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


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'])

