Tensorflow version vs tensorboard version

Question

I would like to ask if tensorflow version could be different than tensorboard's one?

I have a problem (404 problem) and someone suggested installing a newer version of tensorboard using:

pip uninstall tensorflow-tensorboard
pip install tensorboard

I checked my versions and they are both 1.6.0:

from tensorboard import version; print(version.VERSION)
import tensorflow as tf; print(tf.__version__)

1.6.0

Also since I don't remember installing tensorboard separately (I might be mistaken about this one though) I guess it's expected to be on the same version.

So, my question is could they be on different versions? (I guess they could since we have the opportunity to install tensorboard separately). And also is there a point in upgrading one and not the other? Could there be some conflicts in the latter case?

Solution

Since TensorFlow 1.3.0, TensorBoard has had its own PyPI package, but there is a circular dependency between the packages, so when users installs TensorFlow they will always get TensorBoard along (that's why you have it installed). However, the fact is that TensorFlow does really not depend on TensorBoard to work and TensorBoard does not even have a dependency to TensorFlow, so it should not be possible that the two packages affect each other in any way.

About the suggested fix, it tells you to remove tensorflow-tensorboard and then install tensorboard. This fixes a known issue from 1.6.0 due to renaming the TensorBoard package from tensorflow-tensorboard to tensorboard, which caused troubles in some cases. In the GitHub link you posted, the developer suggests to upgrade TensorBoard from 1.5.1 to 1.6.0 to fix one particular issue, hence the need to remove the package with the old name and install the new one. Since you already have TensorBoard 1.6.0, you should most definitely have tensorboard installed, not tensorflow-tensorboard (you can check with pip list if you want). To upgrade to a newer version, you can just run:

pip install --upgrade tensorboard

Comments

[wenxi]

"TensorFlow does not depend on TensorBoard to work". However, if in your code, there are tf.summary.scalar or similar logging ops, you might got error without a TensorBoard installation.