Keras Attention Layer CI workflow (philipperemy/keras-attention)

The Keras Attention Layer CI workflow from philipperemy/keras-attention, explained and optimized by Latchkey.

What it does

This is the Keras Attention Layer CI workflow from the philipperemy/keras-attention repository, a real project running GitHub Actions. It is shown here with attribution under its Apache-2.0 license.

Below, Latchkey shows a faster, safer version produced by its optimization engine.

The workflow

name: Keras Attention Layer CI

on: [ push, pull_request ]

jobs:
  build:

    runs-on: ubuntu-latest
    strategy:
      max-parallel: 4
      matrix:
        python-version: [ "3.9", "3.10" ]

    steps:
      - uses: actions/checkout@v3
      - name: Set up Python ${{ matrix.python-version }}
        uses: actions/setup-python@v3
        with:
          python-version: ${{ matrix.python-version }}
      - name: Install dependencies and package
        run: |
          python -m pip install --upgrade pip
          pip install flake8 pylint tox
      - name: Static Analysis
        run: |
          flake8 . --ignore E402 --count --max-complexity 10 --max-line-length 127 --select=E9,F63,F7,F82 --show-source --statistics
      - name: Run example
        run: |
          tox

The same workflow, on Latchkey

Estimated ~20% faster on cache hits, plus fewer wasted runs and a safer supply chain. Added and changed lines are highlighted.

name: Keras Attention Layer CI
 
on: [ push, pull_request ]
 
concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true
 
jobs:
  build:
    timeout-minutes: 30
 
    runs-on: latchkey-small
    strategy:
      max-parallel: 4
      matrix:
        python-version: [ "3.9", "3.10" ]
 
    steps:
      - uses: actions/checkout@v3
      - name: Set up Python ${{ matrix.python-version }}
        uses: actions/setup-python@v3
        with:
          cache: 'pip'
          python-version: ${{ matrix.python-version }}
      - name: Install dependencies and package
        run: |
          python -m pip install --upgrade pip
          pip install flake8 pylint tox
      - name: Static Analysis
        run: |
          flake8 . --ignore E402 --count --max-complexity 10 --max-line-length 127 --select=E9,F63,F7,F82 --show-source --statistics
      - name: Run example
        run: |
          tox
 

What changed

• Run on Latchkey managed runners with one line (runs-on), which apply the fixes below automatically and self-heal transient failures. This example uses latchkey-small; pick the runner size that fits the job.
• Cancel superseded runs when a branch or PR gets a newer push.
• Cache dependency installs on the setup step so they are served from cache.
• Add a job timeout so a hung step cannot burn hours of runner time.

What Latchkey heals here

This workflow has steps that commonly fail on transient issues (network, registries, flaky browsers). On Latchkey managed runners they are detected, retried, and self-healed instead of failing your build:

• Dependency installs

This workflow runs 1 job (2 with the matrix expanded) per trigger. On Latchkey the same minutes cost up to 58% less than GitHub-hosted, with zero queue time.

Actions used in this workflow