[Bug] Error when loading weights for models

[OnlyForWW]

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main 分支 (mmpretrain 版本)

描述该错误

Hello,I have some questions about model loading weights, I have downloaded the pre-trained model of MMPretrain locally in advance, but when I use torch.load_state_dict() it gives an error, I would like to know how to solve this problem or do I have to load the pre-trained model the way it is documented.

Here's my code.

from mmpretrain import get_model
import torch
net = get_model('resnet50_mocov3-800e-pre_8xb128-linear-coslr-90e_in1k', pretrained=False)
cheak_points = torch.load('./resnet50_linear-8xb128-coslr-90e_in1k_20220927-0e97a483.pth')
net.load_state_dict(cheak_points)
print(net)

When I run it, I get the following error.

raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for ImageClassifier:
    Missing key(s) in state_dict: "backbone.conv1.weight", "backbone.bn1.weight", "backbone.bn1.bias", "backbone.bn1.running_mean", "backbone.bn1.running_var", "backbone.layer1.0.conv1.weight", "backbone.layer1.0.bn1.weight", "backbone.layer1.0.bn1.bias", "backbone.layer1.0.bn1.running_mean", "backbone.layer1.0.bn1.running_var", "backbone.layer1.0.conv2.weight", "backbone.layer1.0.bn2.weight", "backbone.layer1.0.bn2.bias", "backbone.layer1.0.bn2.running_mean", "backbone.layer1.0.bn2.running_var", "backbone.layer1.0.conv3.weight", "backbone.layer1.0.bn3.weight", "backbone.layer1.0.bn3.bias", "backbone.layer1.0.bn3.running_mean", "backbone.layer1.0.bn3.running_var", "backbone.layer1.0.downsample.0.weight", "backbone.layer1.0.downsample.1.weight", "backbone.layer1.0.downsample.1.bias", "backbone.layer1.0.downsample.1.running_mean", "backbone.layer1.0.downsample.1.running_var", "backbone.layer1.1.conv1.weight", "backbone.layer1.1.bn1.weight", "backbone.layer1.1.bn1.bias", "backbone.layer1.1.bn1.running_mean", "backbone.layer1.1.bn1.running_var", "backbone.layer1.1.conv2.weight", "backbone.layer1.1.bn2.weight", "backbone.layer1.1.bn2.bias", "backbone.layer1.1.bn2.running_mean", "backbone.layer1.1.bn2.running_var", "backbone.layer1.1.conv3.weight", "backbone.layer1.1.bn3.weight", "backbone.layer1.1.bn3.bias", "backbone.layer1.1.bn3.running_mean", "backbone.layer1.1.bn3.running_var", "backbone.layer1.2.conv1.weight", "backbone.layer1.2.bn1.weight", "backbone.layer1.2.bn1.bias", "backbone.layer1.2.bn1.running_mean", "backbone.layer1.2.bn1.running_var", "backbone.layer1.2.conv2.weight", "backbone.layer1.2.bn2.weight", "backbone.layer1.2.bn2.bias", "backbone.layer1.2.bn2.running_mean", "backbone.layer1.2.bn2.running_var", "backbone.layer1.2.conv3.weight", "backbone.layer1.2.bn3.weight", "backbone.layer1.2.bn3.bias", "backbone.layer1.2.bn3.running_mean", "backbone.layer1.2.bn3.running_var", "backbone.layer2.0.conv1.weight", "backbone.layer2.0.bn1.weight", "backbone.layer2.0.bn1.bias", "backbone.layer2.0.bn1.running_mean", "backbone.layer2.0.bn1.running_var", "backbone.layer2.0.conv2.weight", "backbone.layer2.0.bn2.weight", "backbone.layer2.0.bn2.bias", "backbone.layer2.0.bn2.running_mean", "backbone.layer2.0.bn2.running_var", "backbone.layer2.0.conv3.weight", "backbone.layer2.0.bn3.weight", "backbone.layer2.0.bn3.bias", "backbone.layer2.0.bn3.running_mean", "backbone.layer2.0.bn3.running_var", "backbone.layer2.0.downsample.0.weight", "backbone.layer2.0.downsample.1.weight", "backbone.layer2.0.downsample.1.bias", "backbone.layer2.0.downsample.1.running_mean", "backbone.layer2.0.downsample.1.running_var", "backbone.layer2.1.conv1.weight", "backbone.layer2.1.bn1.weight", "backbone.layer2.1.bn1.bias", "backbone.layer2.1.bn1.running_mean", "backbone.layer2.1.bn1.running_var", "backbone.layer2.1.conv2.weight", "backbone.layer2.1.bn2.weight", "backbone.layer2.1.bn2.bias", "backbone.layer2.1.bn2.running_mean", "backbone.layer2.1.bn2.running_var", "backbone.layer2.1.conv3.weight", "backbone.layer2.1.bn3.weight", "backbone.layer2.1.bn3.bias", "backbone.layer2.1.bn3.running_mean", "backbone.layer2.1.bn3.running_var", "backbone.layer2.2.conv1.weight", "backbone.layer2.2.bn1.weight", "backbone.layer2.2.bn1.bias", "backbone.layer2.2.bn1.running_mean", "backbone.layer2.2.bn1.running_var", "backbone.layer2.2.conv2.weight", "backbone.layer2.2.bn2.weight", "backbone.layer2.2.bn2.bias", "backbone.layer2.2.bn2.running_mean", "backbone.layer2.2.bn2.running_var", "backbone.layer2.2.conv3.weight", "backbone.layer2.2.bn3.weight", "backbone.layer2.2.bn3.bias", "backbone.layer2.2.bn3.running_mean", "backbone.layer2.2.bn3.running_var", "backbone.layer2.3.conv1.weight", "backbone.layer2.3.bn1.weight", "backbone.layer2.3.bn1.bias", "backbone.layer2.3.bn1.running_mean", "backbone.layer2.3.bn1.running_var", "backbone.layer2.3.conv2.weight", "backbone.layer2.3.bn2.weight", "backbone.layer2.3.bn2.bias", "backbone.layer2.3.bn2.running_mean", "backbone.layer2.3.bn2.running_var", "backbone.layer2.3.conv3.weight", "backbone.layer2.3.bn3.weight", "backbone.layer2.3.bn3.bias", "backbone.layer2.3.bn3.running_mean", "backbone.layer2.3.bn3.running_var", "backbone.layer3.0.conv1.weight", "backbone.layer3.0.bn1.weight", "backbone.layer3.0.bn1.bias", "backbone.layer3.0.bn1.running_mean", "backbone.layer3.0.bn1.running_var", "backbone.layer3.0.conv2.weight", "backbone.layer3.0.bn2.weight", "backbone.layer3.0.bn2.bias", "backbone.layer3.0.bn2.running_mean", "backbone.layer3.0.bn2.running_var", "backbone.layer3.0.conv3.weight", "backbone.layer3.0.bn3.weight", "backbone.layer3.0.bn3.bias", "backbone.layer3.0.bn3.running_mean", "backbone.layer3.0.bn3.running_var", "backbone.layer3.0.downsample.0.weight", "backbone.layer3.0.downsample.1.weight", "backbone.layer3.0.downsample.1.bias", "backbone.layer3.0.downsample.1.running_mean", "backbone.layer3.0.downsample.1.running_var", "backbone.layer3.1.conv1.weight", "backbone.layer3.1.bn1.weight", "backbone.layer3.1.bn1.bias", "backbone.layer3.1.bn1.running_mean", "backbone.layer3.1.bn1.running_var", "backbone.layer3.1.conv2.weight", "backbone.layer3.1.bn2.weight", "backbone.layer3.1.bn2.bias", "backbone.layer3.1.bn2.running_mean", "backbone.layer3.1.bn2.running_var", "backbone.layer3.1.conv3.weight", "backbone.layer3.1.bn3.weight", "backbone.layer3.1.bn3.bias", "backbone.layer3.1.bn3.running_mean", "backbone.layer3.1.bn3.running_var", "backbone.layer3.2.conv1.weight", "backbone.layer3.2.bn1.weight", "backbone.layer3.2.bn1.bias", "backbone.layer3.2.bn1.running_mean", "backbone.layer3.2.bn1.running_var", "backbone.layer3.2.conv2.weight", "backbone.layer3.2.bn2.weight", "backbone.layer3.2.bn2.bias", "backbone.layer3.2.bn2.running_mean", "backbone.layer3.2.bn2.running_var", "backbone.layer3.2.conv3.weight", "backbone.layer3.2.bn3.weight", "backbone.layer3.2.bn3.bias", "backbone.layer3.2.bn3.running_mean", "backbone.layer3.2.bn3.running_var", "backbone.layer3.3.conv1.weight", "backbone.layer3.3.bn1.weight", "backbone.layer3.3.bn1.bias", "backbone.layer3.3.bn1.running_mean", "backbone.layer3.3.bn1.running_var", "backbone.layer3.3.conv2.weight", "backbone.layer3.3.bn2.weight", "backbone.layer3.3.bn2.bias", "backbone.layer3.3.bn2.running_mean", "backbone.layer3.3.bn2.running_var", "backbone.layer3.3.conv3.weight", "backbone.layer3.3.bn3.weight", "backbone.layer3.3.bn3.bias", "backbone.layer3.3.bn3.running_mean", "backbone.layer3.3.bn3.running_var", "backbone.layer3.4.conv1.weight", "backbone.layer3.4.bn1.weight", "backbone.layer3.4.bn1.bias", "backbone.layer3.4.bn1.running_mean", "backbone.layer3.4.bn1.running_var", "backbone.layer3.4.conv2.weight", "backbone.layer3.4.bn2.weight", "backbone.layer3.4.bn2.bias", "backbone.layer3.4.bn2.running_mean", "backbone.layer3.4.bn2.running_var", "backbone.layer3.4.conv3.weight", "backbone.layer3.4.bn3.weight", "backbone.layer3.4.bn3.bias", "backbone.layer3.4.bn3.running_mean", "backbone.layer3.4.bn3.running_var", "backbone.layer3.5.conv1.weight", "backbone.layer3.5.bn1.weight", "backbone.layer3.5.bn1.bias", "backbone.layer3.5.bn1.running_mean", "backbone.layer3.5.bn1.running_var", "backbone.layer3.5.conv2.weight", "backbone.layer3.5.bn2.weight", "backbone.layer3.5.bn2.bias", "backbone.layer3.5.bn2.running_mean", "backbone.layer3.5.bn2.running_var", "backbone.layer3.5.conv3.weight", "backbone.layer3.5.bn3.weight", "backbone.layer3.5.bn3.bias", "backbone.layer3.5.bn3.running_mean", "backbone.layer3.5.bn3.running_var", "backbone.layer4.0.conv1.weight", "backbone.layer4.0.bn1.weight", "backbone.layer4.0.bn1.bias", "backbone.layer4.0.bn1.running_mean", "backbone.layer4.0.bn1.running_var", "backbone.layer4.0.conv2.weight", "backbone.layer4.0.bn2.weight", "backbone.layer4.0.bn2.bias", "backbone.layer4.0.bn2.running_mean", "backbone.layer4.0.bn2.running_var", "backbone.layer4.0.conv3.weight", "backbone.layer4.0.bn3.weight", "backbone.layer4.0.bn3.bias", "backbone.layer4.0.bn3.running_mean", "backbone.layer4.0.bn3.running_var", "backbone.layer4.0.downsample.0.weight", "backbone.layer4.0.downsample.1.weight", "backbone.layer4.0.downsample.1.bias", "backbone.layer4.0.downsample.1.running_mean", "backbone.layer4.0.downsample.1.running_var", "backbone.layer4.1.conv1.weight", "backbone.layer4.1.bn1.weight", "backbone.layer4.1.bn1.bias", "backbone.layer4.1.bn1.running_mean", "backbone.layer4.1.bn1.running_var", "backbone.layer4.1.conv2.weight", "backbone.layer4.1.bn2.weight", "backbone.layer4.1.bn2.bias", "backbone.layer4.1.bn2.running_mean", "backbone.layer4.1.bn2.running_var", "backbone.layer4.1.conv3.weight", "backbone.layer4.1.bn3.weight", "backbone.layer4.1.bn3.bias", "backbone.layer4.1.bn3.running_mean", "backbone.layer4.1.bn3.running_var", "backbone.layer4.2.conv1.weight", "backbone.layer4.2.bn1.weight", "backbone.layer4.2.bn1.bias", "backbone.layer4.2.bn1.running_mean", "backbone.layer4.2.bn1.running_var", "backbone.layer4.2.conv2.weight", "backbone.layer4.2.bn2.weight", "backbone.layer4.2.bn2.bias", "backbone.layer4.2.bn2.running_mean", "backbone.layer4.2.bn2.running_var", "backbone.layer4.2.conv3.weight", "backbone.layer4.2.bn3.weight", "backbone.layer4.2.bn3.bias", "backbone.layer4.2.bn3.running_mean", "backbone.layer4.2.bn3.running_var", "head.fc.weight", "head.fc.bias". 
    Unexpected key(s) in state_dict: "meta", "state_dict", "message_hub", "param_schedulers".

