RuntimeError: Error(s) in loading state_dict for DataParallel

[drsleep]

RuntimeError: Error(s) in loading state_dict for DataParallel

[DrSleep]

looks like you are trying to load from "args.ckpt_path", which defines the model with 40 classes, while you created the model with 2. You either need to provide correct ckpt_path to the model with 2 classes (if it exists), or omit that path altogether

[xiaoyuamw]

I am so sorry that I am a freshman for it, I just change NUM_CLASSES = [40] * 3 in this file(config.py) to NUM_CLASSES = [2] * 3 because of my train(val) datasets needed to be devided into 2 classes.

but it run,and error:

INFO:main: Loaded Segmenter 50, ImageNet-Pre-Trained=True, #PARAMS=27.31M
Traceback (most recent call last):
File "C:/Users/likun3/Documents/light-weight-refinenet-master/src/train.py", line 432, in
main()
File "C:/Users/likun3/Documents/light-weight-refinenet-master/src/train.py", line 367, in main
best_val, epoch_start = load_ckpt(args.ckpt_path, {'segmenter' : segmenter})
File "C:/Users/likun3/Documents/light-weight-refinenet-master/src/train.py", line 240, in load_ckpt
v.load_state_dict(ckpt[k])
File "D:\Soft\Anaconda_\envs\dp\lib\site-packages\torch\nn\modules\module.py", line 769, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for DataParallel:
size mismatch for module.clf_conv.weight: copying a param with shape torch.Size([40, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([2, 256, 3, 3]).
size mismatch for module.clf_conv.bias: copying a param with shape torch.Size([40]) from checkpoint, the shape in current model is torch.Size([2]).

Could someone help me ? please~~~

Hi @LiKunWHU

I also met such an error now and don't know how to solve it! So, i want to ask whether you had solved it before? if so, can you tell me how you do?

Thank you very much!

Best Regards.