Solved by ptrblck in post #2 
              
              
                Your approach should work, as seen in this example: 
lin = nn.Linear(1, 1)
sd = lin.state_dict()
print(sd)
> OrderedDict([('weight', tensor([[-0.5414]])), ('bias', tensor([0.8279]))])

sd['weight'].copy_(torch.tensor([[1.]]))
print(lin.state_dict())
> OrderedDict([('weight', tensor([[1.]])), ('bias'…