环境信息

{'sys.platform': 'win32',
 'Python': '3.9.18 (main, Sep 11 2023, 14:09:26) [MSC v.1916 64 bit (AMD64)]',
 'CUDA available': True,
 'numpy_random_seed': 2147483648,
 'GPU 0': 'NVIDIA GeForce RTX 3080',
 'CUDA_HOME': None,
 'MSVC': '用于 x64 的 Microsoft (R) C/C++ 优化编译器 19.37.32825 版',
 'GCC': 'n/a',
 'PyTorch': '2.0.1+cu118',
 'TorchVision': '0.15.2+cu118',
 'OpenCV': '4.8.1',
 'MMEngine': '0.9.1',
 'MMCV': '2.0.1',
 'MMPreTrain': '1.1.0+'}

其他信息

No response

[Mumengchao]

Have you solved this issue? I'm facing s similar problem. Traceback (most recent call last): File "./tools/train.py", line 162, in main() File "./tools/train.py", line 158, in main runner.train() File "/home/mchmu/miniconda3/envs/openmmlab_20240112/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1765, in train self.load_or_resume() File "/home/mchmu/miniconda3/envs/openmmlab_20240112/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1696, in load_or_resume self.resume(resume_from) File "/home/mchmu/miniconda3/envs/openmmlab_20240112/lib/python3.8/site-packages/mmengine/runner/runner.py", line 2075, in resume self.message_hub.load_state_dict(checkpoint['message_hub']) KeyError: 'message_hub'

config file with : load_from = '/home/mchmu/datasets/DP/RSCD-dataset-1million/resnet18_8xb32_in1k_20210831-fbbb1da6.pth'

[Mumengchao]

It might be that the "message_hub" wasn't created during the model training. I commented out this line:

self.message_hub.load_state_dict(checkpoint['message_hub'])

and now it runs fine. However, I'm not sure if there will be any other issues.