Applying callbacks in a custom training loop in Tensorflow 2.0

Question

I\'m writing a custom training loop using the code provided in the Tensorflow DCGAN implementation guide. I wanted to add callbacks in the training loop. In Keras I know we

Answer 1

I think you would need to implement the functionality of the callback manually. It should not be too difficult. You could for instance have the "train_step" function return the losses and then implement functionality of callbacks such as early stopping in your "train" function. For callbacks such as learning rate schedule the function tf.keras.backend.set_value(generator_optimizer.lr,new_lr) would come in handy. Therefore the functionality of the callback would be implemented in your "train" function.