How can I extract the weight and bias of Linear layers in PyTorch?

Question

In model.state_dict(), model.parameters() and model.named_parameters() weights and biases of nn.Linear() modules are contained separately, e.q. fc1.weight and fc1.bias. Is there a simple pythonic way to get both of them?

Expected example looks similar to this:

layer = model['fc1']
print(layer.weight)
print(layer.bias)

Answer 1

You can recover the named parameters for each linear layer in your model like so:

from torch import nn

for layer in model.children():
    if isinstance(layer, nn.Linear):
        print(layer.state_dict()['weight'])
        print(layer.state_dict()['bias'])