The parameters of a CNN model is returning None

vision
1

Hello, i create a CNN model like this global_model = CNNMnist(args=args). Then i send it to device, set it to train. Then i train my local models, collect the local_weights and the average them to get updated global_model.
Now i am trying to get the items from the .parameters() function but all i get is None as item.grad. When i do the same thing for the local_models, i get the desired output. What am i doing wrong?

global_model.to(device)
global_model.train()
...................
global_weights = average_weights(local_weights)
global_model.load_state_dict(global_weights)
last_update = []
for item in global_model.parameters():
    last_update.append(copy.deepcopy(item.grad))
    print(item.grad)

Output: None None None None None None None None

Any help would be appreciated.

2

item.grad stores the gradients of the parameters wrt the loss function and not the weights.

What you want is -

weights = [c.detach().numpy() for c in global_model.parameters()]

3

Hi, thanks for your reply. could you please elaborate a little? where exactly should i insert the line and how do i get the desired outcome?
Thanks

4

Hi. You can try the following.

for param in global_model.parameters():
    last_update.append(param.clone().data.cpu().numpy())