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joe-siyuan-qiao / DetectoRS

DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution
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The problem is “The model and loaded state dict do not match exactly” #63

Open Wenting-Xu opened 4 years ago

Wenting-Xu commented 4 years ago

Thanks for your error report and we appreciate it a lot.

Checklist

  1. I have searched related issues but cannot get the expected help.
  2. The bug has not been fixed in the latest version.

Describe the bug I train my dataset as coco formI can properly train myself for data sets in coco format.bue i got an warming Reproduction

  1. Did you make any modifications on the code or config? Did you understand what you have modified? i just change num_classes

  2. What dataset did you use? my own dataset as coco format.it contain 21 classes Environment

  3. Please run python mmdet/utils/collect_env.py to collect necessary environment infomation and paste it here. sys.platform: linux Python: 3.7.7 (default, May 7 2020, 21:25:33) [GCC 7.3.0] CUDA available: True CUDA_HOME: /usr/local/cuda-10.1 NVCC: Cuda compilation tools, release 10.1, V10.1.243 GPU 0,1,2,3: Tesla V100-DGXS-32GB GCC: gcc (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0 PyTorch: 1.4.0 PyTorch compiling details: PyTorch built with:

    • GCC 7.3
    • Intel(R) Math Kernel Library Version 2020.0.1 Product Build 20200208 for Intel(R) 64 architecture applications
    • Intel(R) MKL-DNN v0.21.1 (Git Hash 7d2fd500bc78936d1d648ca713b901012f470dbc)
    • OpenMP 201511 (a.k.a. OpenMP 4.5)
    • NNPACK is enabled
    • CUDA Runtime 10.0
    • 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 2.5.1
    • Build settings: BLAS=MKL, BUILD_NAMEDTENSOR=OFF, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -fopenmp -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -O2 -fPIC -Wno-narrowing -Wall -Wextra -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-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 -Wno-stringop-overflow, DISABLE_NUMA=1, 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: 0.5.0 OpenCV: 4.3.0 MMCV: 1.0.4 MMDetection: 1.1.0+unknown MMDetection Compiler: GCC 7.4 MMDetection CUDA Compiler: 10.1

Error traceback If applicable, paste the error trackback here.

2020-07-27 09:29:04,833 - mmdet - WARNING - The model and loaded state dict do not match exactly

