stable-baselines3 Docker & Self-Hosted Deployment

GitHub

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

13,953 stars Python Python 47 files · ~80,488 tokens #baselines#gsde#gym#machine-learning#openai#python#pytorch#reinforcement-learning
1. Pull Image (DOCKERHUB) docker pull DLR-RM/stable-baselines3:latest
2. Docker Run (1-Click Launch) docker run -d --name stable-baselines3 --restart always dlr-rm/stable-baselines3:latest
3. Podman Run podman run -d --name stable-baselines3 --restart always dlr-rm/stable-baselines3:latest
4. Skopeo Inspect (Zero-Pull Manifest) skopeo inspect docker://docker.io/dlr-rm/stable-baselines3:latest
5. ORAS Pull (OCI Artifact) oras pull dlr-rm/stable-baselines3:latest
Dockerfile 
ARG PARENT_IMAGE=mambaorg/micromamba:2.0-ubuntu24.04
FROM $PARENT_IMAGE
ARG PYTORCH_DEPS=https://download.pytorch.org/whl/cpu
ARG PYTHON_VERSION=3.12
ARG MAMBA_DOCKERFILE_ACTIVATE=1  # (otherwise python will not be found)

# Install micromamba env and dependencies
RUN micromamba install -n base -y python=$PYTHON_VERSION && \
    micromamba clean --all --yes

ENV CODE_DIR=/home/$MAMBA_USER

# Copy setup file only to install dependencies
COPY --chown=$MAMBA_USER:$MAMBA_USER ./setup.py ${CODE_DIR}/stable-baselines3/setup.py
COPY --chown=$MAMBA_USER:$MAMBA_USER ./stable_baselines3/version.txt ${CODE_DIR}/stable-baselines3/stable_baselines3/version.txt

RUN cd ${CODE_DIR}/stable-baselines3 && \
    pip install uv && \
    uv pip install --system torch --default-index ${PYTORCH_DEPS} && \
    uv pip install --system -e .[extra,tests,docs] && \
    # Use headless version for docker
    uv pip uninstall --system opencv-python && \
    uv pip install --system opencv-python-headless && \
    pip cache purge && \
    uv cache clean

CMD /bin/bash