What about:
import tensorflow as tf

model = tf.keras.models.Sequential([
  tf.keras.layers.Dense(2, activation='softmax', input_shape=(1,))
])

model.compile(optimizer='rmsprop', loss='categorical_crossentropy')

xs = tf.constant([[1.0]])
ys = tf.constant([[0.2, 0.8]])

model.train_on_batch(xs, ys)

graph = model.train_function.get_concrete_function(iter([(xs, ys)])).graph # The concrete function takes an iterator
isinstance(graph, tf.Graph) # True

graph.get_operations()

This will list the operations performed during a single compiled training step. If you want to export that to a readable format you can do graph.as_graph_def().