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https://github.com/peckjon/coreml_ghactions

Train and Run Apple CoreML Models using GitHub Actions
https://github.com/peckjon/coreml_ghactions

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Train and Run Apple CoreML Models using GitHub Actions

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## Training and Running CoreML Models using GitHub Actions



Apple's [CoreML](https://developer.apple.com/documentation/coreml) provides a way to run model predictions on iOS and OSX. Some parts of the libarary, such as the [model conversion tools](https://developer.apple.com/documentation/coreml/converting_trained_models_to_core_ml), can be run on non-Apple platforms, but the [prediction methods](https://developer.apple.com/documentation/coreml/mlmodel#2880473) will fail unless run on an iPhone (iOS) or Mac (OSX). This can present a problem for datascientists and developers without access to an Apple device.



Fortunately, [GitHub Actions](https://github.com/features/actions) provides macOS as a [virtual machine type](https://help.github.com/en/articles/workflow-syntax-for-github-actions#jobsjob_idruns-on) for running jobs. This makes it possible for developers to run CoreML predictions from inside a GitHub Actions workflow.



#### Training the model



First, we'll train an extremely simple [sklearn](https://scikit-learn.org/stable/) model and export it to CoreML: see [train.py](train.py) for details, or clone this repository and run:



```bash

pip install -r requirements.txt

python train.py 

```



This ingests known square footage and listing prices of some Seattle-area homes from [prices.csv](prices.csv), fits a linear regression, and exports [pricing.mlmodel](pricing.mlmodel).



#### Running a prediction



On iOS or OSX only, we can run [predict.py](predict.py), which ingests a list of square-footage values from [input.csv](input.csv) and uses [pricing.mlmodel](pricing.mlmodel) to generate and save a list of predicted prices as [output.csv](output.csv).



```bash

pip install coremltools

python predict.py

```



#### Setting up GitHub Actions



We can now [configure a sequence of actions](https://developer.github.com/actions/creating-github-actions/) to be triggered when specific files are pushed to our repository. We'll set up two separate workflows, both stored in [/.github/workflows](/.github/workflows):



- [train.yml](/.github/workflows/train.yml) will be executed whenever prices.csv or train.py changes, and will run train.py to generate a new pricing.mlmodel



- [predict.yml](/.github/workflows/predict.yml) will be executed whenever input.csv, predict.py, or pricing.mlmodel changes. It will run predict.py to generate a new output.csv



In addition, either job will be run if the job configuration file itself is changed, e.g.: 



```bash

on: 

  push:

    paths:

    - .github/workflows/predict.yml

    - input.csv

    - predict.py

    - pricing.mlmodel

```



Let's examine each section of the jobs/build section of predict.yml to better understand what's going on:



```bash

runs-on: macOS-latest

strategy:

  max-parallel: 1

  matrix:

    python-version: [3.6]

```



Here, we specify that this job will run in the latest OSX container, with Python 3.6 installed.



```bash

steps:

- uses: actions/checkout@v1

- name: Set up Python ${{ matrix.python-version }}

  uses: actions/setup-python@v1

  with:

    python-version: ${{ matrix.python-version }}

```



Our first steps check out the current repo and set up the specified Python.



```bash

- name: Install dependencies

  run: |

    python -m pip install --upgrade pip

    pip install coremltools

- name: Run predictions

  run: python predict.py

```



Next, we install our dependencies and run the prediction script.



```bash

- name: Commit changed output

  env:

    GITHUB_ACTOR: ${{ secrets.GITHUB_ACTOR }}

    GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

    GITHUB_REPOSITORY: ${{ secrets.GITHUB_REPOSITORY }}

  run: |

    git remote set-url origin "https://$GITHUB_ACTOR:[email protected]/$GITHUB_REPOSITORY.git"

    git commit -m "updated predictions" output.csv

    git push origin HEAD:master

```



Lastly, we commit our changed file(s) back to the repo. This requires some backflips using [runtime variables](https://developer.github.com/actions/creating-github-actions/accessing-the-runtime-environment/), as our code inside the workflow has been automatically checked out on a [detached branch](http://marklodato.github.io/visual-git-guide/index-en.html#detached).



#### Try it yourself



Read more about [GitHub actions](https://github.com/features/actions), then clone this repository and commit a change to the input.csv file. Click the "Actions" tab at the top of your repo to examine the run, then check to see if output.csv has changed.



Enjoy!