about pretrained model

[wanboyang]

when I use pretrained model DIFNet.pth， some errors reports： RuntimeError: Error(s) in loading state_dict for Difnet_LRP: Missing key(s) in state_dict: "decoder.layers.0.pwff.layer_norm1.weight", "decoder.layers.0.pwff.layer_norm1.bias", "decoder.layers.1.pwff.layer_norm1.weight", "decoder.layers.1.pwff.layer_norm1.bias", "decoder.layers.2.pwff.layer_norm1.weight", "decoder.layers.2.pwff.layer_norm1.bias". It seems a mismatch between Difnet_LRP architecture code and the pretrained model weights.

[wanboyang]

and I retrain the Difnet_LRP by using the default setting. The performance is lower than the one reported in this paper.

[mrwu-mac]

when I use pretrained model DIFNet.pth， some errors reports： RuntimeError: Error(s) in loading state_dict for Difnet_LRP: Missing key(s) in state_dict: "decoder.layers.0.pwff.layer_norm1.weight", "decoder.layers.0.pwff.layer_norm1.bias", "decoder.layers.1.pwff.layer_norm1.weight", "decoder.layers.1.pwff.layer_norm1.bias", "decoder.layers.2.pwff.layer_norm1.weight", "decoder.layers.2.pwff.layer_norm1.bias". It seems a mismatch between Difnet_LRP architecture code and the pretrained model weights.

We are sorry for this, we have updated the code. Note that difnet_lrp use a decoder as same as the base_lrp.

[zhangxuying1004]

when I use pretrained model DIFNet.pth， some errors reports： RuntimeError: Error(s) in loading state_dict for Difnet_LRP: Missing key(s) in state_dict: "decoder.layers.0.pwff.layer_norm1.weight", "decoder.layers.0.pwff.layer_norm1.bias", "decoder.layers.1.pwff.layer_norm1.weight", "decoder.layers.1.pwff.layer_norm1.bias", "decoder.layers.2.pwff.layer_norm1.weight", "decoder.layers.2.pwff.layer_norm1.bias". It seems a mismatch between Difnet_LRP architecture code and the pretrained model weights.

Our code has been updated, and the test results of our pre-trained difnet_lrp are as follows:

[wanboyang]

Thanks for replying