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

You can access modules by name using _modules:

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()

        self.conv1 = nn.Conv2d(3, 3, 3)

    def forward(self, input):
        return self.conv1(input)

model = Net()
print(model._modules['conv1'])