Problem about testing my trained model about swinir HOT 5 CLOSED

The main difference between my pretrained model and yours (trained on KAIR) is that:
1, my pretrained model is a dict: {'params': model}.
2, KAIR's model is just the model.

Therefore, you have to use the following line to load my pretrained model:

model.load_state_dict(torch.load(args.model_path)['params'], strict=True) # specify the dict key

and the following line to load your trained model (on KAIR)

model.load_state_dict(torch.load(args.model_path), strict=True) # directly load it

Sorry for the inconsistence between KAIR and SwinIR testing code. We will fix this problem.

from swinir.

Hi, sorry for this bug. Please remove ['params'] in Line 126

model.load_state_dict(torch.load(args.model_path), strict=True). 

from swinir.

Hi, sorry for this bug. Please remove ['params'] in Line 126

SwinIR/main_test_swinir.py

Line 126 in 96a446f

model.load_state_dict(torch.load(args.model_path)['params'], strict=True)

as

model.load_state_dict(torch.load(args.model_path), strict=True). 

Thanks for reply.
I notice that when I ran your pretrained model, the main_test_swinir.py works fine.
However, when I ran main_test_swinir.py with either 500000_optimizerG.pth 500000_G.pth 500000_E.pth, it occurs the above error.
Is it the 500000_G.pth has some problem?

from swinir.

Update: I have fixed the bug.

from swinir.

Thanks a lot.

from swinir.