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Runtime error
| # model settings | |
| backbone_norm_cfg = dict(type='LN', eps=1e-6, requires_grad=True) | |
| norm_cfg = dict(type='SyncBN', requires_grad=True) | |
| data_preprocessor = dict( | |
| type='SegDataPreProcessor', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| bgr_to_rgb=True, | |
| pad_val=0, | |
| seg_pad_val=255) | |
| model = dict( | |
| type='EncoderDecoder', | |
| data_preprocessor=data_preprocessor, | |
| pretrained='pretrain/jx_vit_large_p16_384-b3be5167.pth', | |
| backbone=dict( | |
| type='VisionTransformer', | |
| img_size=(768, 768), | |
| patch_size=16, | |
| in_channels=3, | |
| embed_dims=1024, | |
| num_layers=24, | |
| num_heads=16, | |
| out_indices=(5, 11, 17, 23), | |
| drop_rate=0.1, | |
| norm_cfg=backbone_norm_cfg, | |
| with_cls_token=False, | |
| interpolate_mode='bilinear', | |
| ), | |
| neck=dict( | |
| type='MLANeck', | |
| in_channels=[1024, 1024, 1024, 1024], | |
| out_channels=256, | |
| norm_cfg=norm_cfg, | |
| act_cfg=dict(type='ReLU'), | |
| ), | |
| decode_head=dict( | |
| type='SETRMLAHead', | |
| in_channels=(256, 256, 256, 256), | |
| channels=512, | |
| in_index=(0, 1, 2, 3), | |
| dropout_ratio=0, | |
| mla_channels=128, | |
| num_classes=19, | |
| norm_cfg=norm_cfg, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), | |
| auxiliary_head=[ | |
| dict( | |
| type='FCNHead', | |
| in_channels=256, | |
| channels=256, | |
| in_index=0, | |
| dropout_ratio=0, | |
| num_convs=0, | |
| kernel_size=1, | |
| concat_input=False, | |
| num_classes=19, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), | |
| dict( | |
| type='FCNHead', | |
| in_channels=256, | |
| channels=256, | |
| in_index=1, | |
| dropout_ratio=0, | |
| num_convs=0, | |
| kernel_size=1, | |
| concat_input=False, | |
| num_classes=19, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), | |
| dict( | |
| type='FCNHead', | |
| in_channels=256, | |
| channels=256, | |
| in_index=2, | |
| dropout_ratio=0, | |
| num_convs=0, | |
| kernel_size=1, | |
| concat_input=False, | |
| num_classes=19, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), | |
| dict( | |
| type='FCNHead', | |
| in_channels=256, | |
| channels=256, | |
| in_index=3, | |
| dropout_ratio=0, | |
| num_convs=0, | |
| kernel_size=1, | |
| concat_input=False, | |
| num_classes=19, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), | |
| ], | |
| train_cfg=dict(), | |
| test_cfg=dict(mode='whole')) | |