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[FEATURE] Mobilenet Series Search Space (#82)
* add mbv2 block and identity * add mbv2 block and identity unittests * expand_factor -> expand_ratio * add searchable mobilenet v2 * fix lints * add spos subnet retraining config * fix mmcls slurm search * add proxyless_gpu setting for mbv2 * use bn default * add angelnas spos config * update spos readme * fix SELayer's useage * add docstring * rename mbv2 to mb * add some unittest of mb * rename mb to mobilenet * add some rename-mb in configs * update README of spos * add rename-mb in unittest * update test_mmcls Co-authored-by: wutongshenqiu <[email protected]> Co-authored-by: humu789 <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,66 @@ | ||
| stage_0_block_0: | ||
| chosen: | ||
| - mb_k3e1 | ||
| stage_1_block_0: | ||
| chosen: | ||
| - mb_k5e3 | ||
| stage_1_block_1: | ||
| chosen: | ||
| - mb_k5e3 | ||
| stage_1_block_2: | ||
| chosen: | ||
| - identity | ||
| stage_1_block_3: | ||
| chosen: | ||
| - mb_k3e3 | ||
| stage_2_block_0: | ||
| chosen: | ||
| - mb_k3e3 | ||
| stage_2_block_1: | ||
| chosen: | ||
| - identity | ||
| stage_2_block_2: | ||
| chosen: | ||
| - identity | ||
| stage_2_block_3: | ||
| chosen: | ||
| - mb_k3e3 | ||
| stage_3_block_0: | ||
| chosen: | ||
| - mb_k7e6 | ||
| stage_3_block_1: | ||
| chosen: | ||
| - identity | ||
| stage_3_block_2: | ||
| chosen: | ||
| - mb_k7e3 | ||
| stage_3_block_3: | ||
| chosen: | ||
| - mb_k7e3 | ||
| stage_4_block_0: | ||
| chosen: | ||
| - mb_k3e3 | ||
| stage_4_block_1: | ||
| chosen: | ||
| - mb_k3e3 | ||
| stage_4_block_2: | ||
| chosen: | ||
| - mb_k7e3 | ||
| stage_4_block_3: | ||
| chosen: | ||
| - mb_k5e3 | ||
| stage_5_block_0: | ||
| chosen: | ||
| - mb_k5e6 | ||
| stage_5_block_1: | ||
| chosen: | ||
| - mb_k7e3 | ||
| stage_5_block_2: | ||
| chosen: | ||
| - mb_k7e3 | ||
| stage_5_block_3: | ||
| chosen: | ||
| - mb_k7e3 | ||
| stage_6_block_0: | ||
| chosen: | ||
| - mb_k5e6 |
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configs/nas/spos/spos_evolution_search_mobilenet_proxyless_gpu_flops465_8xb512_in1k.py
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| _base_ = ['./spos_supernet_mobilenet_proxyless_gpu_8xb128_in1k.py'] | ||
|
|
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| data = dict( | ||
| samples_per_gpu=512, | ||
| workers_per_gpu=16, | ||
| ) | ||
|
|
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| algorithm = dict(bn_training_mode=True) | ||
|
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| searcher = dict( | ||
| type='EvolutionSearcher', | ||
| candidate_pool_size=50, | ||
| candidate_top_k=10, | ||
| constraints=dict(flops=465 * 1e6), | ||
| metrics='accuracy', | ||
| score_key='accuracy_top-1', | ||
| max_epoch=20, | ||
| num_mutation=25, | ||
| num_crossover=25, | ||
| mutate_prob=0.1) |
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configs/nas/spos/spos_mobilenet_for_check_ckpt_from_anglenas.py
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| _base_ = [ | ||
| './spos_subnet_mobilenet_proxyless_gpu_8xb128_in1k.py', | ||
| ] | ||
|
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| img_norm_cfg = dict(mean=[0., 0., 0.], std=[1., 1., 1.], to_rgb=False) | ||
| train_pipeline = [ | ||
| dict(type='LoadImageFromFile'), | ||
| dict(type='RandomResizedCrop', size=224), | ||
| dict(type='ColorJitter', brightness=0.4, contrast=0.4, saturation=0.4), | ||
| dict(type='RandomFlip', flip_prob=0.5, direction='horizontal'), | ||
| dict(type='Normalize', **img_norm_cfg), | ||
| dict(type='ImageToTensor', keys=['img']), | ||
| dict(type='ToTensor', keys=['gt_label']), | ||
| dict(type='Collect', keys=['img', 'gt_label']) | ||
| ] | ||
| test_pipeline = [ | ||
| dict(type='LoadImageFromFile'), | ||
| dict(type='Resize', size=(256, -1)), | ||
| dict(type='CenterCrop', crop_size=224), | ||
| dict(type='Normalize', **img_norm_cfg), | ||
| dict(type='ImageToTensor', keys=['img']), | ||
| dict(type='Collect', keys=['img']) | ||
| ] | ||
| data = dict( | ||
| train=dict(pipeline=train_pipeline), | ||
| val=dict(pipeline=test_pipeline), | ||
