Keras + TensorFlow Realtime training chart

Question

I have the following code running inside a Jupyter notebook:

# Visualize training history
from keras.models import Sequential
from keras.layers import Dense
impo         


        

Answer 1

Keras comes with a callback for TensorBoard.

You can easily add this behaviour to your model and then just run tensorboard on top of the logging data.

callbacks = [TensorBoard(log_dir='./logs')]
result = model.fit(X, Y, ..., callbacks=callbacks)

And then on your shell:

tensorboard --logdir=/logs

If you need it in your notebook, you can also write your own callback to get metrics while training:

 class LogCallback(Callback):

    def on_epoch_end(self, epoch, logs=None):
        print(logs["train_accuracy"])

This would get the training accuracy at the end of the current epoch and print it. There's some good documentation around it on the official keras site.