Implement/document TB debugging with tf.keras model.fit

Currently (in TF 2.0.0 and TF 2.1.0 and tf-nightly/tb-nightly) the /#debugger view shows this snippet for “Keras Model”:

import tensorflow as tf
from tensorflow.python import debug as tf_debug
import keras

keras.backend.set_session(
    tf_debug.TensorBoardDebugWrapperSession(tf.Session(), "ip-a-b-c-d:6064"))
# Define your keras model, called "model".
model.fit(...)

But I’m using tf.keras. So I tried the above with from tensorflow import keras instead of import keras, and that fails (in TF 2.0.0 and TF 2.1.0 and tf-nightly) with:

AttributeError: module 'tensorflow.python.keras.api._v2.keras.backend' has no attribute 'set_session'

Looks like set_session was marked compat.v1 already in Tensorflow 2.0.0: https://github.com/tensorflow/tensorflow/commit/86ac0d0a377d5b89a97c9c468a31b6506c9a7209

So I didn’t find any instructions anywhere for using the Tensorboard debugger view with a tf.keras model.fit scenario in Tensorflow 2.0.0 up.

Is that not implemented at all, or the setup just not documented?

[rantav]

I too see similar (bogus) behavior as @gthb describes, usingTensorFlow version: 2.1.0

[bazhenov]

I’m facing the same issue in TF/2.2.0. Tensorflow doesn’t even try to connect to Tensorboard debugger plugin.