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model = dict( |
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type='ImageClassifier', |
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backbone=dict(type='VAN', arch='tiny', drop_path_rate=0.1), |
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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=256, |
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init_cfg=None, |
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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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