modelstore examples

This directory contains examples of training models and storing them into a model store over different types of storage.

The Python script in examples-by-ml-model iterates over all of the supported ML frameworks and all of the supported storage types. For each pair, it trains a model, uploads it to storage, and then downloads/loads it back.

The bash script cli-examples has exaples of how to run python -m modelstore commands.

Pre-requisites

As with the main library, these scripts have been developed using pyenv and pyenv-virtualenv.

Set up - examples by ML model

Warning: the examples-by-ml-model virtual environment installs ALL of the machine learning frameworks that are supported by modelstore. In your own project, you will only need to install the machine learning frameworks that you need.

Start by cd'ing into the directory containing the example you want to run:

❯ cd examples-by-ml-model/

And then you can use this Makefile command that creates a new virtual environment and installs all of the requirements:

❯ make pyenv

Running all of the examples

After creating a virtual environment, you can run all of the examples using:

❯ make run

This will run all of the examples - you can expect it to take some time!

Running a specific example

Start by cd'ing into the directory containing the example you want to run:

❯ cd examples-by-ml-model/

After creating a virtual environment, you can run all of the examples using:

❯ python main.py --modelstore-in $backend --ml-framework $framework