Pre-training weights and model loading show mismatch

[GZ-YourZY]

I used the pre-training model you posted and the pre-training model loaded by default and it shows a model mismatch, why is that?

Traceback (most recent call last):
File "train.py", line 130, in
Logger.load_checkpoint(model, optimizer, scheduler)
File "/Volumetric-Aggregation-Transformer-main/common/logger.py", line 141, in load_checkpoint
model.load_state_dict(checkpoint['state_dict'])
File "/VAT/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1223, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for VAT:
Missing key(s) in state_dict: "backbone.conv1.weight", "backbone.bn1.weight", "backbone.bn1.bias", "backbone.bn1.running_mean", "backbone.bn1.running_var", "backbone.layer1.0.conv1.weight", "backbone.layer1.0.bn1.weight", "backbone.layer1.0.bn1.bias", "backbone.layer1.0.bn1.running_mean", "backbone.layer1.0.bn1.running_var", "backbone.layer1.0.conv2.weight", "backbone.layer1.0.bn2.weight", "backbone.layer1.0.bn2.bias", "backbone.layer1.0.bn2.running_mean", "backbone.layer1.0.bn2.running_var", "backbone.layer1.0.conv3.weight", "backbone.layer1.0.bn3.weight", "backbone.layer1.0.bn3.bias", "backbone.layer1.0.bn3.running_mean", "backbone.layer1.0.bn3.running_var", "backbone.layer1.0.downsample.0.weight", "backbone.layer1.0.downsample.1.weight", "backbone.layer1.0.downsample.1.bias", "backbone.layer1.0.downsample.1.running_mean", "backbone.layer1.0.downsample.1.running_var", "backbone.layer1.1.conv1.weight", "backbone.layer1.1.bn1.weight", "backbone.layer1.1.bn1.bias", "backbone.layer1.1.bn1.running_mean", "backbone.layer1.1.bn1.running_var", "backbone.layer1.1.conv2.weight", "backbone.layer1.1.bn2.weight", "backbone.layer1.1.bn2.bias", "backbone.layer1.1.bn2.running_mean", "backbone.layer1.1.bn2.running_var", "backbone.layer1.1.conv3.weight", "backbone.layer1.1.bn3.weight", "backbone.layer1.1.bn3.bias", "backbone.layer1.1.bn3.running_mean", "backbone.layer1.1.bn3.running_var", "backbone.layer1.2.conv1.weight", "backbone.layer1.2.bn1.weight", "backbone.layer1.2.bn1.bias", "backbone.layer1.2.bn1.running_mean", "backbone.layer1.2.bn1.running_var", "backbone.layer1.2.conv2.weight", "backbone.layer1.2.bn2.weight", "backbone.layer1.2.bn2.bias", "backbone.layer1.2.bn2.running_mean", "backbone.layer1.2.bn2.running_var", "backbone.layer1.2.conv3.weight", "backbone.layer1.2.bn3.weight", "backbone.layer1.2.bn3.bias", "backbone.layer1.2.bn3.running_mean", "backbone.layer1.2.bn3.running_var", "backbone.layer2.0.conv1.weight", "backbone.layer2.0.bn1.weight", "backbone.layer2.0.bn1.bias", "backbone.layer2.0.bn1.running_mean", "backbone.layer2.0.bn1.running_var", "backbone.layer2.0.conv2.weight", "backbone.layer2.0.bn2.weight", "backbone.layer2.0.bn2.bias", "backbone.layer2.0.bn2.running_mean", "backbone.layer2.0.bn2.running_var", "backbone.layer2.0.conv3.weight", "backbone.layer2.0.bn3.weight", "backbone.layer2.0.bn3.bias", "backbone.layer2.0.bn3.running_mean", "backbone.layer2.0.bn3.running_var", "backbone.layer2.0.downsample.0.weight", "backbone.layer2.0.downsample.1.weight", "backbone.layer2.0.downsample.1.bias", "backbone.layer2.0.downsample.1.running_mean", "backbone.layer2.0.downsample.1.running_var", "backbone.layer2.1.conv1.weight", "backbone.layer2.1.bn1.weight", "backbone.layer2.1.bn1.bias", "backbone.layer2.1.bn1.running_mean

[NicoCatalano]

Seems like in the checkpoint files the keys have an additional substring module.
You can remove it with something like:

# Load the checkpoint
checkpoint = torch.load('coco_resnet50/coco_resnet50_fold0/best_model.pt')['state_dict']

# Modify keys to remove the 'module.' prefix
modified_checkpoint = {key.replace('module.', ''): value for key, value in checkpoint.items()}


# Load trained model
model.load_state_dict(modified_checkpoint)