The model and loaded state dict do not match exactly

[xzxedu]

Hi when I try to use extract.py to extract the features, I download the pretrained model from the link and run, but it shows the following:

The model and loaded state dict do not match exactly

unexpected key in source state_dict: conv1.weight, bn1.weight, bn1.bias, bn1.running_mean, bn1.running_var, bn1.num_batches_tracked, layer1.0.conv1.weight, layer1.0.bn1.weight, layer1.0.bn1.bias, layer1.0.bn1.running_mean, layer1.0.bn1.running_var, layer1.0.bn1.num_batches_tracked, layer1.0.conv2.weight, layer1.0.bn2.weight, layer1.0.bn2.bias, layer1.0.bn2.running_mean, layer1.0.bn2.running_var, layer1.0.bn2.num_batches_tracked, layer1.0.conv3.weight, layer1.0.bn3.weight, layer1.0.bn3.bias, layer1.0.bn3.running_mean, layer1.0.bn3.running_var, layer1.0.bn3.num_batches_tracked, layer1.0.downsample.0.weight, layer1.0.downsample.1.weight, layer1.0.downsample.1.bias, layer1.0.downsample.1.running_mean, layer1.0.downsample.1.running_var, layer1.0.downsample.1.num_batches_tracked, layer1.1.conv1.weight, layer1.1.bn1.weight, layer1.1.bn1.bias, layer1.1.bn1.running_mean, layer1.1.bn1.running_var, layer1.1.bn1.num_batches_tracked, layer1.1.conv2.weight, layer1.1.bn2.weight, layer1.1.bn2.bias, layer1.1.bn2.running_mean, layer1.1.bn2.running_var, layer1.1.bn2.num_batches_tracked, layer1.1.conv3.weight, layer1.1.bn3.weight, layer1.1.bn3.bias, layer1.1.bn3.running_mean, layer1.1.bn3.running_var, layer1.1.bn3.num_batches_tracked, layer1.2.conv1.weight, layer1.2.bn1.weight, layer1.2.bn1.bias, layer1.2.bn1.running_mean, layer1.2.bn1.running_var, layer1.2.bn1.num_batches_tracked, layer1.2.conv2.weight, layer1.2.bn2.weight, layer1.2.bn2.bias, layer1.2.bn2.running_mean, layer1.2.bn2.running_var, layer1.2.bn2.num_batches_tracked, layer1.2.conv3.weight, layer1.2.bn3.weight, layer1.2.bn3.bias, layer1.2.bn3.running_mean, layer1.2.bn3.running_var, layer1.2.bn3.num_batches_tracked, layer2.0.conv1.weight, layer2.0.bn1.weight, layer2.0.bn1.bias, layer2.0.bn1.running_mean, layer2.0.bn1.running_var, layer2.0.bn1.num_batches_tracked, layer2.0.conv2.weight, layer2.0.bn2.weight, layer2.0.bn2.bias, layer2.0.bn2.running_mean, layer2.0.bn2.running_var, layer2.0.bn2.num_batches_tracked, layer2.0.conv3.weight, layer2.0.bn3.weight, layer2.0.bn3.bias, layer2.0.bn3.running_mean, layer2.0.bn3.running_var, layer2.0.bn3.num_batches_tracked, layer2.0.downsample.0.weight, layer2.0.downsample.1.weight, layer2.0.downsample.1.bias, layer2.0.downsample.1.running_mean, layer2.0.downsample.1.running_var, layer2.0.downsample.1.num_batches_tracked, layer2.1.conv1.weight, layer2.1.bn1.weight, layer2.1.bn1.bias, layer2.1.bn1.running_mean, layer2.1.bn1.running_var, layer2.1.bn1.num_batches_tracked, layer2.1.conv2.weight, layer2.1.bn2.weight, layer2.1.bn2.bias, layer2.1.bn2.running_mean, layer2.1.bn2.running_var, layer2.1.bn2.num