When you're using tf.keras in TensorFlow 2.0, training your models with `fit` is one option, but you can also write a custom training loop. It takes about 10 lines.pic.twitter.com/Tn3NA4pZaf
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Is there a suggested way to incorporate callbacks in these custom training loops? I could only find this suggested way, which looks appropriate. https://groups.google.com/forum/#!topic/keras-users/IS-wBskAg0k …
That's correct, you can always call the callback methods manually at different stages of training (e.g. `on_epoch_begin`, `on_epoch_end`...)
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Thanks. Does this always require using callback.set_model(model). In some of my implementations I found that some of my models created using Model didn't have model.stop_training.
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