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* support kd for mbv2 and shufflenetv2 * WIP: fix ckpt path * WIP: fix kd r34-r18 * add metafile * fix metafile * delete
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37 changes: 37 additions & 0 deletions
37
configs/distill/mmcls/kd/kd_logits_resnet50_mobilenet-v2_8xb32_in1k.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,37 @@ | ||
| _base_ = ['mmcls::mobilenet_v2/mobilenet-v2_8xb32_in1k.py'] | ||
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| student = _base_.model | ||
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| teacher_ckpt = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth' # noqa: E501 | ||
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| model = dict( | ||
| _scope_='mmrazor', | ||
| _delete_=True, | ||
| type='SingleTeacherDistill', | ||
| data_preprocessor=dict( | ||
| type='ImgDataPreprocessor', | ||
| # RGB format normalization parameters | ||
| mean=[123.675, 116.28, 103.53], | ||
| std=[58.395, 57.12, 57.375], | ||
| # convert image from BGR to RGB | ||
| bgr_to_rgb=True), | ||
| architecture=student, | ||
| teacher=dict( | ||
| cfg_path='mmcls::resnet/resnet50_8xb32_in1k.py', pretrained=False), | ||
| teacher_ckpt=teacher_ckpt, | ||
| distiller=dict( | ||
| type='ConfigurableDistiller', | ||
| student_recorders=dict( | ||
| fc=dict(type='ModuleOutputs', source='head.fc')), | ||
| teacher_recorders=dict( | ||
| fc=dict(type='ModuleOutputs', source='head.fc')), | ||
| distill_losses=dict( | ||
| loss_kl=dict(type='KLDivergence', tau=1, loss_weight=3)), | ||
| loss_forward_mappings=dict( | ||
| loss_kl=dict( | ||
| preds_S=dict(from_student=True, recorder='fc'), | ||
| preds_T=dict(from_student=False, recorder='fc'))))) | ||
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| find_unused_parameters = True | ||
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| val_cfg = dict(_delete_=True, type='mmrazor.SingleTeacherDistillValLoop') |
37 changes: 37 additions & 0 deletions
37
configs/distill/mmcls/kd/kd_logits_resnet50_shufflenet-v2-1x_16xb64_in1k.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,37 @@ | ||
| _base_ = ['mmcls::shufflenet_v2/shufflenet-v2-1x_16xb64_in1k.py'] | ||
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| student = _base_.model | ||
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| teacher_ckpt = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth' # noqa: E501 | ||
|
|
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| model = dict( | ||
| _scope_='mmrazor', | ||
| _delete_=True, | ||
| type='SingleTeacherDistill', | ||
| data_preprocessor=dict( | ||
| type='ImgDataPreprocessor', | ||
| # RGB format normalization parameters | ||
| mean=[123.675, 116.28, 103.53], | ||
| std=[58.395, 57.12, 57.375], | ||
| # convert image from BGR to RGB | ||
| bgr_to_rgb=True), | ||
| architecture=student, | ||
| teacher=dict( | ||
| cfg_path='mmcls::resnet/resnet50_8xb32_in1k.py', pretrained=False), | ||
| teacher_ckpt=teacher_ckpt, | ||
| distiller=dict( | ||
| type='ConfigurableDistiller', | ||
| student_recorders=dict( | ||
| fc=dict(type='ModuleOutputs', source='head.fc')), | ||
| teacher_recorders=dict( | ||
| fc=dict(type='ModuleOutputs', source='head.fc')), | ||
| distill_losses=dict( | ||
| loss_kl=dict(type='KLDivergence', tau=1, loss_weight=3)), | ||
| loss_forward_mappings=dict( | ||
| loss_kl=dict( | ||
| preds_S=dict(from_student=True, recorder='fc'), | ||
| preds_T=dict(from_student=False, recorder='fc'))))) | ||
|
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| find_unused_parameters = True | ||
|
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| val_cfg = dict(_delete_=True, type='mmrazor.SingleTeacherDistillValLoop') |
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