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| _base_ = [ | |
| '../_base_/models/setr_pup.py', '../_base_/datasets/cityscapes_768x768.py', | |
| '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' | |
| ] | |
| crop_size = (768, 768) | |
| data_preprocessor = dict(size=crop_size) | |
| norm_cfg = dict(type='SyncBN', requires_grad=True) | |
| crop_size = (768, 768) | |
| model = dict( | |
| data_preprocessor=data_preprocessor, | |
| pretrained=None, | |
| backbone=dict( | |
| drop_rate=0., | |
| init_cfg=dict( | |
| type='Pretrained', checkpoint='pretrain/vit_large_p16.pth')), | |
| auxiliary_head=[ | |
| dict( | |
| type='SETRUPHead', | |
| in_channels=1024, | |
| channels=256, | |
| in_index=0, | |
| num_classes=19, | |
| dropout_ratio=0, | |
| norm_cfg=norm_cfg, | |
| num_convs=2, | |
| up_scale=4, | |
| kernel_size=3, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), | |
| dict( | |
| type='SETRUPHead', | |
| in_channels=1024, | |
| channels=256, | |
| in_index=1, | |
| num_classes=19, | |
| dropout_ratio=0, | |
| norm_cfg=norm_cfg, | |
| num_convs=2, | |
| up_scale=4, | |
| kernel_size=3, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), | |
| dict( | |
| type='SETRUPHead', | |
| in_channels=1024, | |
| channels=256, | |
| in_index=2, | |
| num_classes=19, | |
| dropout_ratio=0, | |
| norm_cfg=norm_cfg, | |
| num_convs=2, | |
| up_scale=4, | |
| kernel_size=3, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)) | |
| ], | |
| test_cfg=dict(mode='slide', crop_size=crop_size, stride=(512, 512))) | |
| optimizer = dict(weight_decay=0.0) | |
| optim_wrapper = dict( | |
| type='OptimWrapper', | |
| optimizer=optimizer, | |
| paramwise_cfg=dict(custom_keys={'head': dict(lr_mult=10.)})) | |
| train_dataloader = dict(batch_size=1) | |
| val_dataloader = dict(batch_size=1) | |
| test_dataloader = val_dataloader | |