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SLSA for ML models example #4

SLSA for ML models example

SLSA for ML models example #4

Workflow file for this run

name: SLSA for ML models example
on:
workflow_dispatch:
inputs:
model_type:
description: Name of the model (implies framework)
required: true
type: choice
options:
- tensorflow_model.keras
- tensorflow_hdf5_model.h5
- tensorflow_hdf5.weights.h5
- pytorch_model.pth
- pytorch_full_model.pth
- pytorch_jitted_model.pt
permissions: read-all
defaults:
run:
shell: bash
jobs:
train:
name: Train model and save as ${{ github.event.inputs.model_type }}
runs-on: ubuntu-latest
outputs:
hash: ${{ steps.hash.outputs.hash }}
steps:
- uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
- uses: actions/setup-python@0a5c61591373683505ea898e09a3ea4f39ef2b9c # v5.0.0
with:
python-version: 3.11
cache: pip
cache-dependency-path: slsa_for_models/install/requirements_${{ runner.os }}.txt
- name: Install dependencies
run: |
set -euo pipefail
bash .github/workflows/scripts/venv_setup.sh
python -m pip install --require-hashes -r slsa_for_models/install/requirements_${{ runner.os }}.txt
- name: Build model
env:
MODEL_TYPE: ${{ github.event.inputs.model_type }}
run: |
set -euo pipefail
bash .github/workflows/scripts/venv_activate.sh
python slsa_for_models/main.py "$MODEL_TYPE"
- uses: actions/upload-artifact@c7d193f32edcb7bfad88892161225aeda64e9392 # v4.0.0
with:
path: ${{ github.event.inputs.model_type }}
name: ${{ github.event.inputs.model_type }}
if-no-files-found: error
- id: hash
env:
MODEL: ${{ github.event.inputs.model_type }}
run: |
set -euo pipefail
sha256sum "$MODEL" > checksum
echo "hash=$(cat checksum | base64 -w0)" >> "${GITHUB_OUTPUT}"
provenance:
needs: [train]
permissions:
actions: read
id-token: write
contents: write
uses: slsa-framework/slsa-github-generator/.github/workflows/generator_generic_slsa3.yml@v1.9.0
with:
base64-subjects: "${{ needs.train.outputs.hash }}"
upload-assets: true # NOTE: This does nothing unless 'upload-tag-name' parameter is also set to an existing tag