PyTorch, nn.Sequential(), access weights of a specific module in nn.Sequential()

Question

this should be a quick one. When I use a pre-defined module in PyTorch, I can typically access its weights fairly easily. However, how do I access them if I wrapped the modu

Answer 1

An easy way to access the weights is to use the state_dict() of your model.

This should work in your case:

for k, v in model_2.state_dict().iteritems():
    print("Layer {}".format(k))
    print(v)

Another option is to get the modules() iterator. If you know beforehand the type of your layers this should also work:

for layer in model_2.modules():
   if isinstance(layer, nn.Linear):
        print(layer.weight)