Closed juliusyang97 closed 3 years ago
juliusyang97
commented
3 years ago 还有这个问题
CUDA_VISIBLE_DEVICES="0" python tools/trainval.py configs/trainval/tinaface/tinaface.py2020-12-19 22:32:14,872 - vedadet - WARNING - EvalHook is not in modes ['train']2020-12-19 22:32:14,873 - vedadet - INFO - Loading weights from torchvision://resnet502020-12-19 22:32:15,102 - vedadet - WARNING - The model and loaded state dict do not match exactly
hxcai
commented
3 years ago @juliusyang97 This is a warning means that model only load backbone weight and others are not loaded.
juliusyang97
commented
3 years ago @juliusyang97 This is a warning means that model only load backbone weight and others are not loaded.
您好，那这个运行时出现missing keys in source state_dict: neck.lateral_convs.0.conv.weight......一长串之后就一直不动，没反应，怎么回事啊，希望能得到您的解答
mike112223
commented
3 years ago Hi @juliusyang97, In order to speed up the training process, the default setting of logger's interval is 100 that may cause a long wait for printing the info. So you can modify this line 'dict(typename='LoggerHook', interval=100)' of hooks in config, e.g 'dict(typename='LoggerHook', interval=1)'
juliusyang97
commented
3 years ago In order to speed up the training process, the default setting of logger's interval is 100 that may cause a long wait for printing the info. So you can modify this line 'dict(typename='LoggerHook', interval=100)' of hooks in config, e.g 'dict(typename='LoggerHook', interval=1)'
好的好的， 谢谢我试一试
mike112223
commented
3 years ago @juliusyang97, if it is still stuck, please provide you config.
juliusyang97
commented
3 years ago 您好，我现在还有这个问题
Hi @juliusyang97, In order to speed up the training process, the default setting of logger's interval is 100 that may cause a long wait for printing the info. So you can modify this line 'dict(typename='LoggerHook', interval=100)' of hooks in config, e.g 'dict(typename='LoggerHook', interval=1)'
您好，我现在还是有这个问题
`CUDA_VISIBLE_DEVICES="0" python tools/trainval.py configs/trainval/tinaface/tinaface.py
2020-12-29 18:09:20,558 - vedadet - WARNING - EvalHook is not in modes ['train']
2020-12-29 18:09:20,559 - vedadet - INFO - Loading weights from torchvision://resnet50
2020-12-29 18:09:20,843 - vedadet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: backbone.bn1.running_mean, backbone.bn1.running_var, backbone.bn1.weight, backbone.bn1.bias, backbone.fc.weight, backbone.fc.bias, backbone.layer1.0.bn1.running_mean, backbone.layer1.0.bn1.running_var, backbone.layer1.0.bn1.weight, backbone.layer1.0.bn1.bias, backbone.layer1.0.bn2.running_mean, backbone.layer1.0.bn2.running_var, backbone.layer1.0.bn2.weight, backbone.layer1.0.bn2.bias, backbone.layer1.0.bn3.running_mean, backbone.layer1.0.bn3.running_var, backbone.layer1.0.bn3.weight, backbone.layer1.0.bn3.bias, backbone.layer1.0.downsample.1.running_mean, backbone.layer1.0.downsample.1.running_var, backbone.layer1.1.bn1.running_mean, backbone.layer1.1.bn1.running_var, backbone.layer1.1.bn1.weight, backbone.layer1.1.bn1.bias, backbone.layer1.1.bn2.running_mean, backbone.layer1.1.bn2.running_var, backbone.layer1.1.bn2.weight, backbone.layer1.1.bn2.bias, backbone.layer1.1.bn3.running_mean, backbone.layer1.1.bn3.running_var, backbone.layer1.1.bn3.weight, backbone.layer1.1.bn3.bias, backbone.layer1.2.bn1.running_mean, backbone.layer1.2.bn1.running_var, backbone.layer1.2.bn1.weight, backbone.layer1.2.bn1.bias, backbone.layer1.2.bn2.running_mean, backbone.layer1.2.bn2.running_var, backbone.layer1.2.bn2.weight, backbone.layer1.2.bn2.bias, backbone.layer1.2.bn3.running_mean, backbone.layer1.2.bn3.running_var, backbone.layer1.2.bn3.weight, backbone.layer1.2.bn3.bias, backbone.layer2.0.bn1.running_mean, backbone.layer2.0.bn1.running_var, backbone.layer2.0.bn1.weight, backbone.layer2.0.bn1.bias, backbone.layer2.0.bn2.running_mean, backbone.layer2.0.bn2.running_var, backbone.layer2.0.bn2.weight, backbone.layer2.0.bn2.bias, backbone.layer2.0.bn3.running_mean, backbone.layer2.0.bn3.running_var, backbone.layer2.0.bn3.weight, backbone.layer2.0.bn3.bias, backbone.layer2.0.downsample.1.running_mean, backbone.layer2.0.downsample.1.running_var, backbone.layer2.1.bn1.running_mean, backbone.layer2.1.bn1.running_var, backbone.layer2.1.bn1.weight, backbone.layer2.1.bn1.bias, backbone.layer2.1.bn2.running_mean, backbone.layer2.1.bn2.running_var, backbone.layer2.1.bn2.weight, backbone.layer2.1.bn2.bias, backbone.layer2.1.bn3.running_mean, backbone.layer2.1.bn3.running_var, backbone.layer2.1.bn3.weight, backbone.layer2.1.bn3.bias, backbone.layer2.2.bn1.running_mean, backbone.layer2.2.bn1.running_var, backbone.layer2.2.bn1.weight, backbone.layer2.2.bn1.bias, backbone.layer2.2.bn2.running_mean, backbone.layer2.2.bn2.running_var, backbone.layer2.2.bn2.weight, backbone.layer2.2.bn2.bias, backbone.layer2.2.bn3.running_mean, backbone.layer2.2.bn3.running_var, backbone.layer2.2.bn3.weight, backbone.layer2.2.bn3.bias, backbone.layer2.3.bn1.running_mean, backbone.layer2.3.bn1.running_var, backbone.layer2.3.bn1.weight, backbone.layer2.3.bn1.bias, backbone.layer2.3.bn2.running_mean, backbone.layer2.3.bn2.running_var, backbone.layer2.3.bn2.weight, backbone.layer2.3.bn2.bias, backbone.layer2.3.bn3.running_mean, backbone.layer2.3.bn3.running_var, backbone.layer2.3.bn3.weight, backbone.layer2.3.bn3.bias, backbone.layer3.0.bn1.running_mean, backbone.layer3.0.bn1.running_var, backbone.layer3.0.bn1.weight, backbone.layer3.0.bn1.bias, backbone.layer3.0.bn2.running_mean, backbone.layer3.0.bn2.running_var, backbone.layer3.0.bn2.weight, backbone.layer3.0.bn2.bias, backbone.layer3.0.bn3.running_mean, backbone.layer3.0.bn3.running_var, backbone.layer3.0.bn3.weight, backbone.layer3.0.bn3.bias, backbone.layer3.0.downsample.1.running_mean, backbone.layer3.0.downsample.1.running_var, backbone.layer3.1.bn1.running_mean, backbone.layer3.1.bn1.running_var, backbone.layer3.1.bn1.weight, backbone.layer3.1.bn1.bias, backbone.layer3.1.bn2.running_mean, backbone.layer3.1.bn2.running_var, backbone.layer3.1.bn2.weight, backbone.layer3.1.bn2.bias, backbone.layer3.1.bn3.running_mean, backbone.layer3.1.bn3.running_var, backbone.layer3.1.bn3.weight, backbone.layer3.1.bn3.bias, backbone.layer3.2.bn1.running_mean, backbone.layer3.2.bn1.running_var, backbone.layer3.2.bn1.weight, backbone.layer3.2.bn1.bias, backbone.layer3.2.bn2.running_mean, backbone.layer3.2.bn2.running_var, backbone.layer3.2.bn2.weight, backbone.layer3.2.bn2.bias, backbone.layer3.2.bn3.running_mean, backbone.layer3.2.bn3.running_var, backbone.layer3.2.bn3.weight, backbone.layer3.2.bn3.bias, backbone.layer3.3.bn1.running_mean, backbone.layer3.3.bn1.running_var, backbone.layer3.3.bn1.weight, backbone.layer3.3.bn1.bias, backbone.layer3.3.bn2.running_mean, backbone.layer3.3.bn2.running_var, backbone.layer3.3.bn2.weight, backbone.layer3.3.bn2.bias, backbone.layer3.3.bn3.running_mean, backbone.layer3.3.bn3.running_var, backbone.layer3.3.bn3.weight, backbone.layer3.3.bn3.bias, backbone.layer3.4.bn1.running_mean, backbone.layer3.4.bn1.running_var, backbone.layer3.4.bn1.weight, backbone.layer3.4.bn1.bias, backbone.layer3.4.bn2.running_mean, backbone.layer3.4.bn2.running_var, backbone.layer3.4.bn2.weight, backbone.layer3.4.bn2.bias, backbone.layer3.4.bn3.running_mean, backbone.layer3.4.bn3.running_var, backbone.layer3.4.bn3.weight, backbone.layer3.4.bn3.bias, backbone.layer3.5.bn1.running_mean, backbone.layer3.5.bn1.running_var, backbone.layer3.5.bn1.weight, backbone.layer3.5.bn1.bias, backbone.layer3.5.bn2.running_mean, backbone.layer3.5.bn2.running_var, backbone.layer3.5.bn2.weight, backbone.layer3.5.bn2.bias, backbone.layer3.5.bn3.running_mean, backbone.layer3.5.bn3.running_var, backbone.layer3.5.bn3.weight, backbone.layer3.5.bn3.bias, backbone.layer4.0.bn1.running_mean, backbone.layer4.0.bn1.running_var, backbone.layer4.0.bn1.weight, backbone.layer4.0.bn1.bias, backbone.layer4.0.bn2.running_mean, backbone.layer4.0.bn2.running_var, backbone.layer4.0.bn2.weight, backbone.layer4.0.bn2.bias, backbone.layer4.0.bn3.running_mean, backbone.layer4.0.bn3.running_var, backbone.layer4.0.bn3.weight, backbone.layer4.0.bn3.bias, backbone.layer4.0.downsample.1.running_mean, backbone.layer4.0.downsample.1.running_var, backbone.layer4.1.bn1.running_mean, backbone.layer4.1.bn1.running_var, backbone.layer4.1.bn1.weight, backbone.layer4.1.bn1.bias, backbone.layer4.1.bn2.running_mean, backbone.layer4.1.bn2.running_var, backbone.layer4.1.bn2.weight, backbone.layer4.1.bn2.bias, backbone.layer4.1.bn3.running_mean, backbone.layer4.1.bn3.running_var, backbone.layer4.1.bn3.weight, backbone.layer4.1.bn3.bias, backbone.layer4.2.bn1.running_mean, backbone.layer4.2.bn1.running_var, backbone.layer4.2.bn1.weight, backbone.layer4.2.bn1.bias, backbone.layer4.2.bn2.running_mean, backbone.layer4.2.bn2.running_var, backbone.layer4.2.bn2.weight, backbone.layer4.2.bn2.bias, backbone.layer4.2.bn3.running_mean, backbone.layer4.2.bn3.running_var, backbone.layer4.2.bn3.weight, backbone.layer4.2.bn3.bias
missing keys in source state_dict: backbone.gn1.weight, backbone.gn1.bias, backbone.layer1.0.gn1.weight, backbone.layer1.0.gn1.bias, backbone.layer1.0.gn2.weight, backbone.layer1.0.gn2.bias, backbone.layer1.0.gn3.weight, backbone.layer1.0.gn3.bias, backbone.layer1.1.gn1.weight, backbone.layer1.1.gn1.bias, backbone.layer1.1.gn2.weight, backbone.layer1.1.gn2.bias, backbone.layer1.1.gn3.weight, backbone.layer1.1.gn3.bias, backbone.layer1.2.gn1.weight, backbone.layer1.2.gn1.bias, backbone.layer1.2.gn2.weight, backbone.layer1.2.gn2.bias, backbone.layer1.2.gn3.weight, backbone.layer1.2.gn3.bias, backbone.layer2.0.gn1.weight, backbone.layer2.0.gn1.bias, backbone.layer2.0.gn2.weight, backbone.layer2.0.gn2.bias, backbone.layer2.0.gn3.weight, backbone.layer2.0.gn3.bias, backbone.layer2.1.gn1.weight, backbone.layer2.1.gn1.bias, backbone.layer2.1.gn2.weight, backbone.layer2.1.gn2.bias, backbone.layer2.1.gn3.weight, backbone.layer2.1.gn3.bias, backbone.layer2.2.gn1.weight, backbone.layer2.2.gn1.bias, backbone.layer2.2.gn2.weight, backbone.layer2.2.gn2.bias, backbone.layer2.2.gn3.weight, backbone.layer2.2.gn3.bias, backbone.layer2.3.gn1.weight, backbone.layer2.3.gn1.bias, backbone.layer2.3.gn2.weight, backbone.layer2.3.gn2.bias, backbone.layer2.3.gn3.weight, backbone.layer2.3.gn3.bias, backbone.layer3.0.gn1.weight, backbone.layer3.0.gn1.bias, backbone.layer3.0.conv2.conv_offset.weight, backbone.layer3.0.conv2.conv_offset.bias, backbone.layer3.0.gn2.weight, backbone.layer3.0.gn2.bias, backbone.layer3.0.gn3.weight, backbone.layer3.0.gn3.bias, backbone.layer3.1.gn1.weight, backbone.layer3.1.gn1.bias, backbone.layer3.1.conv2.conv_offset.weight, backbone.layer3.1.conv2.conv_offset.bias, backbone.layer3.1.gn2.weight, backbone.layer3.1.gn2.bias, backbone.layer3.1.gn3.weight, backbone.layer3.1.gn3.bias, backbone.layer3.2.gn1.weight, backbone.layer3.2.gn1.bias, backbone.layer3.2.conv2.conv_offset.weight, backbone.layer3.2.conv2.conv_offset.bias, backbone.layer3.2.gn2.weight, backbone.layer3.2.gn2.bias, backbone.layer3.2.gn3.weight, backbone.layer3.2.gn3.bias, backbone.layer3.3.gn1.weight, backbone.layer3.3.gn1.bias, backbone.layer3.3.conv2.conv_offset.weight, backbone.layer3.3.conv2.conv_offset.bias, backbone.layer3.3.gn2.weight, backbone.layer3.3.gn2.bias, backbone.layer3.3.gn3.weight, backbone.layer3.3.gn3.bias, backbone.layer3.4.gn1.weight, backbone.layer3.4.gn1.bias, backbone.layer3.4.conv2.conv_offset.weight, backbone.layer3.4.conv2.conv_offset.bias, backbone.layer3.4.gn2.weight, backbone.layer3.4.gn2.bias, backbone.layer3.4.gn3.weight, backbone.layer3.4.gn3.bias, backbone.layer3.5.gn1.weight, backbone.layer3.5.gn1.bias, backbone.layer3.5.conv2.conv_offset.weight, backbone.layer3.5.conv2.conv_offset.bias, backbone.layer3.5.gn2.weight, backbone.layer3.5.gn2.bias, backbone.layer3.5.gn3.weight, backbone.layer3.5.gn3.bias, backbone.layer4.0.gn1.weight, backbone.layer4.0.gn1.bias, backbone.layer4.0.conv2.conv_offset.weight, backbone.layer4.0.conv2.conv_offset.bias, backbone.layer4.0.gn2.weight, backbone.layer4.0.gn2.bias, backbone.layer4.0.gn3.weight, backbone.layer4.0.gn3.bias, backbone.layer4.1.gn1.weight, backbone.layer4.1.gn1.bias, backbone.layer4.1.conv2.conv_offset.weight, backbone.layer4.1.conv2.conv_offset.bias, backbone.layer4.1.gn2.weight, backbone.layer4.1.gn2.bias, backbone.layer4.1.gn3.weight, backbone.layer4.1.gn3.bias, backbone.layer4.2.gn1.weight, backbone.layer4.2.gn1.bias, backbone.layer4.2.conv2.conv_offset.weight, backbone.layer4.2.conv2.conv_offset.bias, backbone.layer4.2.gn2.weight, backbone.layer4.2.gn2.bias, backbone.layer4.2.gn3.weight, backbone.layer4.2.gn3.bias, neck.0.lateral_convs.0.conv.weight, neck.0.lateral_convs.0.gn.weight, neck.0.lateral_convs.0.gn.bias, neck.0.lateral_convs.1.conv.weight, neck.0.lateral_convs.1.gn.weight, neck.0.lateral_convs.1.gn.bias, neck.0.lateral_convs.2.conv.weight, neck.0.lateral_convs.2.gn.weight, neck.0.lateral_convs.2.gn.bias, neck.0.lateral_convs.3.conv.weight, neck.0.lateral_convs.3.gn.weight, neck.0.lateral_convs.3.gn.bias, neck.0.fpn_convs.0.conv.weight, neck.0.fpn_convs.0.gn.weight, neck.0.fpn_convs.0.gn.bias, neck.0.fpn_convs.1.conv.weight, neck.0.fpn_convs.1.gn.weight, neck.0.fpn_convs.1.gn.bias, neck.0.fpn_convs.2.conv.weight, neck.0.fpn_convs.2.gn.