Why the value of a variable inside a tensorflow graph not frozen

Question

I'm trying to save and load the graph of a tensorflow module that contains a tf.Variable as an intern variable.

Here is the code:

import tensorflow as tf

class MyModule(tf.Module):
    def __init__(self, v):
        self.v = v
        pass

    @tf.function(input_signature=[tf.TensorSpec(shape=None, dtype=tf.int32), tf.TensorSpec(shape=None, dtype=tf.int32)])
    def __call__(self, x, v):
        self.v.assign( x * v, read_value=False )
        return self.v

x = tf.constant( tf.random.uniform(shape=[2,1], maxval=3, dtype=tf.int32) )
v = tf.Variable([[1], [2]])
module = MyModule(v)


#############################################
x = tf.constant( tf.random.uniform(shape=[3,1], maxval=3, dtype=tf.int32) )
v = tf.Variable([[1], [2], [3]])
module = MyModule(v)

tf.saved_model.save(module, "module")     

imported = tf.saved_model.load("module")

x = tf.constant([80,0,20,24,321])
v = tf.Variable(3*tf.ones_like(x), trainable=False)

result = imported(x,v)
print(result)                                                       

The output is this: tf.Tensor([240 0 60 72 963], shape=(5,), dtype=int32)

My question is the following: Given that the graph has been saved, why the value of the variable self.v can still be changed. Isn't is supposed to be frozen.