Tensorflow 2.0 custom_scalar plugin for tensorboard

To set layout for custom_layout plugin in tensorflow 1.x you should use method add_summary in FileWriter class. So the code should look like this:

with tf.summary.FileWriter(LOGDIR) as writer:
   layout_summary = summary_lib.custom_scalar_pb(...)
   writer.add_summary(layout_summary)

In tensorflow 2 add_summary method was removed. How can I set custom_scalar layout now? Is it a bug or a desired API change?

[dcbr]

I managed to make the custom_scalar plugin work in TF2.3 as follows:

import tensorflow as tf
from tensorboard.plugins.custom_scalar import layout_pb2
from tensorboard.plugins.custom_scalar.summary import pb as custom_scalar_pb

writer = tf.summary.create_file_writer(LOGDIR)
layout = custom_scalar_pb(layout_pb2.Layout(...))
with writer.as_default():
    tensor = tf.constant(tf.make_ndarray(layout.value[0].tensor))
    tf.summary.write(layout.value[0].tag, tensor, step=0, metadata=layout.value[0].metadata)

It would however be nice to have native TF2 support for this, allowing us to write something along the lines tf.summary.custom_scalar(layout).

[nfelt]

This is still an open issue; I’ve transferred it to the TensorBoard repository since that’s a better place to track it, since if we were to add a TF 2.0 native summary op for custom scalars, it would be defined in TensorBoard’s codebase.

Right now, we haven’t worked on the custom scalars dashboard in quite a while due to low usage and a general desire to approach this kind of feature differently (allowing UI-driven configuration rather than requiring the layout to be hardcoded in the written summaries).

At this point, I’d recommend using the workaround from https://github.com/tensorflow/tensorboard/issues/5343#issuecomment-749066283. (There is also the tf.summary.experimental.write_raw_pb() approach used in the updated demo code as of https://github.com/tensorflow/tensorboard/pull/5011, if you have a serialized version of the v1 summary proto.)