32 lines
893 B
Python
32 lines
893 B
Python
# model settings
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model = dict(
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type='ImageClassifier',
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backbone=dict(
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type='SVT',
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arch='base',
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in_channels=3,
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out_indices=(3, ),
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qkv_bias=True,
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norm_cfg=dict(type='LN'),
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norm_after_stage=[False, False, False, True],
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drop_rate=0.0,
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attn_drop_rate=0.,
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drop_path_rate=0.3),
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neck=dict(type='GlobalAveragePooling'),
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head=dict(
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type='LinearClsHead',
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num_classes=1000,
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in_channels=768,
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loss=dict(
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type='LabelSmoothLoss', label_smooth_val=0.1, mode='original'),
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cal_acc=False),
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init_cfg=[
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dict(type='TruncNormal', layer='Linear', std=0.02, bias=0.),
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dict(type='Constant', layer='LayerNorm', val=1., bias=0.)
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],
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train_cfg=dict(augments=[
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dict(type='Mixup', alpha=0.8),
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dict(type='CutMix', alpha=1.0)
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]),
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)
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