Yes, since the .module keywords will be added by nn.DataParallel you could store the internal model’s state_dict by accessing m.module.state_dict() where m is the nn.DataParallel object:
model = nn.Linear(1, 1)
print(model.state_dict())
> OrderedDict([('weight', tensor([[-0.8219]])), ('bias', tensor([-0.6302]))])

model = nn.DataParallel(model)
print(model.state_dict())
> OrderedDict([('module.weight', tensor([[-0.8219]], device='cuda:0')), ('module.bias', tensor([-0.6302], device='cuda:0'))])

print(model.module.state_dict())
> OrderedDict([('weight', tensor([[-0.8219]], device='cuda:0')), ('bias', tensor([-0.6302], device='cuda:0'))])