How can Tensorboard files be merged/combined or appended?

Question

If I have multiple Tensorboard files, how can they be combined into a single Tensorboard file?

Say in keras the following model.fit() was called multiple times for a single model, for example in a typical GAN implementation:

for i in range(num_epochs):
    model.fit(epochs=1, callbacks=Tensorboard())

This will produce a new Tensorboard file each time, which is not useful. Not sure if there is way to have Tensorboard append, or not produce unique time-stamped files each callback call.

Answer 1

It seems in tensorboard 2.3, you can access the tensorboard file's logged data and load it into a pandas dataframe. This tutorial outlines the approach:

https://www.tensorflow.org/tensorboard/dataframe_api

At the time of writing, I couldn't find a tensorboard version 2.3, but the module the tutorial relies upon - tensorboard.data.experimental.ExperimentFromDev() - seems to be present in tensorboard 2.2: https://github.com/tensorflow/tensorboard/blob/master/tensorboard/data/experimental/experiment_from_dev.py#L71

You could load existing data from several tensorboard files into dataframes and then combine those dataframes in the desired manner to write the combined dataframe to a new tensorboard file. I had considered this approach to address the problem of having multiple tensorboard files for different training runs but haven't tried it yet in my project.