Standards in Machine Learning Models

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Thierry Janssens

An introduction to the different standards on interchanging machine learning models.

Internet

Introduction to reusing
models across languages
Thierry Janssens
23/10/2018 1

Introduction to reusing
models across languages
Thierry Janssens
Blog: https://www.dataT.be
VISIONWORKS
part of

Machine
Learning
Models
Different algorithms & programming languages

Training a supervised model
software
hardware
train run

Languages
https://fossbytes.com/popular-top-
programming-languages-machine-learning-
data-science/ (2016)

What about .net?
× CNTK, now Microsoft Cognitive toolkit
× January 2017
× Linux and Windows 64bit
× Python & C#
× ONNX support (early 2018)
× Focus on NN
× Accord.net
× API
× Dec 2014
× C#
× C. R. Souza, http://accord-framework.net .
What did Microsoft do?

PMML
× First appearance in 1997 !
× Last update in 2014 – version 4.3
× XML-based
× Widely accepted
× Over 30 organisations support it
× http://dmg.org/pmml/products.html
× Producers <-> consumers !
× Similar standard = PFA
Predictive Model Markup Language

NNEF
× December 2017, version 1.0
× The Krhonos Group
× Open Specification
× Descriptive model and data
× Text based and detailed
× no native
support yet
× exporter in C++
on Github
Neural Network Exchange Format
10/04/2018

ONNX
× December, 2017 version 1.0
× Amazon, Facebook & Microsoft
× Many supporters are joining
× Descriptive, open format.
× ‘binary’ -> protobuf
× Python, C# and R
Open Neural Network eXchange

NNVM
• Amazon and University of Washingthon, first appearance
oct 2017
• Non descriptive
• A compiler that translates models to a ‘uniform’
underlying intermediate representation (IR code).
• For specific hardware (ARM, Nvidia)

A note on Brainscript
• Microsoft
• Is a declarative language to write models
• Part of CNTK
• Descriptive, but in a ‘binary’ format
• Future not clear…

Conclusion
 PMML for all models
× broad support in
different languages and
tools
× New version on its way
 ONNX & NNEF
× only for Neural Networks
× need the underlying
language to be NNEF or
ONNX aware
 NNEF
× More options in its
current form
× Backed by a lot of
companies, but…
× But no native support yet
 ONNX
× Focusses on ease of use
× Working version in Python
& R
× Active community

× Past year +/- 17.000 – 15/09/2018
Sep 2018

Questions?
Thierry Janssens@ordina.be
Blog: https://www.dataT.be
VISIONWORKS
part of

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