Unexpected key(s) in state_dict

I get an RuntimeError: Error(s) in loading state_dict for DataParallel: I when I tried to load a model as follows;

model = ModelMark1()
model = torch.nn.DataParallel(model)
checkpoint = torch.load(checkpoint_path, map_location=device)

The details of error;

Unexpected key(s) in state_dict: "module.velocity_model.some_layer.gen_fc.linear.weight", "module.velocity_model.some_layer.gen_fc.linear.bias".

Here is the printed checkpoint dictionary;

odict_keys(['module.spectrogram_extractor.stft.conv_real.weight', 'module.spectrogram_extractor.stft.conv_imag.weight', 'module.logmel_extractor.melW', 'module.bn0.weight', 'module.bn0.bias', 'module.bn0.running_mean', 'module.bn0.running_var', 'module.bn0.num_batches_tracked', 'module.velocity_model.conv_block1.conv1.weight', 'module.velocity_model.conv_block1.conv2.weight', 'module.velocity_model.conv_block1.bn1.weight', 'module.velocity_model.conv_block1.bn1.bias', 'module.velocity_model.conv_block1.bn1.running_mean', 'module.velocity_model.conv_block1.bn1.running_var', 'module.velocity_model.conv_block1.bn1.num_batches_tracked', 'module.velocity_model.conv_block1.bn2.weight', 'module.velocity_model.conv_block1.bn2.bias', 'module.velocity_model.conv_block1.bn2.running_mean', 'module.velocity_model.conv_block1.bn2.running_var', 'module.velocity_model.conv_block1.bn2.num_batches_tracked',  'module.velocity_model.fc.weight', 'module.velocity_model.fc.bias', 'module.velocity_model.some_layer.gen_fc.linear.weight', 'module.velocity_model.some_layer.gen_fc.linear.bias'])

I am not too sure what are the problem here since the module.velocity_model. keys are loaded.
Also the model structure, names are not changed in ModelMark1.
Please let me know if you have advice/clue/solution on this issue.
Thank you so much for your help in advance!

Check for typos or provide the state dictionary of the new model you are trying to set.

There is no typo I think since it is generated by pytorch and I just loaded them.
The model I trained is one which have those unexpected keys and is the same as ModelMark1. I do not known why there is model does not recognize the 2 keys.
Is there any way to check all expected keys by the ModelMark1?

I think the problem is that the layer contains these 2 unexpected keys are not initialized in constructor but in a forward method. Does this cause not creating keys when instantiating the ModelMark1?
If so is there any way to add “mock keys” of the 2 keys in the state_dict and run the model for evaluation or testing purposes?