weight, neck.0.fpn_convs.2.gn.bias, neck.0.fpn_convs.3.conv.weight, neck.0.fpn_convs.3.gn.weight, neck.0.fpn_convs.3.gn.bias, neck.0.fpn_convs.4.conv.weight, neck.0.fpn_convs.4.gn.weight, neck.0.fpn_convs.4.gn.bias, neck.0.fpn_convs.5.conv.weight, neck.0.fpn_convs.5.gn.weight, neck.0.fpn_convs.5.gn.bias, neck.1.level_convs.0.0.conv.weight, neck.1.level_convs.0.0.gn.weight, neck.1.level_convs.0.0.gn.bias, neck.1.level_convs.0.1.conv.weight, neck.1.level_convs.0.1.gn.weight, neck.1.level_convs.0.1.gn.bias, neck.1.level_convs.0.2.conv.weight, neck.1.level_convs.0.2.gn.weight, neck.1.level_convs.0.2.gn.bias, neck.1.level_convs.0.3.conv.weight, neck.1.level_convs.0.3.gn.weight, neck.1.level_convs.0.3.gn.bias, neck.1.level_convs.0.4.conv.weight, neck.1.level_convs.0.4.gn.weight, neck.1.level_convs.0.4.gn.bias, bbox_head.cls_convs.0.conv.weight, bbox_head.cls_convs.0.gn.weight, bbox_head.cls_convs.0.gn.bias, bbox_head.cls_convs.1.conv.weight, bbox_head.cls_convs.1.gn.weight, bbox_head.cls_convs.1.gn.bias, bbox_head.cls_convs.2.conv.weight, bbox_head.cls_convs.2.gn.weight, bbox_head.cls_convs.2.gn.bias, bbox_head.cls_convs.3.conv.weight, bbox_head.cls_convs.3.gn.weight, bbox_head.cls_convs.3.gn.bias, bbox_head.reg_convs.0.conv.weight, bbox_head.reg_convs.0.gn.weight, bbox_head.reg_convs.0.gn.bias, bbox_head.reg_convs.1.conv.weight, bbox_head.reg_convs.1.gn.weight, bbox_head.reg_convs.1.gn.bias, bbox_head.reg_convs.2.conv.weight, bbox_head.reg_convs.2.gn.weight, bbox_head.reg_convs.2.gn.bias, bbox_head.reg_convs.3.conv.weight, bbox_head.reg_convs.3.gn.weight, bbox_head.reg_convs.3.gn.bias, bbox_head.retina_cls.weight, bbox_head.retina_cls.bias, bbox_head.retina_reg.weight, bbox_head.retina_reg.bias, bbox_head.retina_iou.weight, bbox_head.retina_iou.bias
卡在这里不动 我的环境配置： addict 2.4.0
albumentations 0.5.2
certifi 2020.12.5
cycler 0.10.0
Cython 0.29.21
decorator 4.4.2
imagecorruptions 1.1.2
imageio 2.9.0
imgaug 0.4.0
kiwisolver 1.3.1
matplotlib 3.3.3
mmpycocotools 12.0.3
networkx 2.5
numpy 1.19.4
opencv-python 4.4.0.46
opencv-python-headless 4.4.0.46
Pillow 8.0.1
pip 20.3.3
pyparsing 2.4.7
python-dateutil 2.8.1
PyWavelets 1.1.1
PyYAML 5.3.1
scikit-image 0.18.0
scipy 1.5.4
setuptools 51.0.0.post20201207
Shapely 1.7.1
six 1.15.0
terminaltables 3.1.0
tifffile 2020.12.8
torch 1.7.1
torchvision 0.8.2
typing-extensions 3.7.4.3
vedadet 0.1.0 /home/user/yjq/vedadet
wheel 0.36.2
yapf 0.30.0 nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130 +-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.57 Driver Version: 450.57 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 TITAN Xp Off | 00000000:02:00.0 Off | N/A |
| 19% 31C P0 61W / 250W | 0MiB / 12196MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 TITAN Xp Off | 00000000:03:00.0 Off | N/A |
| 17% 36C P0 60W / 250W | 0MiB / 12196MiB | 0% Default |
| | | N/A |`
请您帮我看看吧
juliusyang97
commented
3 years ago 您好，我现在还有这个问题
Hi @juliusyang97, In order to speed up the training process, the default setting of logger's interval is 100 that may cause a long wait for printing the info. So you can modify this line 'dict(typename='LoggerHook', interval=100)' of hooks in config, e.g 'dict(typename='LoggerHook', interval=1)'
您好，我现在还是有这个问题 `CUDA_VISIBLE_DEVICES="0" python tools/trainval.py configs/trainval/tinaface/tinaface.py 2020-12-29 18:09:20,558 - vedadet - WARNING - EvalHook is not in modes ['train'] 2020-12-29 18:09:20,559 - vedadet - INFO - Loading weights from torchvision://resnet50 2020-12-29 18:09:20,843 - vedadet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: backbone.bn1.running_mean, backbone.bn1.running_var, backbone.bn1.weight, backbone.bn1.bias, backbone.fc.weight, backbone.fc.bias, backbone.layer1.0.bn1.running_mean, backbone.layer1.0.bn1.running_var, backbone.layer1.0.bn1.weight, backbone.layer1.0.bn1.bias, backbone.layer1.0.bn2.running_mean, backbone.layer1.0.bn2.running_var, backbone.layer1.0.bn2.weight, backbone.layer1.0.bn2.bias, backbone.layer1.0.bn3.running_mean, backbone.layer1.0.bn3.running_var, backbone.layer1.0.bn3.weight, backbone.layer1.0.bn3.bias, backbone.layer1.0.downsample.1.running_mean, backbone.layer1.0.downsample.1.running_var, backbone.layer1.1.bn1.running_mean, backbone.layer1.1.bn1.running_var, backbone.layer1.1.bn1.weight, backbone.layer1.1.bn1.bias, backbone.layer1.1.bn2.running_mean, backbone.layer1.1.bn2.running_var, backbone.layer1.1.bn2.weight, backbone.layer1.1.bn2.bias, backbone.layer1.1.bn3.running_mean, backbone.layer1.1.bn3.running_var, backbone.layer1.1.bn3.weight, backbone.layer1.1.bn3.bias, backbone.layer1.2.bn1.running_mean, backbone.layer1.2.bn1.running_var, backbone.layer1.2.bn1.weight, backbone.layer1.2.bn1.bias, backbone.layer1.2.bn2.running_mean, backbone.layer1.2.bn2.running_var, backbone.layer1.2.bn2.weight, backbone.layer1.2.bn2.bias, backbone.layer1.2.bn3.running_mean, backbone.layer1.2.bn3.running_var, backbone.layer1.2.bn3.weight, backbone.layer1.2.bn3.bias, backbone.layer2.0.bn1.running_mean, backbone.layer2.0.bn1.running_var, backbone.layer2.0.bn1.weight, backbone.layer2.0.bn1.bias, backbone.layer2.0.bn2.running_mean, backbone.layer2.0.bn2.running_var, backbone.layer2.0.bn2.weight, backbone.layer2.0.bn2.bias, backbone.layer2.0.bn3.running_mean, backbone.layer2.0.bn3.running_var, backbone.layer2.0.bn3.weight, backbone.layer2.0.bn3.bias, backbone.layer2.0.downsample.1.running_mean, backbone.layer2.0.downsample.1.running_var, backbone.layer2.1.bn1.running_mean, backbone.layer2.1.bn1.running_var, backbone.layer2.1.bn1.weight, backbone.layer2.1.bn1.bias, backbone.layer2.1.bn2.running_mean, backbone.layer2.1.bn2.running_var, backbone.layer2.1.bn2.weight, backbone.layer2.1.bn2.bias, backbone.layer2.1.bn3.running_mean, backbone.layer2.1.bn3.running_var, backbone.layer2.1.bn3.weight, backbone.layer2.1.bn3.bias, backbone.layer2.2.bn1.running_mean, backbone.layer2.2.bn1.running_var, backbone.layer2.2.bn1.weight, backbone.layer2.2.bn1.bias, backbone.layer2.2.bn2.running_mean, backbone.layer2.2.bn2.running_var, backbone.layer2.2.bn2.weight, backbone.layer2.2.bn2.bias, backbone.layer2.2.bn3.running_mean, backbone.layer2.2.bn3.running_var, backbone.layer2.2.bn3.weight, backbone.layer2.2.bn3.bias, backbone.layer2.3.bn1.running_mean, backbone.layer2.3.bn1.running_var, backbone.layer2.3.bn1.weight, backbone.layer2.3.bn1.bias, backbone.layer2.3.bn2.running_mean, backbone.layer2.3.bn2.running_var, backbone.layer2.3.bn2.weight, backbone.layer2.3.bn2.bias, backbone.layer2.3.bn3.running_mean, backbone.layer2.3.bn3.running_var, backbone.layer2.3.bn3.weight, backbone.layer2.3.bn3.bias, backbone.layer3.0.bn1.running