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open-mmlab
open-mmlab
[Bug] Error when loading weights for models
分支
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
Have you solved this issue? I'm facing s similar problem.
Traceback (most recent call last):
File "./tools/train.py", line 162, in
config file with : load_from = '/home/mchmu/datasets/DP/RSCD-dataset-1million/resnet18_8xb32_in1k_20210831-fbbb1da6.pth'
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.