Welcome to Umlaut
=================

What is Umlaut?
----------------
Umlaut is an end-to-end machine learning benchmarking tool for Python, designed to be applicable in every step of a machine learning pipeline.
It includes a Python package that contains functions and classes for measuring metrics of the system and model.
The collected measurement values can be visualised and compared using a CLI included in the package.

What can be measured using Umlaut?
-----------------------------------
Using Umlaut, you can collect and visualise the following metrics:

* CPU usage
* Memory consumption
* Power consumption
* Runtime
* Throughput
* Latency
* Time-To-Accuracy
* Loss
* Confusion Matrix

How do I use it?
----------------
We have prepared an :doc:`example </example_umlaut>` that will guide you through the usage of our tool.
We also recommend you have a look at the :doc:`module reference </moduleref>`.



What's with the name?
---------------------
Umlaut stands for Universal Machine Learning Analysis Utility.

Who developed it?
-----------------
Umlaut was developed by Christian Jacob, Jost Morgenstern, Willi Rieck and Jonas Schulze as part of their bachelor project at `HPIDES <https://hpides.github.io/>`_.

.. toctree::
   :hidden:

   Example usage <example_umlaut>
   Module reference <moduleref>