_mean, backbone.layer3.0.bn1.running_var, backbone.layer3.0.bn1.weight, backbone.layer3.0.bn1.bias, backbone.layer3.0.bn2.running_mean, backbone.layer3.0.bn2.running_var, backbone.layer3.0.bn2.weight, backbone.layer3.0.bn2.bias, backbone.layer3.0.bn3.running_mean, backbone.layer3.0.bn3.running_var, backbone.layer3.0.bn3.weight, backbone.layer3.0.bn3.bias, backbone.layer3.0.downsample.1.running_mean, backbone.layer3.0.downsample.1.running_var, backbone.layer3.1.bn1.running_mean, backbone.layer3.1.bn1.running_var, backbone.layer3.1.bn1.weight, backbone.layer3.1.bn1.bias, backbone.layer3.1.bn2.running_mean, backbone.layer3.1.bn2.running_var, backbone.layer3.1.bn2.weight, backbone.layer3.1.bn2.bias, backbone.layer3.1.bn3.running_mean, backbone.layer3.1.bn3.running_var, backbone.layer3.1.bn3.weight, backbone.layer3.1.bn3.bias, backbone.layer3.2.bn1.running_mean, backbone.layer3.2.bn1.running_var, backbone.layer3.2.bn1.weight, backbone.layer3.2.bn1.bias, backbone.layer3.2.bn2.running_mean, backbone.layer3.2.bn2.running_var, backbone.layer3.2.bn2.weight, backbone.layer3.2.bn2.bias, backbone.layer3.2.bn3.running_mean, backbone.layer3.2.bn3.running_var, backbone.layer3.2.bn3.weight, backbone.layer3.2.bn3.bias, backbone.layer3.3.bn1.running_mean, backbone.layer3.3.bn1.running_var, backbone.layer3.3.bn1.weight, backbone.layer3.3.bn1.bias, backbone.layer3.3.bn2.running_mean, backbone.layer3.3.bn2.running_var, backbone.layer3.3.bn2.weight, backbone.layer3.3.bn2.bias, backbone.layer3.3.bn3.running_mean, backbone.layer3.3.bn3.running_var, backbone.layer3.3.bn3.weight, backbone.layer3.3.bn3.bias, backbone.layer3.4.bn1.running_mean, backbone.layer3.4.bn1.running_var, backbone.layer3.4.bn1.weight, backbone.layer3.4.bn1.bias, backbone.layer3.4.bn2.running_mean, backbone.layer3.4.bn2.running_var, backbone.layer3.4.bn2.weight, backbone.layer3.4.bn2.bias, backbone.layer3.4.bn3.running_mean, backbone.layer3.4.bn3.running_var, backbone.layer3.4.bn3.weight, backbone.layer3.4.bn3.bias, backbone.layer3.5.bn1.running_mean, backbone.layer3.5.bn1.running_var, backbone.layer3.5.bn1.weight, backbone.layer3.5.bn1.bias, backbone.layer3.5.bn2.running_mean, backbone.layer3.5.bn2.running_var, backbone.layer3.5.bn2.weight, backbone.layer3.5.bn2.bias, backbone.layer3.5.bn3.running_mean, backbone.layer3.5.bn3.running_var, backbone.layer3.5.bn3.weight, backbone.layer3.5.bn3.bias, backbone.layer4.0.bn1.running_mean, backbone.layer4.0.bn1.running_var, backbone.layer4.0.bn1.weight, backbone.layer4.0.bn1.bias, backbone.layer4.0.bn2.running_mean, backbone.layer4.0.bn2.running_var, backbone.layer4.0.bn2.weight, backbone.layer4.0.bn2.bias, backbone.layer4.0.bn3.running_mean, backbone.layer4.0.bn3.running_var, backbone.layer4.0.bn3.weight, backbone.layer4.0.bn3.bias, backbone.layer4.0.downsample.1.running_mean, backbone.layer4.0.downsample.1.running_var, backbone.layer4.1.bn1.running_mean, backbone.layer4.1.bn1.running_var, backbone.layer4.1.bn1.weight, backbone.layer4.1.bn1.bias, backbone.layer4.1.bn2.running_mean, backbone.layer4.1.bn2.running_var, backbone.layer4.1.bn2.weight, backbone.layer4.1.bn2.bias, backbone.layer4.1.bn3.running_mean, backbone.layer4.1.bn3.running_var, backbone.layer4.1.bn3.weight, backbone.layer4.1.bn3.bias, backbone.layer4.2.bn1.running_mean, backbone.layer4.2.bn1.running_var, backbone.layer4.2.bn1.weight, backbone.layer4.2.bn1.bias, backbone.layer4.2.bn2.running_mean, backbone.layer4.2.bn2.running_var, backbone.layer4.2.bn2.weight, backbone.layer4.2.bn2.bias, backbone.layer4.2.bn3.running_mean, backbone.layer4.2.bn3.running_var, backbone.layer4.2.bn3.weight, backbone.layer4.2.bn3.bias
missing keys in source state_dict: backbone.gn1.weight, backbone.gn1.bias, backbone.layer1.0.gn1.weight, backbone.layer1.0.gn1.bias, backbone.layer1.0.gn2.weight, backbone.layer1.0.gn2.bias, backbone.layer1.0.gn3.weight, backbone.layer1.0.gn3.bias, backbone.layer1.1.gn1.weight, backbone.layer1.1.gn1.bias, backbone.layer1.1.gn2.weight, backbone.layer1.1.gn2.bias, backbone.layer1.1.gn3.weight, backbone.layer1.1.gn3.bias, backbone.layer1.2.gn1.weight, backbone.layer1.2.gn1.bias, backbone.layer1.2.gn2.weight, backbone.layer1.2.gn2.bias, backbone.layer1.2.gn3.weight, backbone.layer1.2.gn3.bias, backbone.layer2.0.gn1.weight, backbone.layer2.0.gn1.bias, backbone.layer2.0.gn2.weight, backbone.layer2.0.gn2.bias, backbone.layer2.0.gn3.weight, backbone.layer2.0.gn3.bias, backbone.layer2.1.gn1.weight, backbone.layer2.1.gn1.bias, backbone.layer2.1.gn2.weight, backbone.layer2.1.gn2.bias, backbone.layer2.1.gn3.weight, backbone.layer2.1.gn3.bias, backbone.layer2.2.gn1.weight, backbone.layer2.2.gn1.bias, backbone.layer2.2.gn2.weight, backbone.layer2.2.gn2.bias, backbone.layer2.2.gn3.weight, backbone.layer2.2.gn3.bias, backbone.layer2.3.gn1.weight, backbone.layer2.3.gn1.bias, backbone.layer2.3.gn2.weight, backbone.layer2.3.gn2.bias, backbone.layer2.3.gn3.weight, backbone.layer2.3.gn3.bias, backbone.layer3.0.gn1.weight, backbone.layer3.0.gn1.bias, backbone.layer3.0.conv2.conv_offset.weight, backbone.layer3.0.conv2.conv_offset.bias, backbone.layer3.0.gn2.weight, backbone.layer3.0.gn2.bias, backbone.layer3.0.gn3.weight, backbone.layer3.0.gn3.bias, backbone.layer3.1.gn1.weight, backbone.layer3.1.gn1.bias, backbone.layer3.1.conv2.conv_offset.weight, backbone.layer3.1.conv2.conv_offset.bias, backbone.layer3.1.gn2.weight, backbone.layer3.1.gn2.bias, backbone.layer3.1.gn3.weight, backbone.layer3.1.gn3.bias, backbone.layer3.2.gn1.weight, backbone.layer3.2.gn1.bias, backbone.layer3.2.conv2.conv_offset.weight, backbone.layer3.2.conv2.conv_offset.bias, backbone.layer3.2.gn2.weight, backbone.layer3.2.gn2.bias, backbone.layer3.2.gn3.weight, backbone.layer3.2.gn3.bias, backbone.layer3.3.gn1.weight, backbone.layer3.3.gn1.bias, backbone.layer3.3.conv2.conv_offset.weight, backbone.layer3.3.conv2.conv_offset.bias, backbone.layer3.3.gn2.weight, backbone.layer3.3.gn2.bias, backbone.layer3.3.gn3.weight, backbone.layer3.3.gn3.bias, backbone.layer3.4.gn1.weight, backbone.layer3.4.gn1.bias, backbone.layer3.4.conv2.conv_offset.weight, backbone.layer3.4.conv2.conv_offset.bias, backbone.layer3.4.gn2.weight, backbone.layer3.4.gn2.bias, backbone.layer3.4.gn3.weight, backbone.layer3.4.gn3.bias, backbone.layer3.5.gn1.weight, backbone.layer3.5.gn1.bias, backbone.layer3.5.conv2.conv_offset.weight, backbone.layer3.5.conv2.conv_offset.bias, backbone.layer3.5.gn2.weight, backbone.layer3.5.gn2.bias, backbone.layer3.5.gn3.weight, backbone.layer3.5.gn3.bias, backbone.layer4.0.gn1.weight, backbone.layer4.0.gn1.bias, backbone.layer4.0.conv2.conv_offset.weight, backbone.layer4.0.conv2.conv_offset.bias, backbone.layer4.0.gn2.weight, backbone.layer4.0.gn2.bias, backbone.layer4.0.gn3.weight, backbone.layer4.0.gn3.bias, backbone.layer4.1.gn1.weight, backbone.layer4.1.gn1.bias, backbone.layer4.1.conv2.conv_offset.weight, backbone.layer4.1.conv2.conv_offset.bias, backbone.layer4.1.gn2.weight, backbone.layer4.1.gn2.bias, backbone.layer4.1.gn3.weight, backbone.layer4.1.gn3.bias, backbone.layer4.2.gn1.weight, backbone.layer4.2.gn1.bias, backbone.layer4.2.conv2.conv_offset.weight, backbone.layer4.2.conv2.conv_offset.bias, backbone.layer4.2.gn2.weight, backbone.layer4.2.gn2.bias, backbone.layer4.2.gn3.weight, backbone.layer4.2.gn3.bias, neck.0.lateral_convs.0.conv.weight, neck.0.lateral_convs.0.gn.weight, neck.0.lateral_convs.0.gn.bias, neck.0.lateral_convs.1.conv.weight, neck.0.lateral_convs.1.gn.weight, neck.0.lateral_convs.1.gn.bias, neck.0.lateral_convs.2.conv.weight, neck.0.lateral_convs.2.gn.weight, neck.0.lateral_convs.2.gn.bias, neck.0.lateral_convs.3.conv.weight, neck.0.lateral_convs.3.gn.weight, neck.0.lateral_convs.3.gn.bias, neck.0.fpn_convs.0.conv.weight, neck.0.fpn_convs.0.gn.weight, neck.0.fpn_convs.0.gn.bias, neck.0.fpn_convs.1.conv.weight, neck.0.fpn_convs.1.gn.weight, neck.0.fpn_convs.1.gn.bias, neck.0.fpn_convs.2.conv.weight, neck.0.fpn_convs.2.gn.weight, neck.0.fpn_convs.2.gn.bias, neck.0.fpn_convs.3.conv.weight, neck.0.fpn_convs.3.gn.weight, neck.0.fpn_convs.3.gn.bias, neck.0.fpn_convs.4.conv.weight, neck.0.fpn_convs.4.gn.weight, neck.0.fpn_convs.4.gn.bias, neck.0.fpn_convs.5.conv.weight, neck.0.fpn_convs.5.gn.weight, neck.0.fpn_convs.5.gn.bias, neck.1.level_convs.0.0.conv.weight, neck.1.level_convs.0.0.gn.weight, neck.1.level_convs.0.0.gn.bias, neck.1.level_convs.0.1.conv.weight, neck.1.level_convs.0.1.gn.weight, neck.1.level_convs.0.1.gn.bias, neck.1.level_convs.0.2.conv.weight, neck.1.level_convs.0.2.gn.weight, neck.1.level_convs.0.2.gn.bias, neck.1.level_convs.0.3.conv.weight, neck.1.level_convs.0.3.gn.weight, neck.1.level_convs.0.3.gn.bias, neck.1.level_convs.0.4.conv.weight, neck.1.level_convs.0.4.gn.weight, neck.1.level_convs.0.4.gn.bias, bbox_head.cls_convs.0.conv.weight, bbox_head.cls_convs.0.gn.weight, bbox_head.cls_convs.0.gn.bias, bbox_head.cls_convs.1.conv.weight, bbox_head.cls_convs.1.gn.weight, bbox_head.cls_convs.1.gn.bias, bbox_head.cls_convs.2.conv.weight, bbox_head.cls_convs.2.gn.weight, bbox_head.cls_convs.2.gn.bias, bbox_head.cls_convs.3.conv.weight, bbox_head.cls_convs.3.gn.weight, bbox_head.cls_convs.3.gn.bias, bbox_head.reg_convs.0.conv.weight, bbox_head.reg_convs.0.gn.weight, bbox_head.reg_convs.0.gn.bias, bbox_head.reg_convs.1.conv.weight, bbox_head.reg_convs.1.gn.weight, bbox_head.reg_convs.1.gn.bias, bbox_head.reg_convs.2.conv.weight, bbox_head.reg_convs.2.gn.weight, bbox_head.reg_convs.2.gn.bias, bbox_head.reg_convs.3.conv.weight, bbox_head.reg_convs.3.gn.weight, bbox_head.reg_convs.3.gn.bias, bbox_head.retina_cls.weight, bbox_head.retina_cls.bias, bbox_head.retina_reg.weight, bbox_head.retina_reg.bias, bbox_head.retina_iou.weight, bbox_head.retina_iou.bias
卡在这里不动 我的环境配置：addict 2.4.0 albumentations 0.5.2 certifi 2020.12.5 cycler 0.10.0 Cython 0.29.21 decorator 4.4.2 imagecorruptions 1.1.2 imageio 2.9.0 imgaug 0.4.0 kiwisolver 1.3.1 matplotlib 3.3.3 mmpycocotools 12.0.3 networkx 2.5 numpy 1.19.4 opencv-python 4.4.0.46 opencv-python-headless 4.4.0.46 Pillow 8.0.1 pip 20.3.3 pyparsing 2.4.7 python-dateutil 2.8.1 PyWavelets 1.1.1 PyYAML 5.3.1 scikit-image 0.18.0 scipy 1.5.4 setuptools 51.0.0.post20201207 Shapely 1.7.1 six 1.15.0 terminaltables 3.1.0 tifffile 2020.12.8 torch 1.7.1 torchvision 0.8.2 typing-extensions 3.7.4.3 vedadet 0.1.0 /home/user/yjq/vedadet wheel 0.36.2 yapf 0.30.0`nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2018 NVIDIA Corporation Built on Sat_Aug_25_21:08:01_CDT_2018 Cuda compilation tools, release 10.0, V10.0.130+-----------------------------------------------------------------------------+ | NVIDIA-SMI 450.57 Driver Version: 450.57 CUDA Version: 11.0 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 TITAN Xp Off | 00000000:02:00.0 Off | N/A | | 19% 31C P0 61W / 250W | 0MiB / 12196MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ | 1 TITAN Xp Off | 00000000:03:00.0 Off | N/A | | 17% 36C P0 60W / 250W | 0MiB / 12196MiB | 0% Default | | | | N/A |请您帮我看看吧
`# packages in environment at /home/user/miniconda3/envs/vedadet: #
_libgcc_mutex 0.1 main https://mirrors.ustc.edu.cn/anaconda/pkgs/main
addict 2.4.0 pypi_0 pypi
albumentations 0.5.2 pypi_0 pypi
ca-certificates 2020.12.8 h06a4308_0 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
certifi 2020.12.5 py37h06a4308_0 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
cycler 0.10.0 pypi_0 pypi
cython 0.29.21 pypi_0 pypi
decorator 4.4.2 pypi_0 pypi
imagecorruptions 1.1.2 pypi_0 pypi
imageio 2.9.0 pypi_0 pypi
imgaug 0.4.0 pypi_0 pypi
kiwisolver 1.3.1 pypi_0 pypi
ld_impl_linux-64 2.33.1 h53a641e_7 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
libedit 3.1.20191231 h14c3975_1 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
libffi 3.3 he6710b0_2 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
libgcc-ng 9.1.0 hdf63c60_0 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
libstdcxx-ng 9.1.0 hdf63c60_0 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
matplotlib 3.3.3 pypi_0 pypi
mmpycocotools 12.0.3 pypi_0 pypi
ncurses 6.2 he6710b0_1 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
networkx 2.5 pypi_0 pypi
numpy 1.19.4 pypi_0 pypi
opencv-python 4.4.0.46 pypi_0 pypi
opencv-python-headless 4.4.0.46 pypi_0 pypi
openssl 1.1.1i h27cfd23_0 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
pillow 8.0.1 pypi_0 pypi
pip 20.3.3 py37h06a4308_0 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
pyparsing 2.4.7 pypi_0 pypi
python 3.7.9 h7579374_0 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
python-dateutil 2.8.1 pypi_0 pypi
pywavelets 1.1.1 pypi_0 pypi
pyyaml 5.3.1 pypi_0 pypi
readline 8.0 h7b6447c_0 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
scikit-image 0.18.0 pypi_0 pypi
scipy 1.5.4 pypi_0 pypi
setuptools 51.0.0 py37h06a4308_2 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
shapely 1.7.1 pypi_0 pypi
six 1.15.0 pypi_0 pypi
sqlite 3.33.0 h62c20be_0 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
terminaltables 3.1.0 pypi_0 pypi
tifffile 2020.12.8 pypi_0 pypi
tk 8.6.10 hbc83047_0 https://mirrors.ustc.edu.cn/anaconda/pkgs/main
torch 1.7.1 pypi_0 pypi
torchvision 0.8.2 pypi_0 pypi
typing-extensions 3.7.4.3 pypi_0 pypi
vedadet 0.1.0 dev_0
mike112223
commented
3 years ago Did you use your own dataset?