_batches_tracked, layer2.1.conv3.weight, layer2.1.bn3.weight, layer2.1.bn3.bias, layer2.1.bn3.running_mean, layer2.1.bn3.running_var, layer2.1.bn3.num_batches_tracked, layer2.2.conv1.weight, layer2.2.bn1.weight, layer2.2.bn1.bias, layer2.2.bn1.running_mean, layer2.2.bn1.running_var, layer2.2.bn1.num_batches_tracked, layer2.2.conv2.weight, layer2.2.bn2.weight, layer2.2.bn2.bias, layer2.2.bn2.running_mean, layer2.2.bn2.running_var, layer2.2.bn2.num_batches_tracked, layer2.2.conv3.weight, layer2.2.bn3.weight, layer2.2.bn3.bias, layer2.2.bn3.running_mean, layer2.2.bn3.running_var, layer2.2.bn3.num_batches_tracked, layer2.3.conv1.weight, layer2.3.bn1.weight, layer2.3.bn1.bias, layer2.3.bn1.running_mean, layer2.3.bn1.running_var, layer2.3.bn1.num_batches_tracked, layer2.3.conv2.weight, layer2.3.bn2.weight, layer2.3.bn2.bias, layer2.3.bn2.running_mean, layer2.3.bn2.running_var, layer2.3.bn2.num_batches_tracked, layer2.3.conv3.weight, layer2.3.bn3.weight, layer2.3.bn3.bias, layer2.3.bn3.running_mean, layer2.3.bn3.running_var, layer2.3.bn3.num_batches_tracked, layer3.0.conv1.weight, layer3.0.bn1.weight, layer3.0.bn1.bias, layer3.0.bn1.running_mean, layer3.0.bn1.running_var, layer3.0.bn1.num_batches_tracked, layer3.0.conv2.weight, layer3.0.bn2.weight, layer3.0.bn2.bias, layer3.0.bn2.running_mean, layer3.0.bn2.running_var, layer3.0.bn2.num_batches_tracked, layer3.0.conv3.weight, layer3.0.bn3.weight, layer3.0.bn3.bias, layer3.0.bn3.running_mean, layer3.0.bn3.running_var, layer3.0.bn3.num_batches_tracked, layer3.0.downsample.0.weight, layer3.0.downsample.1.weight, layer3.0.downsample.1.bias, layer3.0.downsample.1.running_mean, layer3.0.downsample.1.running_var, layer3.0.downsample.1.num_batches_tracked, layer3.1.conv1.weight, layer3.1.bn1.weight, layer3.1.bn1.bias, layer3.1.bn1.running_mean, layer3.1.bn1.running_var, layer3.1.bn1.num_batches_tracked, layer3.1.conv2.weight, layer3.1.bn2.weight, layer3.1.bn2.bias, layer3.1.bn2.running_mean, layer3.1.bn2.running_var, layer3.1.bn2.num_batches_tracked, layer3.1.conv3.weight, layer3.1.bn3.weight, layer3.1.bn3.bias, layer3.1.bn3.running_mean, layer3.1.bn3.running_var, layer3.1.bn3.num_batches_tracked, layer3.2.conv1.weight, layer3.2.bn1.weight, layer3.2.bn1.bias, layer3.2.bn1.running_mean, layer3.2.bn1.running_var, layer3.2.bn1.num_batches_tracked, layer3.2.conv2.weight, layer3.2.bn2.weight, layer3.2.bn2.bias, layer3.2.bn2.running_mean, layer3.2.bn2.running_var, layer3.2.bn2.num_batches_tracked, layer3.2.conv3.weight, layer3.2.bn3.weight, layer3.2.bn3.bias, layer3.2.bn3.running_mean, layer3.2.bn3.running_var, layer3.2.bn3.num_batches_tracked, layer3.3.conv1.weight, layer3.3.bn1.weight, layer3.3.bn1.bias, layer3.3.bn1.running_mean, layer3.3.bn1.running_var, layer3.3.bn1.num_batches_tracked, layer3.3.conv2.weight, layer3.3.bn2.weight, layer3.3.bn2.bias, layer3.3.bn2.running_mean, layer3.3.bn2.running