35 lines
993 B
Python
35 lines
993 B
Python
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# model settings
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norm_cfg = dict(type='SyncBN', requires_grad=True)
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model = dict(
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type='EncoderDecoder',
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pretrained=None,
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backbone=dict(
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type='MixVisionTransformer',
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in_channels=3,
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embed_dims=32,
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num_stages=4,
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num_layers=[2, 2, 2, 2],
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num_heads=[1, 2, 5, 8],
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patch_sizes=[7, 3, 3, 3],
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sr_ratios=[8, 4, 2, 1],
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out_indices=(0, 1, 2, 3),
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mlp_ratio=4,
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qkv_bias=True,
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drop_rate=0.0,
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attn_drop_rate=0.0,
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drop_path_rate=0.1),
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decode_head=dict(
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type='SegformerHead',
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in_channels=[32, 64, 160, 256],
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in_index=[0, 1, 2, 3],
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channels=256,
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dropout_ratio=0.1,
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num_classes=19,
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norm_cfg=norm_cfg,
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align_corners=False,
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loss_decode=dict(
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type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
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# model training and testing settings
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train_cfg=dict(),
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test_cfg=dict(mode='whole'))
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