mmsegmentation 自定义模型报错：KeyError: ‘EncoderDecoder is not in the model registry
# mmsegmentation 自定义模型报错：KeyError: 'EncoderDecoder is not in the model registry'
在使用 `mmsegmentation` 自定义模型时，可能会遇到以下错误：
KeyError: 'EncoderDecoder is not in the model registry. Please check whether the value of EncoderDecoder is correct or it was registered as expected. More details can be found at https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#import-the-custom-module'
这通常是由于模型内部初始化问题引起的。
## 解决方法
在配置文件中添加以下内容：
```python
custom_imports = dict(
imports=['mmseg.models.backbones.rdt_fastvit'],
allow_failed_imports=False
)
修改后的配置文件示例：
# model settings
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
)
custom_imports = dict(imports=['mmseg.models.backbones.rdt_fastvit'],allow_failed_imports=False
)
model = dict(type='EncoderDecoder',data_preprocessor=data_preprocessor,backbone=dict(type='RDT_FastViT',model_name='rdt_sa12_s',pretrained=False,checkpoint_path='/path/rdt_fastvit_sa12.pth.tar',num_classes=1000,in_chans=3,drop_rate=0.1,global_pool='avg',retina_size=512,patch_number=4,use_residual=True,use_retina_field=False),neck=dict(type='FPN',in_channels=[64, 128, 256, 512],out_channels=256,num_outs=4),decode_head=dict(type='FPNHead',in_channels=[256, 256, 256, 256],in_index=[0, 1, 2, 3],feature_strides=[4, 8, 16, 32],channels=128,dropout_ratio=0.1,num_classes=19,norm_cfg=norm_cfg,align_corners=False,loss_decode=dict(type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),train_cfg=dict(),test_cfg=dict(mode='whole')
)
添加后，再次运行会显示详细的出错位置，例如：
ImportError: cannot import name 'PatchEmbedCifar' from 'timm.layers.patch_embed' (/root/anaconda3/envs/mmseg/lib/python3.9/site-packages/timm/layers/patch_embed.py)