Thank you, you answer guided me to look at why my network don’t know state dict so is decide to use the constructor code from pytorch densenet and it works :
import re
Code modified from torchvision densenet source for loading from pre .4 densenet weights.
checkpoint = torch.load(’./model.pth.tar’)
state_dict = checkpoint[‘state_dict’]
remove_data_parallel = False # Change if you don’t want to use nn.DataParallel(model)
pattern = re.compile(
r’^(.*denselayer\d+.(?:norm|relu|conv)).((?:[12]).(?:weight|bias|running_mean|running_var))$’)
for key in list(state_dict.keys()):
match = pattern.match(key)
new_key = match.group(1) + match.group(2) if match else key
new_key = new_key[7:] if remove_data_parallel else new_key
state_dict[new_key] = state_dict[key]
# Delete old key only if modified.
if match or remove_data_parallel:
del state_dict[key]