From discussion: https://groups.google.com/a/tensorflow.org/g/discuss/c/c0-oY9ajKfc/m/UYbokrc_BAAJ

simple_network.py

from tensorflow import keras
import numpy as np
from IPython import embed


INPUT_SHAPE = (3, 3, 1)
CONV_SIZE = 3
model_name = 'test_model'

def create_model():
    sub_image = keras.layers.Input(shape=INPUT_SHAPE, name="image")
    c2d=keras.layers.Conv2D(1, (CONV_SIZE, CONV_SIZE), use_bias=False, name="C2D")(sub_image)
    output = keras.layers.Dense(1, name="action",use_bias=False,trainable=False)(c2d)
    model = keras.models.Model(inputs=sub_image, outputs=output, name=model_name)   
    return model

input = np.ones((1, 3, 3, 1), dtype=np.float)

embed()

model = create_model()
result = model(input)

hl1_weights = model.layers[1].get_weights()
print(np.sum(hl1_weights))

hl2_weights = model.layers[2].get_weights()
print(np.sum(hl2_weights))

print(np.sum(hl1_weights) * np.sum(hl2_weights))

print(f'tf run sum={result}')