When I want to initialize weights, I use following snippet:
def weights_init(model):
    if type(model) in [nn.Conv2d,nn.Linear]:
        nn.init.xavier_normal_(model.weight.data)
        nn.init.constant_(model.bias.data, 0.1)

I use this, when I want to initialize the entire layer type.
But how can I initialize child layer of a layer type, e.g. only one layer of a Conv2d layer type?
Is the following snippet a correct approach?
def weightsPart_init(model):
    for child in list(model.children())[12:13]:       # just one Conv2d layer
      nn.init.xavier_normal_(child.weight.data)
      nn.init.constant_(child.bias.data, 0.1)

Reason for that is, that I have a pretrained model, from which I want to load the weights of specific convolutional layers and use as fixed feature extractor. But the last convolutional layer, I want to initalize with xavier_normal and retrain.
Thanks for help.