[Docs] ckpt `mv-3ddet.pth` doesn't work for grounding task

[iris0329]

Branch

main branch https://mmdetection3d.readthedocs.io/en/latest/

📚 The doc issue

Thanks for your awesome work!

To run 3d grounding task with train.py, the downloaded 3d-detection ckpt mv-3ddet.pth mentioned in readme doesn't work after replacing work_dirs/mv-3ddet/epoch_12.pth in configs/grounding/mv-grounding_8xb12_embodiedscan-vg-9dof.py

Did I miss something? I look forward to your reply. Thanks in advance.

I paste the error log:

04/03 01:06:47 - mmengine - WARNING - The model and loaded state dict do not match exactly

size mismatch for conv1.weight: copying a param with shape torch.Size([64, 3, 7, 7]) from checkpoint, the shape in current model is torch.Size([16, 3, 7, 7]).
size mismatch for bn1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for bn1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for bn1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for bn1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.0.conv1.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([16, 16, 1, 1]).
size mismatch for layer1.0.bn1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.0.bn1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.0.bn1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.0.bn1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.0.conv2.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([16, 16, 3, 3]).
size mismatch for layer1.0.bn2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.0.bn2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.0.bn2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.0.bn2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.0.conv3.weight: copying a param with shape torch.Size([256, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 16, 1, 1]).
size mismatch for layer1.0.bn3.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.0.bn3.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.0.bn3.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.0.bn3.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.0.downsample.0.weight: copying a param with shape torch.Size([256, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 16, 1, 1]).
size mismatch for layer1.0.downsample.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.0.downsample.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.0.downsample.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.0.downsample.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.1.conv1.weight: copying a param with shape torch.Size([64, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([16, 64, 1, 1]).
size mismatch for layer1.1.bn1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.1.bn1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.1.bn1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.1.bn1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.1.conv2.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([16, 16, 3, 3]).
size mismatch for layer1.1.bn2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.1.bn2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.1.bn2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.1.bn2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.1.conv3.weight: copying a param with shape torch.Size([256, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 16, 1, 1]).
size mismatch for layer1.1.bn3.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.1.bn3.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.1.bn3.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.1.bn3.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.2.conv1.weight: copying a param with shape torch.Size([64, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([16, 64, 1, 1]).
size mismatch for layer1.2.bn1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.2.bn1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.2.bn1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.2.bn1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.2.conv2.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([16, 16, 3, 3]).
size mismatch for layer1.2.bn2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.2.bn2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.2.bn2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.2.bn2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for layer1.2.conv3.weight: copying a param with shape torch.Size([256, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 16, 1, 1]).
size mismatch for layer1.2.bn3.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.2.bn3.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.2.bn3.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer1.2.bn3.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer2.0.conv1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([32, 64, 1, 1]).
size mismatch for layer2.0.bn1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.0.bn1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.0.bn1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.0.bn1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.0.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]).
size mismatch for layer2.0.bn2.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.0.bn2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.0.bn2.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.0.bn2.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.0.conv3.weight: copying a param with shape torch.Size([512, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 32, 1, 1]).
size mismatch for layer2.0.bn3.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.0.bn3.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.0.bn3.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.0.bn3.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.0.downsample.0.weight: copying a param with shape torch.Size([512, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 64, 1, 1]).
size mismatch for layer2.0.downsample.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.0.downsample.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.0.downsample.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.0.downsample.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.1.conv1.weight: copying a param with shape torch.Size([128, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([32, 128, 1, 1]).
size mismatch for layer2.1.bn1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.1.bn1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.1.bn1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.1.bn1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.1.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]).
size mismatch for layer2.1.bn2.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.1.bn2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.1.bn2.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.1.bn2.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.1.conv3.weight: copying a param with shape torch.Size([512, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 32, 1, 1]).
size mismatch for layer2.1.bn3.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.1.bn3.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.1.bn3.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.1.bn3.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.2.conv1.weight: copying a param with shape torch.Size([128, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([32, 128, 1, 1]).
size mismatch for layer2.2.bn1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.2.bn1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.2.bn1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.2.bn1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.2.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]).
size mismatch for layer2.2.bn2.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.2.bn2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.2.bn2.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.2.bn2.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.2.conv3.weight: copying a param with shape torch.Size([512, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 32, 1, 1]).
size mismatch for layer2.2.bn3.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.2.bn3.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.2.bn3.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.2.bn3.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.3.conv1.weight: copying a param with shape torch.Size([128, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([32, 128, 1, 1]).
size mismatch for layer2.3.bn1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.3.bn1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.3.bn1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.3.bn1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.3.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]).
size mismatch for layer2.3.bn2.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.3.bn2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.3.bn2.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.3.bn2.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for layer2.3.conv3.weight: copying a param with shape torch.Size([512, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 32, 1, 1]).
size mismatch for layer2.3.bn3.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.3.bn3.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.3.bn3.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer2.3.bn3.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer3.0.conv1.weight: copying a param with shape torch.Size([256, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 128, 1, 1]).
size mismatch for layer3.0.bn1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.0.bn1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.0.bn1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.0.bn1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.0.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for layer3.0.bn2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.0.bn2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.0.bn2.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.0.bn2.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.0.conv3.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 64, 1, 1]).
size mismatch for layer3.0.bn3.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.0.bn3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.0.bn3.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.0.bn3.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.0.downsample.0.weight: copying a param with shape torch.Size([1024, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 128, 1, 1]).
size mismatch for layer3.0.downsample.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.0.downsample.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.0.downsample.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.0.downsample.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.1.conv1.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 256, 1, 1]).
size mismatch for layer3.1.bn1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.1.bn1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.1.bn1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.1.bn1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.1.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for layer3.1.bn2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.1.bn2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.1.bn2.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.1.bn2.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.1.conv3.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 64, 1, 1]).
size mismatch for layer3.1.bn3.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.1.bn3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.1.bn3.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.1.bn3.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.2.conv1.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 256, 1, 1]).
size mismatch for layer3.2.bn1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.2.bn1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.2.bn1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.2.bn1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.2.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for layer3.2.bn2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.2.bn2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.2.bn2.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.2.bn2.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.2.conv3.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 64, 1, 1]).
size mismatch for layer3.2.bn3.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.2.bn3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.2.bn3.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.2.bn3.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.3.conv1.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 256, 1, 1]).
size mismatch for layer3.3.bn1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.3.bn1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.3.bn1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.3.bn1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.3.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for layer3.3.bn2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.3.bn2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.3.bn2.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.3.bn2.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.3.conv3.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 64, 1, 1]).
size mismatch for layer3.3.bn3.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.3.bn3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.3.bn3.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.3.bn3.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.4.conv1.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 256, 1, 1]).
size mismatch for layer3.4.bn1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.4.bn1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.4.bn1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.4.bn1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.4.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for layer3.4.bn2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.4.bn2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.4.bn2.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.4.bn2.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.4.conv3.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 64, 1, 1]).
size mismatch for layer3.4.bn3.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.4.bn3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.4.bn3.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.4.bn3.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.5.conv1.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 256, 1, 1]).
size mismatch for layer3.5.bn1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.5.bn1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.5.bn1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.5.bn1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.5.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for layer3.5.bn2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.5.bn2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.5.bn2.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.5.bn2.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for layer3.5.conv3.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 64, 1, 1]).
size mismatch for layer3.5.bn3.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.5.bn3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.5.bn3.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer3.5.bn3.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for layer4.0.conv1.weight: copying a param with shape torch.Size([512, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 256, 1, 1]).
size mismatch for layer4.0.bn1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.0.bn1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.0.bn1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.0.bn1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.0.conv2.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for layer4.0.bn2.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.0.bn2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.0.bn2.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.0.bn2.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.0.conv3.weight: copying a param with shape torch.Size([2048, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([512, 128, 1, 1]).
size mismatch for layer4.0.bn3.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.0.bn3.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.0.bn3.running_mean: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.0.bn3.running_var: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.0.downsample.0.weight: copying a param with shape torch.Size([2048, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([512, 256, 1, 1]).
size mismatch for layer4.0.downsample.1.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.0.downsample.1.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.0.downsample.1.running_mean: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.0.downsample.1.running_var: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.1.conv1.weight: copying a param with shape torch.Size([512, 2048, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 512, 1, 1]).
size mismatch for layer4.1.bn1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.1.bn1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.1.bn1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.1.bn1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.1.conv2.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for layer4.1.bn2.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.1.bn2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.1.bn2.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.1.bn2.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.1.conv3.weight: copying a param with shape torch.Size([2048, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([512, 128, 1, 1]).
size mismatch for layer4.1.bn3.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.1.bn3.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.1.bn3.running_mean: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.1.bn3.running_var: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.2.conv1.weight: copying a param with shape torch.Size([512, 2048, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 512, 1, 1]).
size mismatch for layer4.2.bn1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.2.bn1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.2.bn1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.2.bn1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.2.conv2.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for layer4.2.bn2.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.2.bn2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.2.bn2.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.2.bn2.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for layer4.2.conv3.weight: copying a param with shape torch.Size([2048, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([512, 128, 1, 1]).
size mismatch for layer4.2.bn3.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.2.bn3.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.2.bn3.running_mean: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for layer4.2.bn3.running_var: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([512]).
unexpected key in source state_dict: fc.weight, fc.bias

