Tune Hyperparameter in sklearn with ray

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I wonder but could not found any information why this appears all the time if I try to tune hyperparameter from sklearn with TuneSearchCV:

Note that the important part is the Log sync warning and as a result that the logging in combination with tensorflow and search_optimization such as optuna does not work:

Backend is sklearn
Concatenating h5 datasets of the following files: 
('output/example_train_1.h5', 'output/example_train_2.h5') 
based on the following keys: 
('x', 'y')
Concatenation successful, resulting shapes for the given dsets:
Key: x, shape: (20000, 25)
Key: y, shape: (20000,)
Log sync requires rsync to be installed.

Process finished with exit code 0

The tuning processes seem to be working, as long as I do not use search-optimization such as optional. I use it within a docker container. I got through the ray-documentation, but I could find the source where I think the error drops. However, I could not find any settings or additional options on how to prevent it.

Furthermore, it seems that rsync is just necessary if I use a cluster. But actually, I don't do that right now.

ray scikit-learn
1 Answers

The warning (Log sync requires rsync to be installed.) does not stop the script from executing. If rsync is not installed, it will just not synchronize logs between nodes, which seems to be unnecessary in your case anyway. You shouldn't run into any problem there.

It's hard to say what the problem here is, as we're missing crucial information: Which version of Ray are you running, which version of tune-sklearn, and how does your training script look like?

If you're running into problems and you suspect it is a bug, please consider opening an issue in the tune-sklearn repository, and make sure to include the above information and preferably a minimal reproducible script so the maintainers can look into this.

user_152626410
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