Skip to content
Latchkey
Start Free

Check-Trained-Agents workflow (DLR-RM/rl-baselines3-zoo)

The Check-Trained-Agents workflow from DLR-RM/rl-baselines3-zoo, explained and optimized by Latchkey.

D

CI health: D - needs work

Point runs-on at Latchkey and get caching, run de-duplication, job timeouts, self-healing for flaky steps, and up to 58% lower cost, applied automatically.

Grade your own workflow free or run it on Latchkey →
Source: DLR-RM/rl-baselines3-zoo.github/workflows/trained_agents.ymlLicense MITView source

What it does

This is the Check-Trained-Agents workflow from the DLR-RM/rl-baselines3-zoo repository, a real project running GitHub Actions. It is shown here with attribution under its MIT license.

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

The workflow

workflow (.yml)
# This workflow will install Python dependencies, run check on trained agents
# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions

name: Check-Trained-Agents

on:
  push:
    branches: [master]
  pull_request:
    branches: [master]

jobs:
  build:
    env:
      TERM: xterm-256color
      FORCE_COLOR: 1
      HF_TOKEN: ${{ secrets.HF_TOKEN }}
    # Skip CI if [ci skip] in the commit message
    if: "! contains(toJSON(github.event.commits.*.message), '[ci skip]')"
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: ["3.10", "3.11", "3.12", "3.13"]
        include:
          # Default version
          - gymnasium-version: "1.0.0"
          # Add a new config to test gym<1.0
          - python-version: "3.10"
            gymnasium-version: "0.29.1"
    steps:
      - uses: actions/checkout@v6
        with:
          submodules: true
      - name: Set up Python ${{ matrix.python-version }}
        uses: actions/setup-python@v6
        with:
          python-version: ${{ matrix.python-version }}
      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip

          # Use uv for faster downloads
          pip install uv
          # cpu version of pytorch
          # See https://github.com/astral-sh/uv/issues/1497
          # Need Pytorch 2.9+ for Python 3.13
          uv pip install --system torch==2.9.1+cpu --index https://download.pytorch.org/whl/cpu
          # Install full requirements (for additional envs and test tools)
          uv pip install --system -r requirements.txt
          # Use headless version
          uv pip install --system opencv-python-headless
          uv pip install --system -e .[plots,tests]

      - name: Install specific version of gym
        run: |
          uv pip install --system gymnasium==${{ matrix.gymnasium-version }}
          uv pip install --system "numpy<2"
          uv pip install --system "ale-py==0.10.1"
        # Only run for python 3.10, downgrade gym to 0.29.1
        if: matrix.gymnasium-version != '1.0.0'

      - name: Check trained agents
        run: |
          make check-trained-agents

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.

# This workflow will install Python dependencies, run check on trained agents
# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
 
name: Check-Trained-Agents
 
on:
  push:
    branches: [master]
  pull_request:
    branches: [master]
 
concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true
 
jobs:
  build:
    timeout-minutes: 30
    env:
      TERM: xterm-256color
      FORCE_COLOR: 1
      HF_TOKEN: ${{ secrets.HF_TOKEN }}
    # Skip CI if [ci skip] in the commit message
    if: "! contains(toJSON(github.event.commits.*.message), '[ci skip]')"
    runs-on: latchkey-small
    strategy:
      matrix:
        python-version: ["3.10", "3.11", "3.12", "3.13"]
        include:
          # Default version
          - gymnasium-version: "1.0.0"
          # Add a new config to test gym<1.0
          - python-version: "3.10"
            gymnasium-version: "0.29.1"
    steps:
      - uses: actions/checkout@v6
        with:
          submodules: true
      - name: Set up Python ${{ matrix.python-version }}
        uses: actions/setup-python@v6
        with:
          cache: 'pip'
          python-version: ${{ matrix.python-version }}
      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip
 
          # Use uv for faster downloads
          pip install uv
          # cpu version of pytorch
          # See https://github.com/astral-sh/uv/issues/1497
          # Need Pytorch 2.9+ for Python 3.13
          uv pip install --system torch==2.9.1+cpu --index https://download.pytorch.org/whl/cpu
          # Install full requirements (for additional envs and test tools)
          uv pip install --system -r requirements.txt
          # Use headless version
          uv pip install --system opencv-python-headless
          uv pip install --system -e .[plots,tests]
 
      - name: Install specific version of gym
        run: |
          uv pip install --system gymnasium==${{ matrix.gymnasium-version }}
          uv pip install --system "numpy<2"
          uv pip install --system "ale-py==0.10.1"
        # Only run for python 3.10, downgrade gym to 0.29.1
        if: matrix.gymnasium-version != '1.0.0'
 
      - name: Check trained agents
        run: |
          make check-trained-agents

What changed

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:

This workflow runs 1 job (4 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

actions/checkout actions/setup-python