Tensorflow Adam Optimizer state not updating ( get_config ) - tensorflow

Question

I am using optimizer.get_config() to get the final state of my adam optimizer (as in https://stackoverflow.com/a/60077159/607528) however .get_config() is returning the initial state. I assume this means one of the following
.get_config() is supposed to return the initial state
my optimizer is not updating because I've set something up wrong
my optimizer is not updating tf's adam is broken (highly unlikely)
my optimizer is updating but is being reset somewhere before I call .get_config()
something else?
Of course I originally noticed the issue in a proper project with training and validation sets etc, but here is a really simple snippet that seems to reproduce the issue:
import tensorflow as tf
import numpy as np
x=np.random.rand(100)
y=(x*3).round()
model = tf.keras.models.Sequential([
tf.keras.layers.Dense(128, activation='relu'),
tf.keras.layers.Dense(10, activation='softmax')
])
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
model.fit(x, y, epochs=500)
model.evaluate(x, y)
model.optimizer.get_config()

Answer 1

If you want to restore your training - you should save optimizer weights, not config:
weight_values = optimizer.get_weights()
with open(self.output_path+'optimizer.pkl', 'wb') as f:
pickle.dump(weight_values, f)
And then load them:
model.fit(dummy_x, dummy_y, epochs=500) # build optimizer by fitting model with dummy input - e.g. random tensors with simpliest shape
with open(self.path_to_saved_model+'optimizer.pkl', 'rb') as f:
weight_values = pickle.load(f)
optimizer.set_weights(weight_values)