juliusyang97
commented
3 years ago Did you use your own dataset?
yes, I used my own dataset
juliusyang97
commented
3 years ago Did you use your own dataset?
yes, I used my own dataset
请问这是和我数据集的格式或者数据集相关的其他的东西有关系吗，您这么一说我好像意识到我对数据集的格式没怎么仔细检查过
mike112223
commented
3 years ago please check #20
juliusyang97
commented
3 years ago 请问您是如何使他成功的呢，我为什么一直在那里不动，您等待了多长时间
杨军奇 yangjunqi1997@foxmail.com
------------------ 原始邮件 ------------------ 发件人: "Pomelo"<notifications@github.com>; 发送时间: 2021年1月20日(星期三) 中午1:32 收件人: "Media-Smart/vedadet"<vedadet@noreply.github.com>; 抄送: "杨军奇"<2107536844@qq.com>; "Mention"<mention@noreply.github.com>; 主题: Re: [Media-Smart/vedadet] The model and loaded state dict do not match exactly (#21)
I have encountered the identical issue when trying to train tinaface, but at the end it seems to be working:
2021-01-20 13:22:11,689 - vedadet - WARNING - EvalHook is not in modes ['train'] 2021-01-20 13:22:11,689 - vedadet - INFO - Loading weights from torchvision://resnet50 2021-01-20 13:22:11,811 - vedadet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: backbone.bn1.running_mean, backbone.bn1.running_var, backbone.bn1.weight, backbone.bn1.bias, backbone.fc.weight, backbone.fc.bias, backbone.layer1.0.bn1.running_mean, backbone.layer1.0.bn1.running_var, backbone.layer1.0.bn1.weight, backbone.layer1.0.bn1.bias, backbone.layer1.0.bn2.running_mean, backbone.layer1.0.bn2.running_var, backbone.layer1.0.bn2.weight, backbone.layer1.0.bn2.bias, backbone.layer1.0.bn3.running_mean, backbone.layer1.0.bn3.running_var, backbone.layer1.0.bn3.weight, backbone.layer1.0.bn3.bias, backbone.layer1.0.downsample.1.running_mean, backbone.layer1.0.downsample.1.running_var, backbone.layer1.1.bn1.running_mean, backbone.layer1.1.bn1.running_var, backbone.layer1.1.bn1.weight, backbone.layer1.1.bn1.bias, backbone.layer1.1.bn2.running_mean, backbone.layer1.1.bn2.running_var, backbone.layer1.1.bn2.weight, backbone.layer1.1.bn2.bias, backbone.layer1.1.bn3.running_mean, backbone.layer1.1.bn3.running_var, backbone.layer1.1.bn3.weight, backbone.layer1.1.bn3.bias, backbone.layer1.2.bn1.running_mean, backbone.layer1.2.bn1.running_var, backbone.layer1.2.bn1.weight, backbone.layer1.2.bn1.bias, backbone.layer1.2.bn2.running_mean, backbone.layer1.2.bn2.running_var, backbone.layer1.2.bn2.weight, backbone.layer1.2.bn2.bias, backbone.layer1.2.bn3.running_mean, backbone.layer1.2.bn3.running_var, backbone.layer1.2.bn3.weight, backbone.layer1.2.bn3.bias, backbone.layer2.0.bn1.running_mean, backbone.layer2.0.bn1.running_var, backbone.layer2.0.bn1.weight, backbone.layer2.0.bn1.bias, backbone.layer2.0.bn2.running_mean, backbone.layer2.0.bn2.running_var, backbone.layer2.0.bn2.weight, backbone.layer2.0.bn2.bias, backbone.layer2.0.bn3.running_mean, backbone.layer2.0.bn3.running_var, backbone.layer2.0.bn3.weight, backbone.layer2.0.bn3.bias, backbone.layer2.0.downsample.1.running_mean, backbone.layer2.0.downsample.1.running_var, backbone.layer2.1.bn1.running_mean, backbone.layer2.1.bn1.running_var, backbone.layer2.1.bn1.weight, backbone.layer2.1.bn1.bias, backbone.layer2.1.bn2.running_mean, backbone.layer2.1.bn2.running_var, backbone.layer2.1.bn2.weight, backbone.layer2.1.bn2.bias, backbone.layer2.1.bn3.running_mean, backbone.layer2.1.bn3.running_var, backbone.layer2.1.bn3.weight, backbone.layer2.1.bn3.bias, backbone.layer2.2.bn1.running_mean, backbone.layer2.2.bn1.running_var, backbone.layer2.2.bn1.weight, backbone.layer2.2.bn1.bias, backbone.layer2.2.bn2.running_mean, backbone.layer2.2.bn2.running_var, backbone.layer2.2.bn2.weight, backbone.layer2.2.bn2.bias, backbone.layer2.2.bn3.running_mean, backbone.layer2.2.bn3.running_var, backbone.layer2.2.bn3.weight, backbone.layer2.2.bn3.bias, backbone.layer2.3.bn1.running_mean, backbone.layer2.3.bn1.running_var, backbone.layer2.3.bn1.weight, backbone.layer2.3.bn1.bias, backbone.layer2.3.bn2.running_mean, backbone.layer2.3.bn2.running_var, backbone.layer2.3.bn2.weight, backbone.layer2.3.bn2.bias, backbone.layer2.3.bn3.running_mean, backbone.layer2.3.bn3.running_var, backbone.layer2.3.bn3.weight, backbone.layer2.3.bn3.bias, backbone.layer3.0.bn1.running_mean, backbone.layer3.0.bn1.running_var, backbone.layer3.0.bn1.weight, backbone.layer3.0.bn1.bias, backbone.layer3.0.bn2.running_mean, backbone.layer3.0.bn2.running_var, backbone.layer3.0.bn2.weight, backbone.layer3.0.bn2.bias, backbone.layer3.0.bn3.running_mean, backbone.layer3.0.bn3.running_var, backbone.layer3.0.bn3.weight, backbone.layer3.0.bn3.bias, backbone.layer3.0.downsample.1.running_mean, backbone.layer3.0.downsample.1.running_var, backbone.layer3.1.bn1.running_mean, backbone.layer3.1.bn1.running_var, backbone.layer3.1.bn1.weight, backbone.layer3.1.bn1.bias, backbone.layer3.1.bn2.running_mean, backbone.layer3.1.bn2.running_var, backbone.layer3.1.bn2.weight, backbone.layer3.1.bn2.bias, backbone.layer3.1.bn3.running_mean, backbone.layer3.1.bn3.running_var, backbone.layer3.1.bn3.weight, backbone.layer3.1.bn3.bias, backbone.layer3.2.bn1.running_mean, backbone.layer3.2.bn1.running_var, backbone.layer3.2.bn1.weight, backbone.layer3.2.bn1.bias, backbone.layer3.2.bn2.running_mean, backbone.layer3.2.bn2.running_var, backbone.layer3.2.bn2.weight, backbone.layer3.2.bn2.bias, backbone.layer3.2.bn3.running_mean, backbone.layer3.2.bn3.running_var, backbone.layer3.2.bn3.weight, backbone.layer3.2.bn3.bias, backbone.layer3.3.bn1.running_mean, backbone.layer3.3.bn1.running_var, backbone.layer3.3.bn1.weight, backbone.layer3.3.bn1.bias, backbone.layer3.3.bn2.running_mean, backbone.layer3.3.bn2.running_var, backbone.layer3.3.bn2.weight, backbone.layer3.3.bn2.bias, backbone.layer3.3.bn3.running_mean, backbone.layer3.3.bn3.running_var, backbone.layer3.3.bn3.weight, backbone.layer3.3.bn3.bias, backbone.layer3.4.bn1.running_mean, backbone.layer3.4.bn1.running_var, backbone.layer3.4.bn1.weight, backbone.layer3.4.bn1.bias, backbone.layer3.4.bn2.running_mean, backbone.layer3.4.bn2.running_var, backbone.layer3.4.bn2.weight, backbone.layer3.4.bn2.bias, backbone.layer3.4.bn3.running_mean, backbone.layer3.4.bn3.running_var, backbone.layer3.4.bn3.weight, backbone.layer3.4.bn3.bias, backbone.layer3.5.bn1.running_mean, backbone.layer3.5.bn1.running_var, backbone.layer3.5.bn1.weight, backbone.layer3.5.bn1.bias, backbone.layer3.5.bn2.running_mean, backbone.layer3.5.bn2.running_var, backbone.layer3.5.bn2.weight, backbone.layer3.5.bn2.bias, backbone.layer3.5.bn3.running_mean, backbone.layer3.5.bn3.running_var, backbone.layer3.5.bn3.weight, backbone.layer3.5.bn3.bias, backbone.layer4.0.bn1.running_mean, backbone.layer4.0.bn1.running_var, backbone.layer4.0.bn1.weight, backbone.layer4.0.bn1.bias, backbone.layer4.0.bn2.running_mean, backbone.layer4.0.bn2.running_var, backbone.layer4.0.bn2.weight, backbone.layer4.0.bn2.bias, backbone.layer4.0.bn3.running_mean, backbone.layer4.0.bn3.running_var, backbone.layer4.0.bn3.weight, backbone.layer4.0.bn3.bias, backbone.layer4.0.downsample.1.running_mean, backbone.layer4.0.downsample.1.running_var, backbone.layer4.1.bn1.running_mean, backbone.layer4.1.bn1.running_var, backbone.layer4.1.bn1.weight, backbone.layer4.1.bn1.bias, backbone.layer4.1.bn2.running_mean, backbone.layer4.1.bn2.running_var, backbone.layer4.1.bn2.weight, backbone.layer4.1.bn2.bias, backbone.layer4.1.bn3.running_mean, backbone.layer4.1.bn3.running_var, backbone.layer4.1.bn3.weight, backbone.layer4.1.bn3.bias, backbone.layer4.2.bn1.running_mean, backbone.layer4.2.bn1.running_var, backbone.layer4.2.bn1.weight, backbone.layer4.2.bn1.bias, backbone.layer4.2.bn2.running_mean, backbone.layer4.2.bn2.running_var, backbone.layer4.2.bn2.weight, backbone.layer4.2.bn2.bias, backbone.layer4.2.bn3.running_mean, backbone.layer4.2.bn3.running_var, backbone.layer4.2.bn3.weight, backbone.layer4.2.bn3.bias
missing keys in source state_dict: backbone.gn1.weight, backbone.gn1.bias, backbone.layer1.0.gn1.weight, backbone.layer1.0.gn1.bias, backbone.layer1.0.gn2.weight, backbone.layer1.0.gn2.bias, backbone.layer1.0.gn3.weight, backbone.layer1.0.gn3.bias, backbone.layer1.1.gn1.weight, backbone.layer1.1.gn1.bias, backbone.layer1.1.gn2.weight, backbone.layer1.1.gn2.bias, backbone.layer1.1.gn3.weight, backbone.layer1.1.gn3.bias, backbone.layer1.2.gn1.weight, backbone.layer1.2.gn1.bias, backbone.layer1.2.gn2.weight, backbone.layer1.2.gn2.bias, backbone.layer1.2.gn3.weight, backbone.layer1.2.gn3.bias, backbone.layer2.0.gn1.weight, backbone.layer2.0.gn1.bias, backbone.layer2.0.gn2.weight, backbone.layer2.0.gn2.bias, backbone.layer2.0.gn3.weight, backbone.layer2.0.gn3.bias, backbone.layer2.1.gn1.weight, backbone.layer2.1.gn1.bias, backbone.layer2.1.gn2.weight, backbone.layer2.1.gn2.bias, backbone.layer2.1.gn3.weight, backbone.layer2.1.gn3.bias, backbone.layer2.2.gn1.weight, 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backbone.layer4.0.conv2.conv_offset.bias, backbone.layer4.0.gn2.weight, backbone.layer4.0.gn2.bias, backbone.layer4.0.gn3.weight, backbone.layer4.0.gn3.bias, backbone.layer4.1.gn1.weight, backbone.layer4.1.gn1.bias, backbone.layer4.1.conv2.conv_offset.weight, backbone.layer4.1.conv2.conv_offset.bias, backbone.layer4.1.gn2.weight, backbone.layer4.1.gn2.bias, backbone.layer4.1.gn3.weight, backbone.layer4.1.gn3.bias, backbone.layer4.2.gn1.weight, backbone.layer4.2.gn1.bias, backbone.layer4.2.conv2.conv_offset.weight, backbone.layer4.2.conv2.conv_offset.bias, backbone.layer4.2.gn2.weight, backbone.layer4.2.gn2.bias, backbone.layer4.2.gn3.weight, backbone.layer4.2.gn3.bias, neck.0.lateral_convs.0.conv.weight, neck.0.lateral_convs.0.gn.weight, neck.0.lateral_convs.0.gn.bias, neck.0.lateral_convs.1.conv.weight, neck.0.lateral_convs.1.gn.weight, neck.0.lateral_convs.1.gn.bias, neck.0.lateral_convs.2.conv.weight, neck.0.lateral_convs.2.gn.weight, neck.0.lateral_convs.2.gn.bias, neck.0.lateral_convs.3.conv.weight, neck.0.lateral_convs.3.gn.weight, neck.0.lateral_convs.3.gn.bias, neck.0.fpn_convs.0.conv.weight, neck.0.fpn_convs.0.gn.weight, neck.0.fpn_convs.0.gn.bias, neck.0.fpn_convs.1.conv.weight, neck.0.fpn_convs.1.gn.weight, neck.0.fpn_convs.1.gn.bias, neck.0.fpn_convs.2.conv.weight, neck.0.fpn_convs.2.gn.weight, neck.0.fpn_convs.2.gn.bias, neck.0.fpn_convs.3.conv.weight, neck.0.fpn_convs.3.gn.weight, neck.0.fpn_convs.3.gn.bias, neck.0.fpn_convs.4.conv.weight, neck.0.fpn_convs.4.gn.weight, neck.0.fpn_convs.4.gn.bias, neck.0.fpn_convs.5.conv.weight, neck.0.fpn_convs.5.gn.weight, neck.0.fpn_convs.5.gn.bias, neck.1.level_convs.0.0.conv.weight, neck.1.level_convs.0.0.gn.weight, neck.1.level_convs.0.0.gn.bias, neck.1.level_convs.0.1.conv.weight, neck.1.level_convs.0.1.gn.weight, neck.1.level_convs.0.1.gn.bias, neck.1.level_convs.0.2.conv.weight, neck.1.level_convs.0.2.gn.weight, neck.1.level_convs.0.2.gn.bias, neck.1.level_convs.0.3.conv.weight, neck.1.level_convs.0.3.gn.weight, neck.1.level_convs.0.3.gn.bias, neck.1.level_convs.0.4.conv.weight, neck.1.level_convs.0.4.gn.weight, neck.1.level_convs.0.4.gn.bias, bbox_head.cls_convs.0.conv.weight, bbox_head.cls_convs.0.gn.weight, bbox_head.cls_convs.0.gn.bias, bbox_head.cls_convs.1.conv.weight, bbox_head.cls_convs.1.gn.weight, bbox_head.cls_convs.1.gn.bias, bbox_head.cls_convs.2.conv.weight, bbox_head.cls_convs.2.gn.weight, bbox_head.cls_convs.2.gn.bias, bbox_head.cls_convs.3.conv.weight, bbox_head.cls_convs.3.gn.weight, bbox_head.cls_convs.3.gn.bias, bbox_head.reg_convs.0.conv.weight, bbox_head.reg_convs.0.gn.weight, bbox_head.reg_convs.0.gn.bias, bbox_head.reg_convs.1.conv.weight, bbox_head.reg_convs.1.gn.weight, bbox_head.reg_convs.1.gn.bias, bbox_head.reg_convs.2.conv.weight, bbox_head.reg_convs.2.gn.weight, bbox_head.reg_convs.2.gn.bias, bbox_head.reg_convs.3.conv.weight, bbox_head.reg_convs.3.gn.weight, bbox_head.reg_convs.3.gn.bias, bbox_head.retina_cls.weight, bbox_head.retina_cls.bias, bbox_head.retina_reg.weight, bbox_head.retina_reg.bias, bbox_head.retina_iou.weight, bbox_head.retina_iou.bias
