Runtime error: size mismatch

[yamiefun]

Hi,
I'm running the google colab provided in README, and I want to subtitude the model to HRNetv2. I download the weights file for encoder and decoder from the link provided in README, and modify the net_encoder and net_decoder weights in the colab, but encounter some error. Here is the error message, do I need to modify anything else?

Loading weights for net_encoder

RuntimeError Traceback (most recent call last)
in ()
4 fc_dim=2048,
5 #weights='ckpt/ade20k-resnet50dilated-ppm_deepsup/encoder_epoch_20.pth')
----> 6 weights='drive/MyDrive/corner/encoder_epoch_30.pth')
7 net_decoder = ModelBuilder.build_decoder(
8 arch='ppm_deepsup',

1 frames
/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in load_state_dict(self, state_dict, strict)
1222 if len(error_msgs) > 0:
1223 raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
-> 1224 self.class.name, "\n\t".join(error_msgs)))
1225 return _IncompatibleKeys(missing_keys, unexpected_keys)
1226

RuntimeError: Error(s) in loading state_dict for ResnetDilated:
size mismatch for layer1.0.conv1.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 128, 1, 1]).
size mismatch for layer1.0.downsample.0.weight: copying a param with shape torch.Size([256, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 128, 1, 1]).