channel](https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.53M_acc-74.23_20211222-e5208bbd_channel_cfg.yaml) | official channel cfg |
+| MobileNet v2(x1.5) | 5.77 | 0.32 | 72.73 | 90.83 | [config](./autoslim_mbv2_subnet_8xb256_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.32M_acc-72.73_20211222-b5b0b33c.pth) | [log](https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1kautoslim_mbv2_subnet_8xb256_in1k_paper_channel_cfg.log.json) | [channel](https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.32M_acc-72.73_20211222-b5b0b33c_channel_cfg.yaml) | official channel cfg |
+| MobileNet v2(x1.5) | 4.13 |0.22 | 71.39 | 90.08 | [config](./autoslim_mbv2_subnet_8xb256_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.22M_acc-71.39_20211222-43117c7b.pth) | [log](https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1kautoslim_mbv2_subnet_8xb256_in1k_paper_channel_cfg.log.json) | [channel](https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.22M_acc-71.39_20211222-43117c7b_channel_cfg.yaml) | official channel cfg |
Note that we ran the official code and the Top-1 Acc of the models with official
channel cfg are 73.8%, 72.5% and 71.1%. And there are 3 differences between our
diff --git a/configs/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k.py b/configs/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k.py
index afc974eb3..00d2f841a 100644
--- a/configs/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k.py
+++ b/configs/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k.py
@@ -10,12 +10,19 @@
label_smooth_val=0.1,
loss_weight=1.0)))
+# FIXME: you may replace this with the channel_cfg searched by yourself
+channel_cfg = [
+ 'https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.53M_acc-74.23_20211222-e5208bbd_channel_cfg.yaml', # noqa: E501
+ 'https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.32M_acc-72.73_20211222-b5b0b33c_channel_cfg.yaml', # noqa: E501
+ 'https://download.openmmlab.com/mmrazor/v0.1/pruning/autoslim/autoslim_mbv2_subnet_8xb256_in1k/autoslim_mbv2_subnet_8xb256_in1k_flops-0.22M_acc-71.39_20211222-43117c7b_channel_cfg.yaml' # noqa: E501
+]
+
algorithm = dict(
architecture=dict(type='MMClsArchitecture', model=model),
distiller=None,
retraining=True,
bn_training_mode=False,
-)
+ channel_cfg=channel_cfg)
runner = dict(type='EpochBasedRunner', max_epochs=300)
diff --git a/docs/en/train.md b/docs/en/train.md
index dc134c617..ad93b8892 100644
--- a/docs/en/train.md
+++ b/docs/en/train.md
@@ -59,6 +59,13 @@ python ./tools/mmcls/train_mmcls.py \
--cfg-options algorithm.mutable_cfg=configs/nas/spos/SPOS_SHUFFLENETV2_330M_IN1k_PAPER.yaml
+We note that instead of using ``--cfg-options``, you can also directly modify ``configs/nas/spos/spos_subnet_shufflenetv2_8xb128_in1k.py`` like this:
+
+
+mutable_cfg = 'configs/nas/spos/SPOS_SHUFFLENETV2_330M_IN1k_PAPER.yaml'
+algorithm = dict(..., mutable_cfg=mutable_cfg)
+
+
## Pruning
Pruning has three steps, including **supernet pre-training**, **search for subnet on the trained supernet** and **subnet retraining**. The commands of the first two steps are similar to NAS, except that we need to use `CONFIG_FILE` of Pruning here. The commands of the **subnet retraining** are as follows.