/home/zhuang/miniconda3/envs/vedadet/lib/python3.6/site-packages/torch/nn/functional.py:3121: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. "See the documentation of nn.Upsample for details.".format(mode)) /home/zhuang/scripts/code for facetracking/vedadet/vedadet/criteria/iou_bbox_anchor_criterion.py:329: UserWarning: This overload of nonzero is deprecated: nonzero() Consider using one of the following signatures instead: nonzero(*, bool as_tuple) (Triggered internally at /pytorch/torch/csrc/utils/python_arg_parser.cpp:766.) iou_weights[(bbox_weights.sum(axis=1) > 0).nonzero()] = 1. 2021-01-20 13:22:50,511 - vedadet - INFO - Saved weights, optimizer, meta at epoch 1, iter 70 as ./workdir/tinaface/epoch_1 2021-01-20 13:23:29,618 - vedadet - INFO - Saved weights, optimizer, meta at epoch 2, iter 140 as ./workdir/tinaface/epoch_2 2021-01-20 13:24:08,643 - vedadet - INFO - Saved weights, optimizer, meta at epoch 3, iter 210 as ./workdir/tinaface/epoch_3 2021-01-20 13:24:48,695 - vedadet - INFO - Saved weights, optimizer, meta at epoch 4, iter 280 as ./workdir/tinaface/epoch_4 2021-01-20 13:25:29,062 - vedadet - INFO - Saved weights, optimizer, meta at epoch 5, iter 350 as ./workdir/tinaface/epoch_5 2021-01-20 13:26:09,527 - vedadet - INFO - Saved weights, optimizer, meta at epoch 6, iter 420 as ./workdir/tinaface/epoch_6 2021-01-20 13:26:50,262 - vedadet - INFO - Saved weights, optimizer, meta at epoch 7, iter 490 as ./workdir/tinaface/epoch_7
However, is this normal? it seems that the programe is saving weights at each epoch, but it should not be this quick..
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ZHUANGHP
commented
3 years ago change tinaface.py of dict(typename='LoggerHook', interval=100) to dict(typename='LoggerHook', interval=1), and it should show the training infomation.
juliusyang97
commented
3 years ago change tinaface.py of dict(typename='LoggerHook', interval=100) to dict(typename='LoggerHook', interval=1), and it should show the training infomation.
这很是让人头大，这个方法在我这里却不起作用
juliusyang97
commented
3 years ago change tinaface.py of dict(typename='LoggerHook', interval=100) to dict(typename='LoggerHook', interval=1), and it should show the training infomation.
您好，请问您是否愿意我们添加为好友，我的QQ：2107536844
你好，请问运行
CUDA_VISIBLE_DEVICES="0" python tools/trainval.py configs/trainval/retinanet/retinanet.py时出现以下信息之后就一直不动了，是什么原因，找了半天没找出原因` loading annotations into memory... Done (t=0.02s) creating index... index created! loading annotations into memory... Done (t=0.00s) creating index... index created! 2020-12-19 19:12:36,718 - vedadet - INFO - Loading weights from torchvision://resnet50 2020-12-19 19:12:36,919 - vedadet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: backbone.fc.weight, backbone.fc.bias
missing keys in source state_dict: neck.lateral_convs.0.conv.weight, neck.lateral_convs.0.conv.bias, neck.lateral_convs.1.conv.weight, neck.lateral_convs.1.conv.bias, neck.lateral_convs.2.conv.weight, neck.lateral_convs.2.conv.bias, neck.fpn_convs.0.conv.weight, neck.fpn_convs.0.conv.bias, neck.fpn_convs.1.conv.weight, neck.fpn_convs.1.conv.bias, neck.fpn_convs.2.conv.weight, neck.fpn_convs.2.conv.bias, neck.fpn_convs.3.conv.weight, neck.fpn_convs.3.conv.bias, neck.fpn_convs.4.conv.weight, neck.fpn_convs.4.conv.bias, bbox_head.cls_convs.0.conv.weight, bbox_head.cls_convs.0.conv.bias, bbox_head.cls_convs.1.conv.weight, bbox_head.cls_convs.1.conv.bias, bbox_head.cls_convs.2.conv.weight, bbox_head.cls_convs.2.conv.bias, bbox_head.cls_convs.3.conv.weight, bbox_head.cls_convs.3.conv.bias, bbox_head.reg_convs.0.conv.weight, bbox_head.reg_convs.0.conv.bias, bbox_head.reg_convs.1.conv.weight, bbox_head.reg_convs.1.conv.bias, bbox_head.reg_convs.2.conv.weight, bbox_head.reg_convs.2.conv.bias, bbox_head.reg_convs.3.conv.weight, bbox_head.reg_convs.3.conv.bias, bbox_head.retina_cls.weight, bbox_head.retina_cls.bias, bbox_head.retina_reg.weight, bbox_head.retina_reg.bias
2020-12-19 19:12:37,126 - vedadet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: backbone.fc.weight, backbone.fc.bias
missing keys in source state_dict: neck.lateral_convs.0.conv.weight, neck.lateral_convs.0.conv.bias, neck.lateral_convs.1.conv.weight, neck.lateral_convs.1.conv.bias, neck.lateral_convs.2.conv.weight, neck.lateral_convs.2.conv.bias, neck.fpn_convs.0.conv.weight, neck.fpn_convs.0.conv.bias, neck.fpn_convs.1.conv.weight, neck.fpn_convs.1.conv.bias, neck.fpn_convs.2.conv.weight, neck.fpn_convs.2.conv.bias, neck.fpn_convs.3.conv.weight, neck.fpn_convs.3.conv.bias, neck.fpn_convs.4.conv.weight, neck.fpn_convs.4.conv.bias, bbox_head.cls_convs.0.conv.weight, bbox_head.cls_convs.0.conv.bias, bbox_head.cls_convs.1.conv.weight, bbox_head.cls_convs.1.conv.bias, bbox_head.cls_convs.2.conv.weight, bbox_head.cls_convs.2.conv.bias, bbox_head.cls_convs.3.conv.weight, bbox_head.cls_convs.3.conv.bias, bbox_head.reg_convs.0.conv.weight, bbox_head.reg_convs.0.conv.bias, bbox_head.reg_convs.1.conv.weight, bbox_head.reg_convs.1.conv.bias, bbox_head.reg_convs.2.conv.weight, bbox_head.reg_convs.2.conv.bias, bbox_head.reg_convs.3.conv.weight, bbox_head.reg_convs.3.conv.bias, bbox_head.retina_cls.weight, bbox_head.retina_cls.bias, bbox_head.retina_reg.weight, bbox_head.retina_reg.bias `