34 lines
848 B
Python
34 lines
848 B
Python
model = dict(
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type='ImageClassifier',
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backbone=dict(
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type='Vig',
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arch='tiny',
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k=9,
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act_cfg=dict(type='GELU'),
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norm_cfg=dict(type='BN'),
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graph_conv_type='mr',
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graph_conv_bias=True,
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epsilon=0.2,
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use_dilation=True,
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use_stochastic=False,
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drop_path=0.1,
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relative_pos=False,
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norm_eval=False,
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frozen_stages=0),
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neck=dict(type='GlobalAveragePooling'),
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head=dict(
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type='VigClsHead',
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num_classes=1000,
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in_channels=192,
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hidden_dim=1024,
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act_cfg=dict(type='GELU'),
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dropout=0.,
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loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
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topk=(1, 5),
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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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