unexpected key in source state_dict: layer3.6.conv1.weight, layer3.6.bn1.weight, layer3.6.bn1.bias, layer3.6.bn1.running_mean, layer3.6.bn1.running_var, layer3.6.conv2.weight, layer3.6.bn2.weight, layer3.6.bn2.bias, layer3.6.bn2.running_mean, layer3.6.bn2.running_var, layer3.6.conv3.weight, layer3.6.bn3.weight, layer3.6.bn3.bias, layer3.6.bn3.running_mean, layer3.6.bn3.running_var, layer3.7.conv1.weight, layer3.7.bn1.weight, layer3.7.bn1.bias, layer3.7.bn1.running_mean, layer3.7.bn1.running_var, layer3.7.conv2.weight, layer3.7.bn2.weight, layer3.7.bn2.bias, layer3.7.bn2.running_mean, layer3.7.bn2.running_var, layer3.7.conv3.weight, layer3.7.bn3.weight, layer3.7.bn3.bias, layer3.7.bn3.running_mean, layer3.7.bn3.running_var, layer3.8.conv1.weight, layer3.8.bn1.weight, layer3.8.bn1.bias, layer3.8.bn1.running_mean, layer3.8.bn1.running_var, layer3.8.conv2.weight, layer3.8.bn2.weight, layer3.8.bn2.bias, layer3.8.bn2.running_mean, layer3.8.bn2.running_var, layer3.8.conv3.weight, layer3.8.bn3.weight, layer3.8.bn3.bias, layer3.8.bn3.running_mean, layer3.8.bn3.running_var, layer3.9.conv1.weight, layer3.9.bn1.weight, layer3.9.bn1.bias, layer3.9.bn1.running_mean, layer3.9.bn1.running_var, layer3.9.conv2.weight, layer3.9.bn2.weight, layer3.9.bn2.bias, layer3.9.bn2.running_mean, layer3.9.bn2.running_var, layer3.9.conv3.weight, layer3.9.bn3.weight, layer3.9.bn3.bias, layer3.9.bn3.running_mean, layer3.9.bn3.running_var, layer3.10.conv1.weight, layer3.10.bn1.weight, layer3.10.bn1.bias, layer3.10.bn1.running_mean, layer3.10.bn1.running_var, layer3.10.conv2.weight, layer3.10.bn2.weight, layer3.10.bn2.bias, layer3.10.bn2.running_mean, layer3.10.bn2.running_var, layer3.10.conv3.weight, layer3.10.bn3.weight, layer3.10.bn3.bias, layer3.10.bn3.running_mean, layer3.10.bn3.running_var, layer3.11.conv1.weight, layer3.11.bn1.weight, layer3.11.bn1.bias, layer3.11.bn1.running_mean, layer3.11.bn1.running_var, layer3.11.conv2.weight, layer3.11.bn2.weight, layer3.11.bn2.bias, layer3.11.bn2.running_mean, layer3.11.bn2.running_var, layer3.11.conv3.weight, layer3.11.bn3.weight, layer3.11.bn3.bias, layer3.11.bn3.running_mean, layer3.11.bn3.running_var, layer3.12.conv1.weight, layer3.12.bn1.weight, layer3.12.bn1.bias, layer3.12.bn1.running_mean, layer3.12.bn1.running_var, layer3.12.conv2.weight, layer3.12.bn2.weight, layer3.12.bn2.bias, layer3.12.bn2.running_mean, layer3.12.bn2.running_var, layer3.12.conv3.weight, layer3.12.bn3.weight, layer3.12.bn3.bias, layer3.12.bn3.running_mean, layer3.12.bn3.running_var, layer3.13.conv1.weight, layer3.13.bn1.weight, layer3.13.bn1.bias, layer3.13.bn1.running_mean, layer3.13.bn1.running_var, layer3.13.conv2.weight, layer3.13.bn2.weight, layer3.13.bn2.bias, layer3.13.bn2.running_mean, layer3.13.bn2.running_var, layer3.13.conv3.weight, layer3.13.bn3.weight, layer3.13.bn3.bias, layer3.13.bn3.running_mean, layer3.13.bn3.running_var, layer3.14.conv1.weight, layer3.14.bn1.weight, layer3.14.bn1.bias, layer3.14.bn1.running_mean, layer3.14.bn1.running_var, layer3.14.conv2.weight, layer3.14.bn2.weight, layer3.14.bn2.bias, layer3