Keras retrieve value of node before activation function

Question

Imagine a fully-connected neural network with its last two layers of the following structure:

[Dense]
    units = 612
    activation = softplus

[Dense]
    unit         


        

Answer 1

easy way to define new layer with new activation function:

def change_layer_activation(layer):

    if isinstance(layer, keras.layers.Conv2D):

        config = layer.get_config()
        config["activation"] = "linear"
        new = keras.layers.Conv2D.from_config(config)

    elif isinstance(layer, keras.layers.Dense):

        config = layer.get_config()
        config["activation"] = "linear"
        new = keras.layers.Dense.from_config(config)

    weights = [x.numpy() for x in layer.weights]

    return new, weights