_var, layer3.3.bn2.num_batches_tracked, layer3.3.conv3.weight, layer3.3.bn3.weight, layer3.3.bn3.bias, layer3.3.bn3.running_mean, layer3.3.bn3.running_var, layer3.3.bn3.num_batches_tracked, layer3.4.conv1.weight, layer3.4.bn1.weight, layer3.4.bn1.bias, layer3.4.bn1.running_mean, layer3.4.bn1.running_var, layer3.4.bn1.num_batches_tracked, layer3.4.conv2.weight, layer3.4.bn2.weight, layer3.4.bn2.bias, layer3.4.bn2.running_mean, layer3.4.bn2.running_var, layer3.4.bn2.num_batches_tracked, layer3.4.conv3.weight, layer3.4.bn3.weight, layer3.4.bn3.bias, layer3.4.bn3.running_mean, layer3.4.bn3.running_var, layer3.4.bn3.num_batches_tracked, layer3.5.conv1.weight, layer3.5.bn1.weight, layer3.5.bn1.bias, layer3.5.bn1.running_mean, layer3.5.bn1.running_var, layer3.5.bn1.num_batches_tracked, layer3.5.conv2.weight, layer3.5.bn2.weight, layer3.5.bn2.bias, layer3.5.bn2.running_mean, layer3.5.bn2.running_var, layer3.5.bn2.num_batches_tracked, layer3.5.conv3.weight, layer3.5.bn3.weight, layer3.5.bn3.bias, layer3.5.bn3.running_mean, layer3.5.bn3.running_var, layer3.5.bn3.num_batches_tracked, layer4.0.conv1.weight, layer4.0.bn1.weight, layer4.0.bn1.bias, layer4.0.bn1.running_mean, layer4.0.bn1.running_var, layer4.0.bn1.num_batches_tracked, layer4.0.conv2.weight, layer4.0.bn2.weight, layer4.0.bn2.bias, layer4.0.bn2.running_mean, layer4.0.bn2.running_var, layer4.0.bn2.num_batches_tracked, layer4.0.conv3.weight, layer4.0.bn3.weight, layer4.0.bn3.bias, layer4.0.bn3.running_mean, layer4.0.bn3.running_var, layer4.0.bn3.num_batches_tracked, layer4.0.downsample.0.weight, layer4.0.downsample.1.weight, layer4.0.downsample.1.bias, layer4.0.downsample.1.running_mean, layer4.0.downsample.1.running_var, layer4.0.downsample.1.num_batches_tracked, layer4.1.conv1.weight, layer4.1.bn1.weight, layer4.1.bn1.bias, layer4.1.bn1.running_mean, layer4.1.bn1.running_var, layer4.1.bn1.num_batches_tracked, layer4.1.conv2.weight, layer4.1.bn2.weight, layer4.1.bn2.bias, layer4.1.bn2.running_mean, layer4.1.bn2.running_var, layer4.1.bn2.num_batches_tracked, layer4.1.conv3.weight, layer4.1.bn3.weight, layer4.1.bn3.bias, layer4.1.bn3.running_mean, layer4.1.bn3.running_var, layer4.1.bn3.num_batches_tracked, layer4.2.conv1.weight, layer4.2.bn1.weight, layer4.2.bn1.bias, layer4.2.bn1.running_mean, layer4.2.bn1.running_var, layer4.2.bn1.num_batches_tracked, layer4.2.conv2.weight, layer4.2.bn2.weight, layer4.2.bn2.bias, layer4.2.bn2.running_mean, layer4.2.bn2.running_var, layer4.2.bn2.num_batches_tracked, layer4.2.conv3.weight, layer4.2.bn3.weight, layer4.2.bn3.bias, layer4.2.bn3.running_mean, layer4.2.bn3.running_var, layer4.2.bn3.num_batches_tracked