.14.bn2.running_mean, layer3.14.bn2.running_var, layer3.14.conv3.weight, layer3.14.bn3.weight, layer3.14.bn3.bias, layer3.14.bn3.running_mean, layer3.14.bn3.running_var, layer3.15.conv1.weight, layer3.15.bn1.weight, layer3.15.bn1.bias, layer3.15.bn1.running_mean, layer3.15.bn1.running_var, layer3.15.conv2.weight, layer3.15.bn2.weight, layer3.15.bn2.bias, layer3.15.bn2.running_mean, layer3.15.bn2.running_var, layer3.15.conv3.weight, layer3.15.bn3.weight, layer3.15.bn3.bias, layer3.15.bn3.running_mean, layer3.15.bn3.running_var, layer3.16.conv1.weight, layer3.16.bn1.weight, layer3.16.bn1.bias, layer3.16.bn1.running_mean, layer3.16.bn1.running_var, layer3.16.conv2.weight, layer3.16.bn2.weight, layer3.16.bn2.bias, layer3.16.bn2.running_mean, layer3.16.bn2.running_var, layer3.16.conv3.weight, layer3.16.bn3.weight, layer3.16.bn3.bias, layer3.16.bn3.running_mean, layer3.16.bn3.running_var, layer3.17.conv1.weight, layer3.17.bn1.weight, layer3.17.bn1.bias, layer3.17.bn1.running_mean, layer3.17.bn1.running_var, layer3.17.conv2.weight, layer3.17.bn2.weight, layer3.17.bn2.bias, layer3.17.bn2.running_mean, layer3.17.bn2.running_var, layer3.17.conv3.weight, layer3.17.bn3.weight, layer3.17.bn3.bias, layer3.17.bn3.running_mean, layer3.17.bn3.running_var, layer3.18.conv1.weight, layer3.18.bn1.weight, layer3.18.bn1.bias, layer3.18.bn1.running_mean, layer3.18.bn1.running_var, layer3.18.conv2.weight, layer3.18.bn2.weight, layer3.18.bn2.bias, layer3.18.bn2.running_mean, layer3.18.bn2.running_var, layer3.18.conv3.weight, layer3.18.bn3.weight, layer3.18.bn3.bias, layer3.18.bn3.running_mean, layer3.18.bn3.running_var, layer3.19.conv1.weight, layer3.19.bn1.weight, layer3.19.bn1.bias, layer3.19.bn1.running_mean, layer3.19.bn1.running_var, layer3.19.conv2.weight, layer3.19.bn2.weight, layer3.19.bn2.bias, layer3.19.bn2.running_mean, layer3.19.bn2.running_var, layer3.19.conv3.weight, layer3.19.bn3.weight, layer3.19.bn3.bias, layer3.19.bn3.running_mean, layer3.19.bn3.running_var, layer3.20.conv1.weight, layer3.20.bn1.weight, layer3.20.bn1.bias, layer3.20.bn1.running_mean, layer3.20.bn1.running_var, layer3.20.conv2.weight, layer3.20.bn2.weight, layer3.20.bn2.bias, layer3.20.bn2.running_mean, layer3.20.bn2.running_var, layer3.20.conv3.weight, layer3.20.bn3.weight, layer3.20.bn3.bias, layer3.20.bn3.running_mean, layer3.20.bn3.running_var, layer3.21.conv1.weight, layer3.21.bn1.weight, layer3.21.bn1.bias, layer3.21.bn1.running_mean, layer3.21.bn1.running_var, layer3.21.conv2.weight, layer3.21.bn2.weight, layer3.21.bn2.bias, layer3.21.bn2.running_mean, layer3.21.bn2.running_var, layer3.21.conv3.weight, layer3.21.bn3.weight, layer3.21.bn3.bias, layer3.21.bn3.running_mean, layer3.21.bn3.running_var, layer3.22.conv1.weight, layer3.22.bn1.weight, layer3.22.bn1.bias, layer3.22.bn1.running_mean, layer3.22.bn1.running_var, layer3.22.conv2.weight, layer3.22.bn2.weight, layer3.22.bn2.bias, layer3.22.bn2.running_mean, layer3.22.bn2.running_var, layer3.22.conv3.weight, layer3.22.bn3.weight, layer3.22.bn3.bias, layer3.22.bn3.running_mean, layer3.22.bn3.running_var

