ML-Dash, A Beautiful Visualization Dashboard for ML
|Downloads|
For detailed codumentation,
see\ ml-dash-tutorial <https://ml-logger.readthedocs.io/en/latest/setting_up.html#ml-dash-tutorial>
__
ML-dash replaces visdom and tensorboard. It allows you to see real-time
updates, review 1000+ of experiments quickly, and dive in-depth into
individual experiments with minimum mental effort.
- Parallel Coordinates
- Aggregating Over Multiple Runs (with different seeds)
- Preview Videos,
matplotlib
figures, and images.
Usage
To make sure you install the newest version of ml_dash
:
.. code-block:: bash
conda install pycurl
pip install ml-logger ml-dash --upgrade --no-cache
Just doing this would not work. The landscape of python modules is a lot
messier than that of javascript. The most up-to-date graphene requires
the following versioned dependencies:
.. code-block:: bash
yes | pip install graphene==2.1.3
yes | pip install graphql-core==2.1
yes | pip install graphql-relay==0.4.5
yes | pip install graphql-server-core==1.1.1
There are two servers:
-
a server that serves the static web-application files ml_dash.app
This is just a static server that serves the web application client.
To run this:
.. code-block:: bash
python -m ml_dash.app
-
the visualization backend ml_dash.server
This server usually lives on your logging server. It offers a
graphQL
API backend for the dashboard client.
.. code-block:: bash
python -m ml_dash.server --logdir=my/folder
Note: the server accepts requests from localhost
only by
default for safety reasons. To overwrite this, see the
documentation here:
ml-dash-tutorial <https://ml-logger.readthedocs.io/en/latest/setting_up.html#ml-dash-tutorial>
__
Implementation Notes
See `https://github.com/episodeyang/ml_logger/tree/master/ml-dash-server/notes/README.md <https://github.com/episodeyang/ml_logger/tree/master/ml-dash-server/notes/README.md>`__
.. |Downloads| image:: http://pepy.tech/badge/ml-dash
:target: http://pepy.tech/project/ml-dash