| test=dict(pipeline=test_pipeline)) |
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configs/nas/spos/spos_subnet_mobilenet_proxyless_gpu_8xb128_in1k.py
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| _base_ = [ | ||
| './spos_supernet_mobilenet_proxyless_gpu_8xb128_in1k.py', | ||
| ] | ||
|
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| algorithm = dict(retraining=True) | ||
| evaluation = dict(interval=10000, metric='accuracy') | ||
| checkpoint_config = dict(interval=30000) | ||
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| runner = dict(max_iters=300000) | ||
| find_unused_parameters = False |
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configs/nas/spos/spos_supernet_mobilenet_proxyless_gpu_8xb128_in1k.py
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| _base_ = [ | ||
| '../../_base_/datasets/mmcls/imagenet_bs128_colorjittor.py', | ||
| '../../_base_/schedules/mmcls/imagenet_bs1024_spos.py', | ||
| '../../_base_/mmcls_runtime.py' | ||
| ] | ||
| norm_cfg = dict(type='BN') | ||
| model = dict( | ||
| type='mmcls.ImageClassifier', | ||
| backbone=dict( | ||
| type='SearchableMobileNet', | ||
| first_channels=40, | ||
| last_channels=1728, | ||
| widen_factor=1.0, | ||
| norm_cfg=norm_cfg, | ||
| arch_setting_type='proxyless_gpu'), | ||
| neck=dict(type='GlobalAveragePooling'), | ||
| head=dict( | ||
| type='LinearClsHead', | ||
| num_classes=1000, | ||
| in_channels=1728, | ||
| loss=dict( | ||
| type='LabelSmoothLoss', | ||
| num_classes=1000, | ||
| label_smooth_val=0.1, | ||
| mode='original', | ||
| loss_weight=1.0), | ||
| topk=(1, 5), | ||
| ), | ||
| ) | ||
|
|
||
| mutator = dict( | ||
| type='OneShotMutator', | ||
| placeholder_mapping=dict( | ||
| searchable_blocks=dict( | ||
| type='OneShotOP', | ||
| choices=dict( | ||
| mb_k3e3=dict( | ||
| type='MBBlock', | ||
| kernel_size=3, | ||
| expand_ratio=3, | ||
| norm_cfg=norm_cfg, | ||
| act_cfg=dict(type='ReLU6')), | ||
| mb_k5e3=dict( | ||
| type='MBBlock', | ||
| kernel_size=5, | ||
| expand_ratio=3, | ||
| norm_cfg=norm_cfg, | ||
| act_cfg=dict(type='ReLU6')), | ||
| mb_k7e3=dict( | ||
| type='MBBlock', | ||
| kernel_size=7, | ||
| expand_ratio=3, | ||
| norm_cfg=norm_cfg, | ||
| act_cfg=dict(type='ReLU6')), | ||
| mb_k3e6=dict( | ||
| type='MBBlock', | ||
| kernel_size=3, | ||
| expand_ratio=6, | ||
| norm_cfg=norm_cfg, | ||
| act_cfg=dict(type='ReLU6')), | ||
| mb_k5e6=dict( | ||
| type='MBBlock', | ||
| kernel_size=5, | ||
| expand_ratio=6, | ||
| norm_cfg=norm_cfg, | ||
| act_cfg=dict(type='ReLU6')), | ||
| mb_k7e6=dict( | ||
| type='MBBlock', | ||
| kernel_size=7, | ||
| expand_ratio=6, | ||
| norm_cfg=norm_cfg, | ||
| act_cfg=dict(type='ReLU6')), | ||
| identity=dict(type='Identity'))), | ||
| first_blocks=dict( | ||
| type='OneShotOP', | ||
| choices=dict( | ||
| mb_k3e1=dict( | ||
| type='MBBlock', | ||
| kernel_size=3, | ||
| expand_ratio=1, | ||
| norm_cfg=norm_cfg, | ||
| act_cfg=dict(type='ReLU6')), )))) | ||
|
|
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| algorithm = dict( | ||
| type='SPOS', | ||
| architecture=dict( | ||
| type='MMClsArchitecture', | ||
| model=model, | ||
| ), | ||
| mutator=mutator, | ||
| distiller=None, | ||
| retraining=False, | ||
| ) | ||
|
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| runner = dict(max_iters=150000) | ||
| evaluation = dict(interval=10000, metric='accuracy') | ||
|
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| # checkpoint saving | ||
| checkpoint_config = dict(interval=30000) | ||
|
|
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| find_unused_parameters = True |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,6 @@ | ||
| # Copyright (c) OpenMMLab. All rights reserved. | ||
| from .darts_backbone import DartsBackbone | ||
| from .searchable_mobilenet import SearchableMobileNet | ||
| from .searchable_shufflenet_v2 import SearchableShuffleNetV2 | ||
|
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| __all__ = ['DartsBackbone', 'SearchableShuffleNetV2'] | ||
| __all__ = ['DartsBackbone', 'SearchableShuffleNetV2', 'SearchableMobileNet'] |
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