missing keys in source state_dict: conv1.weight_gamma, conv1.weight_beta, layer1.0.conv1.weight_gamma, layer1.0.conv1.weight_beta, layer1.0.conv2.weight_gamma, layer1.0.conv2.weight_beta, layer1.0.conv3.weight_gamma, layer1.0.conv3.weight_beta, layer1.0.downsample.0.weight_gamma, layer1.0.downsample.0.weight_beta, layer1.1.conv1.weight_gamma, layer1.1.conv1.weight_beta, layer1.1.conv2.weight_gamma, layer1.1.conv2.weight_beta, layer1.1.conv3.weight_gamma, layer1.1.conv3.weight_beta, layer1.2.conv1.weight_gamma, layer1.2.conv1.weight_beta, layer1.2.conv2.weight_gamma, layer1.2.conv2.weight_beta, layer1.2.conv3.weight_gamma, layer1.2.conv3.weight_beta, layer2.0.conv1.weight_gamma, layer2.0.conv1.weight_beta, layer2.0.conv2.weight_diff, layer2.0.conv2.weight_gamma, layer2.0.conv2.weight_beta, layer2.0.conv2.switch.weight, layer2.0.conv2.switch.bias, layer2.0.conv2.pre_context.weight, layer2.0.conv2.pre_context.bias, layer2.0.conv2.post_context.weight, layer2.0.conv2.post_context.bias, layer2.0.conv2.offset_s.weight, layer2.0.conv2.offset_s.bias, layer2.0.conv2.offset_l.weight, layer2.0.conv2.offset_l.bias, layer2.0.conv3.weight_gamma, layer2.0.conv3.weight_beta, layer2.0.downsample.0.weight_gamma, layer2.0.downsample.0.weight_beta, layer2.1.conv1.weight_gamma, layer2.1.conv1.weight_beta, layer2.1.conv2.weight_diff, layer2.1.conv2.weight_gamma, layer2.1.conv2.weight_beta, layer2.1.conv2.switch.weight, layer2.1.conv2.switch.bias, layer2.1.conv2.pre_context.weight, layer2.1.conv2.pre_context.bias, layer2.1.conv2.post_context.weight, layer2.1.conv2.post_context.bias, layer2.1.conv2.offset_s.weight, layer2.1.conv2.offset_s.bias, layer2.1.conv2.offset_l.weight, layer2.1.conv2.offset_l.bias, layer2.1.conv3.weight_gamma, layer2.1.conv3.weight_beta, layer2.2.conv1.weight_gamma, layer2.2.conv1.weight_beta, layer2.2.conv2.weight_diff, layer2.2.conv2.weight_gamma, layer2.2.conv2.weight_beta, layer2.2.conv2.switch.weight, layer2.2.conv2.switch.bias, layer2.2.conv2.pre_context.weight, layer2.2.conv2.pre_context.bias, layer2.2.conv2.post_context.weight, layer2.2.conv2.post_context.bias, layer2.2.conv2.offset_s.weight, layer2.2.conv2.offset_s.bias, layer2.2.conv2.offset_l.weight, layer2.2.conv2.offset_l.bias, layer2.2.conv3.weight_gamma, layer2.2.conv3.weight_beta, layer2.3.conv1.weight_gamma, layer2.3.conv1.weight_beta, layer2.3.conv2.weight_diff, layer2.3.conv2.weight_gamma, layer2.3.conv2.weight_beta, layer2.3.conv2.switch.weight, layer2.3.conv2.switch.bias, layer2.3.conv2.pre_context.weight, layer2.3.conv2.pre_context.bias, layer2.3.conv2.post_context.weight, layer2.3.conv2.post_context.bias, layer2.3.conv2.offset_s.weight, layer2.3.conv2.offset_s.bias, layer2.3.conv2.offset_l.weight, layer2.3.conv2.offset_l.bias, layer2.3.conv3.weight_gamma, layer2.3.conv3.weight_beta, layer3.0.conv1.weight_gamma, layer3.0.conv1.weight_beta, layer3.0.conv2.weight_diff, layer3.0.conv2.weight_gamma, layer3.0.conv2.weight_beta, layer3.0.conv2.switch.weight, layer3.0.conv2.switch.bias, layer3.0.conv2.pre_context.weight, layer3.0.conv2.pre_context.bias, layer3.0.conv2.post_context.weight, layer3.0.conv2.post_context.bias, layer3.0.conv2.offset_s.weight, layer3.0.conv2.offset_s.bias, layer3.0.conv2.offset_l.weight, layer3.0.conv2.offset_l.bias, layer3.0.conv3.weight_gamma, layer3.0.conv3.weight_beta, layer3.0.downsample.0.weight_gamma, layer3.0.downsample.0.weight_beta, layer3.1.conv1.weight_gamma, layer3.1.conv1.weight_beta, layer3.1.conv2.weight_diff, layer3.1.conv2.weight_gamma, layer3.1.conv2.weight_beta, layer3.1.conv2.switch.weight, layer3.1.conv2.switch.bias, layer3.1.conv2.pre_context.weight, layer3.1.conv2.pre_context.bias, layer3.1.conv2.post_context.weight, layer3.1.conv2.post_context.bias, layer3.1.conv2.offset_s.weight, layer3.1.conv2.offset_s.bias, layer3.1.conv2