Traceback (most recent call last):
  File "tools/train.py", line 158, in <module>
    main()
  File "tools/train.py", line 154, in main
    runner.train()
  File "/home/debug/anaconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1765, in train
    self.load_or_resume()
  File "/home/debug/anaconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1696, in load_or_resume
    self.resume(resume_from)
  File "/home/debug/anaconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/runner.py", line 2017, in resume
    checkpoint = self.load_checkpoint(filename, map_location=device)
  File "/home/debug/anaconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/runner.py", line 2127, in load_checkpoint
    checkpoint = _load_checkpoint(filename, map_location=map_location)
  File "/home/debug/anaconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/checkpoint.py", line 548, in _load_checkpoint
    return CheckpointLoader.load_checkpoint(filename, map_location, logger)
  File "/home/debug/anaconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/checkpoint.py", line 324, in load_checkpoint
    checkpoint_loader = cls._get_checkpoint_loader(filename)
  File "/home/debug/anaconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/checkpoint.py", line 307, in _get_checkpoint_loader
    if re.match(p, path) is not None:
  File "/home/debug/anaconda3/envs/embodiedscan/lib/python3.8/re.py", line 191, in match
    return _compile(pattern, flags).match(string)
TypeError: expected string or bytes-like object

Suggest a potential alternative/fix

No response

[Tai-Wang]

What is your specific command and do you use --resume? It seems the detection checkpoint might be incomplete or broken. You can try to re-download the checkpoint and ensure the downloading is successful.

[Tai-Wang]

Close due to inactivity. Please feel free to reopen this issue if you have any further questions.

[iris0329]

Thank you @Tai-Wang, it's becuase the --resume flag.