Debug Keras tensorflow with Visual Studio code

I am trying to debug the following dummy code with Visual Studio code. However, even if I use tf.config.run_functions_eagerly(True), I always get the autograph_generated file instead of my original python code for the "layer_dummy" method. This seems to be triggered by the Keras input layer. Do you know why and how to fix it?

import tensorflow as tf

from tensorflow.keras import layers
from tensorflow.keras.models import Model

print("TensorFlow version:", tf.__version__)

tf.config.run_functions_eagerly(True)

class layer_dummy(layers.Layer):
    def __init__(self, **kwargs):
        super(layer_dummy, self).__init__(**kwargs)

        c_init = tf.ones_initializer()
        self.c = tf.Variable(
            initial_value=c_init(shape=[1,10]),
            trainable=True,
            name="dummy_var",
        )

    def call(self, x):
        return self.c + x


def make_dummy_model():
    vin = tf.keras.Input(shape=([1, 10]))
    ldummy = layer_dummy()
    vout = ldummy(vin)
    dummy_model = Model(inputs=vin, outputs=vout)
    return dummy_model


dummy = make_dummy_model()
dummy.summary()

exit()