Failed loading checkpoint

[ranpin]

Hi, I'm trying to use your code as a backbone and load the pre-training weights, but have found some issues.

I have not modified anything in efficientVMamba.py and the environment is configured correctly. I refer to your loading method in detection/test_ckpt.py and the code is as follows when I load it:

# image_encoder = Backbone_EfficientVSSM( pretrained='checkpoints/efficient_vmamba_tiny.ckpt' )
# image_encoder = Backbone_EfficientVSSM( pretrained='checkpoints/efficient_vmamba_small.ckpt' )
   image_encoder = Backbone_EfficientVSSM( pretrained='checkpoints/efficient_vmamba_base.ckpt' )

And to verify that it was loaded correctly, I changed just one line of code in Class Backbone_EfficientVSSM in efficientVMamba.py as follows:

# incompatibleKeys = self.load_state_dict(new_state_dict, strict=False) #your before
incompatibleKeys = self.load_state_dict(new_state_dict, strict=True) # changed by me

But I found the following error reported:

Successfully loaded checkpoint from checkpoints/efficient_vmamba_base.ckpt
Failed loading checkpoint from checkpoints/efficient_vmamba_base.ckpt: Error(s) in loading state_dict for Backbone_EfficientVSSM:
Missing key(s) in state_dict: "layers.0.blocks.0.norm2.weight", "layers.0.blocks.0.norm2.bias", "layers.0.blocks.0.mlp.fc1.weight", "layers.0.blocks.0.mlp.fc1.bias", "layers.0.blocks.0.mlp.fc2.weight", "layers.0.blocks.0.mlp.fc2.bias", "layers.0.blocks.1.norm2.weight", "layers.0.blocks.1.norm2.bias", "layers.0.blocks.1.mlp.fc1.weight", "layers.0.blocks.1.mlp.fc1.bias", "layers.0.blocks.1.mlp.fc2.weight", "layers.0.blocks.1.mlp.fc2.bias", "layers.0.downsample.1.weight", "layers.0.downsample.1.bias", "layers.0.downsample.3.weight", "layers.0.downsample.3.bias", "layers.1.blocks.0.norm2.weight", "layers.1.blocks.0.norm2.bias", "layers.1.blocks.0.mlp.fc1.weight", "layers.1.blocks.0.mlp.fc1.bias", "layers.1.blocks.0.mlp.fc2.weight", "layers.1.blocks.0.mlp.fc2.bias", "layers.1.blocks.1.norm2.weight", "layers.1.blocks.1.norm2.bias", "layers.1.blocks.1.mlp.fc1.weight", "layers.1.blocks.1.mlp.fc1.bias", "layers.1.blocks.1.mlp.fc2.weight", "layers.1.blocks.1.mlp.fc2.bias", "layers.1.downsample.1.weight", "layers.1.downsample.1.bias", "layers.1.downsample.3.weight", "layers.1.downsample.3.bias", "layers.2.11.1.weight", "layers.2.11.1.bias", "layers.2.11.3.weight", "layers.2.11.3.bias", "outnorm0.weight", "outnorm0.bias", "outnorm1.weight", "outnorm1.bias", "outnorm2.weight", "outnorm2.bias", "outnorm3.weight", "outnorm3.bias".
Unexpected key(s) in state_dict: "classifier.norm.weight", "classifier.norm.bias", "classifier.head.weight", "classifier.head.bias", "layers.0.downsample.reduction.weight", "layers.0.downsample.norm.weight", "layers.0.downsample.norm.bias", "layers.1.downsample.reduction.weight", "layers.1.downsample.norm.weight", "layers.1.downsample.norm.bias", "layers.2.11.reduction.weight", "layers.2.11.norm.weight", "layers.2.11.norm.bias".

The similar problem occurs when loading the other two weights. May I ask if there is a mismatch between the currently uploaded weights and the model code? Or am I missing something? Looking forward to your reply, thanks!