Learning LabGraph online.
LabGraph is a a Python-first framework used to build sophisticated research systems with real-time streaming, graph API, and parallelism. Facebook Researchers use it prototype wearable hardware systems and process digital signals under their VR/AR efforts into the Metaverse.
To put it simply, LabGraph sets the relationship between the inputs and outputs of computations and provides the needed tooling to run them in parallel to help developers focus on algorithms instead of the environment.
As MLH Fellows who have not used LabGraph before, we had a hard time understanding its purpose, how to set it up correctly, and what to expect from the library. So we decided to help future MLH Fellows get up to speed both on concepts and usage with an interactive tool.
We built the interactive tool to let users get the taste of LabGraph with zero commitments. The interactive terminal lets the users run simulations we prepared with different numbers of features and see their expected outputs.
help
into the terminalTo run LabGraph simulations on your machine, follow steps listed below:
pip install labgraph
to install LabGraph along with its dependecieispython setup.py install
to work with the simulation we prepared and listed under random_labgraph/simulation.py
python random_labgraph/simulation.py 100
to get a graph produced with LabGraph's node in real-timeThis project is served unded the MIT License.
MIT License
Copyright (c) 2022 MLH Fellowship
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Author: MLH-Fellowship
Source: https://github.com/MLH-Fellowship/labgraph-interactive
License: MIT license