diff --git a/configs/distillers/mimic_backbone/mb_cascade_rcnn_swinS_fpn_3x_distill_cascade_rcnn_swinT_fpn_1x_coco.py b/configs/distillers/mimic_backbone/mb_cascade_rcnn_swinS_fpn_3x_distill_cascade_rcnn_swinT_fpn_1x_coco.py
new file mode 100644
index 0000000000000000000000000000000000000000..5f999497c5642c487c7ae301de24a621c36b2014
--- /dev/null
+++ b/configs/distillers/mimic_backbone/mb_cascade_rcnn_swinS_fpn_3x_distill_cascade_rcnn_swinT_fpn_1x_coco.py
@@ -0,0 +1,77 @@
+_base_ = [
+ '../../_base_/models/mask_rcnn_swin_fpn.py',
+ '../../_base_/datasets/coco_instance.py',
+ '../../_base_/schedules/schedule_1x.py', '../../_base_/default_runtime.py'
+]
+
+# model settings
+find_unused_parameters=True
+weight=1
+distiller = dict(
+ type='BackboneDistiller',
+ teacher_pretrained = '/mnt/data3/wangguohua/model/mmdet/swin/cascade_mask_rcnn_swin_small_patch4_window7.pth',
+ init_student = True,
+ distill_cfg = [ dict(feature_level = 0,
+ methods=[dict(type='MSELoss',
+ name='loss_mb_0',
+ student_channels = 96,
+ teacher_channels = 96,
+ weight = weight,
+ )
+ ]
+ ),
+ dict(feature_level = 1,
+ methods=[dict(type='MSELoss',
+ name='loss_mb_1',
+ student_channels = 192,
+ teacher_channels = 192,
+ weight = weight,
+ )
+ ]
+ ),
+ dict(feature_level = 2,
+ methods=[dict(type='MSELoss',
+ name='loss_mb_2',
+ student_channels = 384,
+ teacher_channels = 384,
+ weight = weight,
+ )
+ ]
+ ),
+ dict(feature_level = 3,
+ methods=[dict(type='MSELoss',
+ name='loss_mb_3',
+ student_channels = 768,
+ teacher_channels = 768,
+ weight = weight,
+ )
+ ]
+ ),
+ ]
+ )
+
+student_cfg = 'configs/swin/cascade_mask_rcnn_swin_tiny_patch4_window7_mstrain_480-800_giou_4conv1f_adamw_1x_coco.py'
+teacher_cfg = 'configs/swin/cascade_mask_rcnn_swin_small_patch4_window7_mstrain_480-800_giou_4conv1f_adamw_3x_coco.py'
+
+data = dict(
+ samples_per_gpu=2,
+ workers_per_gpu=2,)
+#data = dict(train=dict(pipeline=train_pipeline))
+
+optimizer = dict(_delete_=True, type='AdamW', lr=0.0001, betas=(0.9, 0.999), weight_decay=0.05,
+ paramwise_cfg=dict(custom_keys={'absolute_pos_embed': dict(decay_mult=0.),
+ 'relative_position_bias_table': dict(decay_mult=0.),
+ 'norm': dict(decay_mult=0.)}))
+lr_config = dict(step=[8, 11])
+#runner = dict(type='EpochBasedRunnerAmp', max_epochs=12)
+runner = dict(type='EpochBasedRunner', max_epochs=12)
+# do not use mmdet version fp16
+# fp16 = None
+# optimizer_config = dict(
+# type="DistOptimizerHook",
+# update_interval=1,
+# grad_clip=None,
+# coalesce=True,
+# bucket_size_mb=-1,
+# use_fp16=True,
+# )
\ No newline at end of file
diff --git a/configs/distillers/mimic_backbone/mb_cascade_rcnn_swinT_fpn_3x_distill_cascade_rcnn_swinT_fpn_1x_coco.py b/configs/distillers/mimic_backbone/mb_cascade_rcnn_swinT_fpn_3x_distill_cascade_rcnn_swinT_fpn_1x_coco.py
new file mode 100644
index 0000000000000000000000000000000000000000..391d9e0a95a6b7e9c954531b9acf5e3b8bb989c0
--- /dev/null
+++ b/configs/distillers/mimic_backbone/mb_cascade_rcnn_swinT_fpn_3x_distill_cascade_rcnn_swinT_fpn_1x_coco.py
@@ -0,0 +1,77 @@
+_base_ = [
+ '../../_base_/models/mask_rcnn_swin_fpn.py',
+ '../../_base_/datasets/coco_instance.py',
+ '../../_base_/schedules/schedule_1x.py', '../../_base_/default_runtime.py'
+]
+
+# model settings
+find_unused_parameters=True
+weight=1
+distiller = dict(
+ type='BackboneDistiller',
+ teacher_pretrained = '/mnt/data3/wangguohua/model/mmdet/swin/cascade_mask_rcnn_swin_tiny_patch4_window7.pth',
+ init_student = True,
+ distill_cfg = [ dict(feature_level = 0,
+ methods=[dict(type='MSELoss',
+ name='loss_mb_0',
+ student_channels = 96,
+ teacher_channels = 96,
+ weight = weight,
+ )
+ ]
+ ),
+ dict(feature_level = 1,
+ methods=[dict(type='MSELoss',
+ name='loss_mb_1',
+ student_channels = 192,
+ teacher_channels = 192,
+ weight = weight,
+ )
+ ]
+ ),
+ dict(feature_level = 2,
+ methods=[dict(type='MSELoss',
+ name='loss_mb_2',
+ student_channels = 384,
+ teacher_channels = 384,
+ weight = weight,
+ )
+ ]
+ ),
+ dict(feature_level = 3,
+ methods=[dict(type='MSELoss',
+ name='loss_mb_3',
+ student_channels = 768,
+ teacher_channels = 768,
+ weight = weight,
+ )
+ ]
+ ),
+ ]
+ )
+
+student_cfg = 'configs/swin/cascade_mask_rcnn_swin_tiny_patch4_window7_mstrain_480-800_giou_4conv1f_adamw_1x_coco.py'
+teacher_cfg = 'configs/swin/cascade_mask_rcnn_swin_tiny_patch4_window7_mstrain_480-800_giou_4conv1f_adamw_3x_coco.py'
+
+data = dict(
+ samples_per_gpu=2,
+ workers_per_gpu=2,)
+#data = dict(train=dict(pipeline=train_pipeline))
+
+optimizer = dict(_delete_=True, type='AdamW', lr=0.0001, betas=(0.9, 0.999), weight_decay=0.05,
+ paramwise_cfg=dict(custom_keys={'absolute_pos_embed': dict(decay_mult=0.),
+ 'relative_position_bias_table': dict(decay_mult=0.),
+ 'norm': dict(decay_mult=0.)}))
+lr_config = dict(step=[8, 11])
+#runner = dict(type='EpochBasedRunnerAmp', max_epochs=12)
+runner = dict(type='EpochBasedRunner', max_epochs=12)
+# do not use mmdet version fp16
+# fp16 = None
+# optimizer_config = dict(
+# type="DistOptimizerHook",
+# update_interval=1,
+# grad_clip=None,
+# coalesce=True,
+# bucket_size_mb=-1,
+# use_fp16=True,
+# )
\ No newline at end of file