missing keys in source state_dict: queue, queue_ptr, queue2, queue2_ptr, encoder_q.0.conv1.weight, encoder_q.0.bn1.weight, encoder_q.0.bn1.bias, encoder_q.0.bn1.running_mean, encoder_q.0.bn1.running_var, encoder_q.0.layer1.0.conv1.weight, encoder_q.0.layer1.0.bn1.weight, encoder_q.0.layer1.0.bn1.bias, encoder_q.0.layer1.0.bn1.running_mean, encoder_q.0.layer1.0.bn1.running_var, encoder_q.0.layer1.0.conv2.weight, encoder_q.0.layer1.0.bn2.weight, encoder_q.0.layer1.0.bn2.bias, encoder_q.0.layer1.0.bn2.running_mean, encoder_q.0.layer1.0.bn2.running_var, encoder_q.0.layer1.0.conv3.weight, encoder_q.0.layer1.0.bn3.weight, encoder_q.0.layer1.0.bn3.bias, encoder_q.0.layer1.0.bn3.running_mean, encoder_q.0.layer1.0.bn3.running_var, encoder_q.0.layer1.0.downsample.0.weight, encoder_q.0.layer1.0.downsample.1.weight, encoder_q.0.layer1.0.downsample.1.bias, encoder_q.0.layer1.0.downsample.1.running_mean, encoder_q.0.layer1.0.downsample.1.running_var, encoder_q.0.layer1.1.conv1.weight, encoder_q.0.layer1.1.bn1.weight, encoder_q.0.layer1.1.bn1.bias, encoder_q.0.layer1.1.bn1.running_mean, encoder_q.0.layer1.1.bn1.running_var, encoder_q.0.layer1.1.conv2.weight, encoder_q.0.layer1.1.bn2.weight, encoder_q.0.layer1.1.bn2.bias, encoder_q.0.layer1.1.bn2.running_mean, encoder_q.0.layer1.1.bn2.running_var, encoder_q.0.layer1.1.conv3.weight, encoder_q.0.layer1.1.bn3.weight, encoder_q.0.layer1.1.bn3.bias, encoder_q.0.layer1.1.bn3.running_mean, encoder_q.0.layer1.1.bn3.running_var, encoder_q.0.layer1.2.conv1.weight, encoder_q.0.layer1.2.bn1.weight, encoder_q.0.layer1.2.bn1.bias, encoder_q.0.layer1.2.bn1.running_mean, encoder_q.0.layer1.2.bn1.running_var, encoder_q.0.layer1.2.conv2.weight, encoder_q.0.layer1.2.bn2.weight, encoder_q.0.layer1.2.bn2.bias, encoder_q.0.layer1.2.bn2.running_mean, encoder_q.0.layer1.2.bn2.running_var, encoder_q.0.layer1.2.conv3.weight, encoder_q.0.layer1.2.bn3.weight, encoder_q.0.layer1.2.bn3.bias, encoder_q.0.layer1.2.bn3.running_mean, encoder_q.0.layer1.2.bn3.running_var, encoder_q.0.layer2.0.conv1.weight, encoder_q.0.layer2.0.bn1.weight, encoder_q.0.layer2.0.bn1.bias, encoder_q.0.layer2.0.bn1.running_mean, encoder_q.0.layer2.0.bn1.running_var, encoder_q.0.layer2.0.conv2.weight, encoder_q.0.layer2.0.bn2.weight, encoder_q.0.layer2.0.bn2.bias, encoder_q.0.layer2.0.bn2.running_mean, encoder_q.0.layer2.0.bn2.running_var, encoder_q.0.layer2.0.conv3.weight, encoder_q.0.layer2.0.bn3.weight, encoder_q.0.layer2.0.bn3.bias, encoder_q.0.layer2.0.bn3.running_mean, encoder_q.0.layer2.0.bn3.running_var, encoder_q.0.layer2.0.downsample.0.weight, encoder_q.0.layer2.0.downsample.1.weight, encoder_q.0.layer2.0.downsample.1.bias, encoder_q.0.layer2.0.downsample.1.running_mean, encoder_q.0.layer2.0.downsample.1.running_var, encoder_q.0.layer2.1.conv1.weight, encoder_q.0.layer2.1.bn1.weight, encoder_q.0.layer2.1.bn1.bias, encoder_q.0.layer2.1.bn1.running_mean, encoder_q.0.layer2.1.bn1.running_var, encoder_q.0.layer2.1.conv2.weight, encoder_q.0.layer2.1.bn2.weight, encoder_q.0.layer2.1.bn2.bias, encoder_q.0.layer2.1.bn2.running_mean, encoder_q.0.layer2.1.bn2.running_var, encoder_q.0.layer2.1.conv3.weight, encoder_q.0.layer2.1.bn3.weight, encoder_q.0.layer2.1.bn3.bias, encoder_q.0.layer2.1.bn3.running_mean, encoder_q.0.layer2.1.bn3.running_var, encoder_q.0.layer2.2.conv1.weight, encoder_q.0.layer2.2.bn1.weight, encoder_q.0.layer2.2.bn1.bias, encoder_q.0.layer2.2.bn1.running_mean, encoder_q.0.layer2.2.bn1.running_var, encoder_q.0.layer2.2.conv2.weight, encoder_q.0.layer2.2.bn2.weight, encoder_q.0.layer2.2.bn2.bias, encoder_q.0.layer2.2.bn2.running_mean, encoder_q.0.layer2.2.bn2.running_var, encoder_q.0.layer2.2.conv3.weight, encoder_q.0.layer2.2.bn3.weight, encoder_q.0.layer2.2.bn3.bias, encoder_q.0.layer2.2.bn3.running_mean, encoder_q.0.layer2.2.bn3.running_var, encoder_q.0.layer2.3.conv1.weight, encoder_q.0.layer2.3.bn1.weight, encoder_q.0.layer2.3.bn1.bias, encoder_q.0.layer2.3.bn1.running_mean, encoder_q.0.layer2.3.bn1.running_var, encoder_q.0.layer2.3.conv2.weight, encoder_q.0.layer2.3.bn2.weight, encoder_q.0.layer2.3.bn2.bias, encoder_q.0.layer2.3.bn2.running_mean, encoder_q.0.layer2.3.bn2.running_var, encoder_q.0.layer2.3.conv3.weight, encoder_q.0.layer2.3.bn3.weight, encoder_q.0.layer2.3.bn3.bias, encoder_q.0.layer2.3.bn3.running_mean, encoder_q.0.layer2.3.bn3.running_var, encoder_q.0.layer3.0.conv1.weight, encoder_q.0.layer3.0.bn1.weight, encoder_q.0.layer3.0.bn1.bias, encoder_q.0.layer3.0.bn1.running_mean, encoder_q.0.layer3.0.bn1.running_var, encoder_q.0.layer3.0.conv2.weight, encoder_q.0.layer3.0.bn2.weight, encoder_q.0.layer3.0.bn2.bias, encoder_q.0.layer3.0.bn2.running_mean, encoder_q.0.layer3.0.bn2.running_var, encoder_q.0.layer3.0.conv3.weight, encoder_q.0.layer3.0.bn3.weight, encoder_q.0.layer3.0.bn3.bias, encoder_q.0.layer3.0.bn3.running_mean, encoder_q.0.layer3.0.bn3.running_var, encoder_q.0.layer3.0.downsample.0.weight, encoder_q.0.layer3.0.downsample.1.weight, encoder_q.0.layer3.0.downsample.1.bias, encoder_q.0.layer3.0.downsample.1.running_mean, encoder_q.0.layer3.0.downsample.1.running_var, encoder_q.0.layer3.1.conv1.weight, encoder_q.0.layer3.1.bn1.weight, encoder_q.0.layer3.1.bn1.bias, encoder_q.0.layer3.1.bn1.running_mean, encoder_q.0.layer3.1.bn1.running_var, encoder_q.0.layer3.1.conv2.weight, encoder_q.0.layer3.1.bn2.weight, encoder_q.0.layer3.1.bn2.bias, encoder_q.0.layer3.1.bn2.running_mean, encoder_q.0.layer3.1.bn2.running_var, encoder_q.0.layer3.1.conv3.weight, encoder_q.0.layer3.1.bn3.weight, encoder_q.0.layer3.1.bn3.bias, encoder_q.0.layer3.1.bn3.running_mean, encoder_q.0.layer3.1.bn3.running_var, encoder_q.0.layer3.2.conv1.weight, encoder_q.0.layer3.2.bn1.weight, encoder_q.0.layer3.2.bn1.bias, encoder_q.0.layer3.2.bn1.running_mean, encoder_q.0.layer3.2.bn1.running_var, encoder_q.0.layer3.2.conv2.weight, encoder_q.0.layer3.2.bn2.weight, encoder_q.0.layer3.2.bn2.bias, 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[gabys-tb]

hi! were you able to solve this?