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[Fix] Align GreedyNAS retraining details with huangtao's code #1

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@pppppM pppppM commented Apr 26, 2022

Motivation

There are some inconsistencies with Huang Tao's code, and I fixed them in this PR.

Modification

  1. register RMSPropTF to OPTIMIZER and remove the hard code in the train api.
  2. custom a new LR hook to align the LR curve and update lr_config.
  3. add a new cls head with dropout and update related configs ( Dropout should be after GlobalAveragePooling)
  4. IterBasedRunner -> EpochBasedRunner
  5. align the init_cfg with huangtao
  6. add the right rand-m9-mstd-0.5 config in mmcls style

pppppM added 6 commits April 26, 2022 11:01
2. update lr config to align lr curve with huangtao
3. IterBasedRunner -> EpochBaseRunner
2. fix the rand-m9-mstd-0.5 config in mmcls style
3. training with full imagenet
2. align init_cfg
3. add default mutable_cfg
4. eval and save ckpt by epoch
optimizer = dict(
type='RMSpropTF',
lr=0.048,
eps=0.001,
weight_decay=1e-5,
momentum=0.9,
filter_bias_and_bn=True)
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params = _add_weight_decay(model, lr, weight_decay)
weight_decay = 0

@@ -5,28 +5,27 @@
]

init_cfg = [
dict(type='FanOutNormal', layer=['Conv2d']),
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nn.init.kaiming_uniform_(m.weight, mode='fan_in', nonlinearity='linear')

humu789 pushed a commit that referenced this pull request Feb 13, 2023
* add function marker and model extractor

* add fsaf split & partial mask rcnn split, import extract.py

* 1. add value renaming  2. add apply_marks in config to turn on/off marks

* rewind changes on pytorch2onnx.py

Co-authored-by: q.yao <[email protected]>
humu789 pushed a commit that referenced this pull request Feb 13, 2023
Co-authored-by: Yifan Zhou <[email protected]>
Co-authored-by: lvhan028 <[email protected]>

Co-authored-by: Yifan Zhou <[email protected]>
Co-authored-by: lvhan028 <[email protected]>
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2 participants