Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

dummy_list
Output
[(Linear(in_features=1, out_features=1, bias=True),
(tensor([0.3000]),),
tensor([-0.7514], grad_fn=<AddBackward0>))]
Now we’re talking! Here is the tuple we were expecting! If you call the model once
again, it will append yet another tuple to the list, and so on and so forth. This hook
is going to be hooked to our model until it is explicitly removed (hence the need to
keep the handles). To remove a hook, you can simply call its remove() method:
dummy_handle.remove()
And the hook goes bye-bye! But we did not lose the collected information, since
our variable, dummy_list, was defined outside the hook function.
Look at the first element of the tuple: It is an instance of a model (or layer). Even if
we use a Sequential model and name the layers, the names won’t make it to the
hook function. So we need to be clever here and make the association ourselves.
Let’s get back to our real model now. We can get a list of all its named modules by
using the appropriate method: named_modules() (what else could it be?!).
modules = list(sbs_cnn1.model.named_modules())
modules
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