.offset_l.weight, layer3.1.conv2.offset_l.bias, layer3.1.conv3.weight_gamma, layer3.1.conv3.weight_beta, layer3.2.conv1.weight_gamma, layer3.2.conv1.weight_beta, layer3.2.conv2.weight_diff, layer3.2.conv2.weight_gamma, layer3.2.conv2.weight_beta, layer3.2.conv2.switch.weight, layer3.2.conv2.switch.bias, layer3.2.conv2.pre_context.weight, layer3.2.conv2.pre_context.bias, layer3.2.conv2.post_context.weight, layer3.2.conv2.post_context.bias, layer3.2.conv2.offset_s.weight, layer3.2.conv2.offset_s.bias, layer3.2.conv2.offset_l.weight, layer3.2.conv2.offset_l.bias, layer3.2.conv3.weight_gamma, layer3.2.conv3.weight_beta, layer3.3.conv1.weight_gamma, layer3.3.conv1.weight_beta, layer3.3.conv2.weight_diff, layer3.3.conv2.weight_gamma, layer3.3.conv2.weight_beta, layer3.3.conv2.switch.weight, layer3.3.conv2.switch.bias, layer3.3.conv2.pre_context.weight, layer3.3.conv2.pre_context.bias, layer3.3.conv2.post_context.weight, layer3.3.conv2.post_context.bias, layer3.3.conv2.offset_s.weight, layer3.3.conv2.offset_s.bias, layer3.3.conv2.offset_l.weight, layer3.3.conv2.offset_l.bias, layer3.3.conv3.weight_gamma, layer3.3.conv3.weight_beta, layer3.4.conv1.weight_gamma, layer3.4.conv1.weight_beta, layer3.4.conv2.weight_diff, layer3.4.conv2.weight_gamma, layer3.4.conv2.weight_beta, layer3.4.conv2.switch.weight, layer3.4.conv2.switch.bias, layer3.4.conv2.pre_context.weight, layer3.4.conv2.pre_context.bias, layer3.4.conv2.post_context.weight, layer3.4.conv2.post_context.bias, layer3.4.conv2.offset_s.weight, layer3.4.conv2.offset_s.bias, layer3.4.conv2.offset_l.weight, layer3.4.conv2.offset_l.bias, layer3.4.conv3.weight_gamma, layer3.4.conv3.weight_beta, layer3.5.conv1.weight_gamma, layer3.5.conv1.weight_beta, layer3.5.conv2.weight_diff, layer3.5.conv2.weight_gamma, layer3.5.conv2.weight_beta, layer3.5.conv2.switch.weight, layer3.5.conv2.switch.bias, layer3.5.conv2.pre_context.weight, layer3.5.conv2.pre_context.bias, layer3.5.conv2.post_context.weight, layer3.5.conv2.post_context.bias, layer3.5.conv2.offset_s.weight, layer3.5.conv2.offset_s.bias, layer3.5.conv2.offset_l.weight, layer3.5.conv2.offset_l.bias, layer3.5.conv3.weight_gamma, layer3.5.conv3.weight_beta, layer4.0.conv1.weight_gamma, layer4.0.conv1.weight_beta, layer4.0.conv2.weight_diff, layer4.0.conv2.weight_gamma, layer4.0.conv2.weight_beta, layer4.0.conv2.switch.weight, layer4.0.conv2.switch.bias, layer4.0.conv2.pre_context.weight, layer4.0.conv2.pre_context.bias, layer4.0.conv2.post_context.weight, layer4.0.conv2.post_context.bias, layer4.0.conv2.offset_s.weight, layer4.0.conv2.offset_s.bias, layer4.0.conv2.offset_l.weight, layer4.0.conv2.offset_l.bias, layer4.0.conv3.weight_gamma, layer4.0.conv3.weight_beta, layer4.0.downsample.0.weight_gamma, layer4.0.downsample.0.weight_beta, layer4.1.conv1.weight_gamma, layer4.1.conv1.weight_beta, layer4.1.conv2.weight_diff, layer4.1.conv2.weight_gamma, layer4.1.conv2.weight_beta, layer4.1.conv2.switch.weight, layer4.1.conv2.switch.bias, layer4.1.conv2.pre_context.weight, layer4.1.conv2.pre_context.bias, layer4.1.conv2.post_context.weight, layer4.1.conv2.post_context.bias, layer4.1.conv2.offset_s.weight, layer4.1.conv2.offset_s.bias, layer4.1.conv2.offset_l.weight, layer4.1.conv2.offset_l.bias, layer4.1.conv3.weight_gamma, layer4.1.conv3.weight_beta, layer4.2.conv1.weight_gamma, layer4.2.conv1.weight_beta, layer4.2.conv2.weight_diff, layer4.2.conv2.weight_gamma, layer4.2.conv2.weight_beta, layer4.2.conv2.switch.weight, layer4.2.conv2.switch.bias, layer4.2.conv2.pre_context.weight, layer4.2.conv2.pre_context.bias, layer4.2.conv2.post_context.weight, layer4.2.conv2.post_context.bias, layer4.2.conv2.offset_s.weight, layer4.2.conv2.offset_s.bias, layer4.2.conv2.offset_l.weight, layer4.2.conv2.offset_l.bias, layer4.2.conv3.weight_gamma, layer4.2.conv3.weight_beta

