Sean_Moriarity:

model.predict(tf.constant([1.0])) # model.predict_function is only populated after 1 call to predict, you can also do the same thing with model.train_function

graph = model.predict_function.get_concrete_function(iter([tf.constant([1.0])])).graph # The concrete function takes an iterator
isinstance(graph, tf.Graph) # True

graph.get_operations()



Thanks for the reply! I’m actually looking for the operators that are called during training (not inference) of the model: during backpropagation as well.