pose estimation 任务训练报错 KeyError: 'SwinTransformer is not in the models registry'

[needsee]

我在下载预训练后的solider_swin_base.pth，运行pose任务的训练时报错如下：

fp16 = dict(loss_scale='dynamic') work_dir = './work_dirs/swin_base_coco_384x288_lly' gpu_ids = range(0, 1)

2023-09-25 16:03:15,197 - mmpose - INFO - Set random seed to 1071184448, deterministic: False Traceback (most recent call last): File "/data1/user/lly/miniconda3/envs/mmcv/lib/python3.7/site-packages/mmcv/utils/registry.py", line 52, in build_from_cfg return obj_cls(*args) File "/data1/user/lly/work/pkg/mmpose-0.25.0/mmpose/models/detectors/top_down.py", line 48, in init self.backbone = builder.build_backbone(backbone) File "/data1/user/lly/work/pkg/mmpose-0.25.0/mmpose/models/builder.py", line 19, in build_backbone return BACKBONES.build(cfg) File "/data1/user/lly/miniconda3/envs/mmcv/lib/python3.7/site-packages/mmcv/utils/registry.py", line 212, in build return self.build_func(args, **kwargs, registry=self) File "/data1/user/lly/miniconda3/envs/mmcv/lib/python3.7/site-packages/mmcv/cnn/builder.py", line 27, in build_model_from_cfg return build_from_cfg(cfg, registry, default_args) File "/data1/user/lly/miniconda3/envs/mmcv/lib/python3.7/site-packages/mmcv/utils/registry.py", line 45, in build_from_cfg f'{obj_type} is not in the {registry.name} registry') KeyError: 'SwinTransformer is not in the models registry'

请问应该怎么解决呢？ 我的环境信息如下： sys.platform: linux Python: 3.7.16 (default, Jan 17 2023, 22:20:44) [GCC 11.2.0] CUDA available: True GPU 0,1,2,3: NVIDIA GeForce RTX 4090 CUDA_HOME: /usr NVCC: Cuda compilation tools, release 10.1, V10.1.243 GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 PyTorch: 1.6.0 PyTorch compiling details: PyTorch built with:

• GCC 7.3
• C++ Version: 201402
• Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
• Intel(R) MKL-DNN v1.5.0 (Git Hash e2ac1fac44c5078ca927cb9b90e1b3066a0b2ed0)
• OpenMP 201511 (a.k.a. OpenMP 4.5)
• NNPACK is enabled
• CPU capability usage: AVX2
• CUDA Runtime 10.1
• NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
• CuDNN 7.6.3
• Magma 2.5.2
• Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_STATIC_DISPATCH=OFF,

TorchVision: 0.7.0 OpenCV: 4.8.0 MMCV: 1.3.17 MMCV Compiler: GCC 7.3 MMCV CUDA Compiler: 10.1 MMPose: 0.25.0+fd361ca