Bug fix If you have already identified the reason, you can provide the information here. If you are willing to create a PR to fix it, please also leave a comment here and that would be much appreciated!

cch2016 commented 4 years ago

I replace backbone resnet50 with resnext101, I meet missing keys in source state_dict problem:

2020-08-11 10:25:03,000 - mmdet - INFO - load model from: open-mmlab://resnext101_32x4d
2020-08-11 10:25:27,770 - mmdet - WARNING - The model and loaded state dict do not match exactly

missing keys in source state_dict: layer2.0.conv2.weight_diff, layer2.0.conv2.switch.weight, layer2.0.conv2.switch.bias, layer2.0.conv2.pre_context.weight, layer2.0.conv2.pre_context.bias, layer2.0.conv2.post_context.weight, layer2.0.conv2.post_context.bias, layer2.0.conv2.offset_s.weight, layer2.0.conv2.offset_s.bias, layer2.0.conv2.offset_l.weight, layer2.0.conv2.offset_l.bias, layer2.1.conv2.weight_diff, layer2.1.conv2.switch.weight, layer2.1.conv2.switch.bias, layer2.1.conv2.pre_context.weight, layer2.1.conv2.pre_context.bias, layer2.1.conv2.post_context.weight, layer2.1.conv2.post_context.bias, layer2.1.conv2.offset_s.weight, layer2.1.conv2.offset_s.bias, layer2.1.conv2.offset_l.weight, layer2.1.conv2.offset_l.bias, layer2.2.conv2.weight_diff, layer2.2.conv2.switch.weight, layer2.2.conv2.switch.bias, layer2.2.conv2.pre_context.weight, layer2.2.conv2.pre_context.bias, layer2.2.conv2.post_context.weight, layer2.2.conv2.post_context.bias, layer2.2.conv2.offset_s.weight, layer2.2.conv2.offset_s.bias, layer2.2.conv2.offset_l.weight, layer2.2.conv2.offset_l.bias, layer2.3.conv2.weight_diff, layer2.3.conv2.switch.weight, layer2.3.conv2.switch.bias, layer2.3.conv2.pre_context.weight, layer2.3.conv2.pre_context.bias, layer2.3.conv2.post_context.weight, layer2.3.conv2.post_context.bias, layer2.3.conv2.offset_s.weight, layer2.3.conv2.offset_s.bias, layer2.3.conv2.offset_l.weight, layer2.3.conv2.offset_l.bias, layer3.0.conv2.weight_diff
dsnqr commented 4 years ago

I also encountered the same problem. How did you solve it later? I really want to know as soon as possible, looking forward to your reply! Thank you very much.