Manage your machine learning experiments.
trixi is a tool to help you configure, visualize and log your experiments in a reproducible fashion.

• Features
• Installation
• Docs
• Examples

Trixi consists of three parts:

• Logging API
  Log what ever data you like in what ever way you like to whatever backend you like.

• Experiment Infrastructure
  Standardize your experiment, let them the framework do all the inconvenient stuff, and simple start, resume, change, finetune and compare all your experiments.

• Experiment Browser
  Compare, Combine and visually inspect the results of your Experiments.

An detailed implementation overview is given here.

The Logging-Api provides a standardized way for logging results to different backends. The logging api supports (among others):

• Values
• Text
• Plots (Bar, Line, Scatter, Piechart, ...)
• Images (Single, as grid)

And offers different Backends, e.g. :

• Visdom (visdom-loggers)
• Matplotlib / Seaborn (plt-loggers)
• Local Disk (file-loggers)
• Telegram (message-loggers)

And an Experiment-logger for logging your experiments, which automatically creates a structured directory and allows storing of config, results, plots, dict, array, images, ...

Here are some examples:

• Visdom:
  

• Files:
  

• Telegram:
  

The Experiment Infrastructure provides a unified way to configure, run, store and evaluate your results. It provides you an Experiment-Interface, for which you can implement the training, validation and testing. Furthermore it automatically provides you with easy access to the Logging API and stores your config es well as the results for easy evaluation and reproduction of different experiments.

For more info, visit the Documentation.

The Experiment Browser offers a complete overview of experiments along with all config parameters and results. It also allows to combine and/or compare different experiments. It also gives an interactive comparison highlighting differences in the configs and a detailed view of all images, plots, results and logs of each experiment, with live plots and more.

Install Trixi:

pip install trixi

Or to always get the newest version you can install trixi directly via git:

git clone https://github.com/MIC-DKFZ/trixi.git
cd trixi
pip install -e .

The docs can be found here: trixi.rtfd.io

Or you can build your own docs using Sphinx.

Install Sphinx: pip install sphinx

Generate Api-docs: path/to/PROJECT/doc$ sphinx-apidoc -f -o . ..

Open index.html: firefox path/to/PROJECT/doc/_build/html/index.html

• rerun make html each time existing modules are updated
• DO NOT forget indent or blank lines
• Code with no classes or functions is not automatically captured using apidoc

This follows the Google style docstring guidelines:

def show_image(self, image, name, file_format=".png", **kwargs):
    """
    This function shows an image.

    Args:
        image(np.ndarray): image to be shown
        name(str): image title
    """

Examples can be found here for:

• Visdom-Logger
• Experiment-Logger
• Experiment Infrastructure (with a simple MNIST Experiment example and resuming and comparison of different hyper parameters)