Skip to content
/ kleio Public
forked from Epistimio/kleio

Experiment management for machine learning

License

Notifications You must be signed in to change notification settings

bouthilx/kleio

 
 

Repository files navigation

Kleiṓ

Note that this is a prototype.

Functionalities are not well tested and interface is very likely to change.


Current PyPi Version Supported Python Versions BSD 3-clause license Documentation Status Codecov Report Travis tests

Kleiṓ is an experiment manager, a logging journal of all data describing your experiments.

Its purpose is to provide an automatic tool to log extensive environment information, including script's code version, system specification and script configuration. The logging journal can include statistics manually logged from within the user's script as well as artifacts and ressources.

It assumes the computation is entirely deterministic, and if not deterministic then one of the argument is a seed that makes it fully reproducible.

Features

As simple and as complex you want

  • Simple and natural
  • Minimal and non-intrusive client interface for logging
  • Database logging (currently powered by MongoDB)
  • Flexible configuration
  • Automatic detection of code or environment change on script resuming
  • Support branching experiments to avoid recomputation and minimize log journal size
  • Inuitive and flexible interface for retrieval and navigation of statistics

Installation

Install Kleiṓ (prototype) by running:

pip install git+https://github.com/epistimio/kleio.git@prototype

Getting started

Configuring the database

TODO

Executing a command

Suppose you would execute your command the following way

$ python myscript.py one_pos_arg --some arguments --and some more

To log your execution with Kleiṓ, you simply need to prepend the command kleio at the beginning of the commandline.

$ kleio python myscript.py one_pos_arg --some arguments --and some more
> trial reserved with id: <some-id-string>

You can resume the script by running the same command again or by specifing the id of the trial.

$ kleio run <some-id-string>

Since Kleiṓ is multiprocess safe, trying to execute the same command twice concurrently will raise an error.

$ kleio run <some-id-string>
> TODO: Error message

To allow resuming execution even though the code or the system changed, you can use the options --allow-code-change, --allow-env-change or --allow-any-change. In order to ensure full reproducibility, the trial will actually be branched. The timestamp of branching will be marked in the trial configuration, so that the change of code or environement can be tracked. Note that since the trial has been branched, the original one can still be resumed using the original code version in the original environement. This makes it possible to compare the effect of code change or environment change.

$ kleio run --allow-any-change python myscript.py one_pos_arg --some arguments --and some more

or

$ kleio run --allow-any-change <some-id-string>

Logging

Statistics

log_statistic(**kwargs)

The method is built such that it will turn whatever is passed to it into a dictionary. Note that you cannot log using positional attributes, you must use named attributes. This is because the log would be meaningless if we would provide unnamed values. Statistics can be retrieved from a trial and sorted with respect to any possible key in the log. Thanks to this, there is no specific timestamp field, and any key such as epoch`, iteration or loss could be used to sort statistics when analysing a trial.

from kleio.client.logger import kleio_logger

kleio_logger.log_statistic(some_time='some time', some_value='some value')
kleio_logger.log_statistic(some_time='some other time', some_value='some other value')

Note that a script using kleio_logger.log_statistic can be executed without kleio. In such case, the method will only print the logged statistics in terminal, without saving it in any database.

Artifacts

log_artifact(filename, artifact, **kwargs)

Artifacts are logged in a similar fashion as for statistics, with the slight difference that a filename and a file-like object must be passed. Any other named arguments are saved as metadata for the artifact. This metadata is particularly usefull when retrieving artifacts based on special keys, such as fetching 'weights' for epoch=10.

from kleio.client.logger import kleio_logger

kleio_logger.log_artifact('some_file_path', some_file_like_object,
                          some_time='some time', some_value='some other value')

Ressources

Ressources are not supported yet, but will have a very similar interface as for artifacts.

Reading

Cat

$ kleio cat <some-id-string>

Tail

$ kleio tail -f <some-id-string>

Info

$ kleio info <some-id-string>

PDB

$ kleio pdb <some-id-string>

List

$ kleio ls

Branching

$ kleio branch <some-id-string> --some new-argument-value --new argument

Note that positional arguments cannot be updated by Kleiṓ when branching.

$ kleio branch --timestamp epoch=10 <some-id-string>

Contribute or Ask

Do you have a question or issues? Do you want to report a bug or suggest a feature? Name it! Please contact us by opening an issue in our repository below:

Start by starring and forking our Github repo!

Thanks for the support!

License

The project is licensed under the BSD license.

About

Experiment management for machine learning

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%