pytorchlab/pytorch Docker Image

pytorchlab/pytorch

Minimal, production-ready PyTorch base images for GPU and CPU workloads — with optional pre-bundled YOLO weights for offline inference.

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Overview

pytorchlab/pytorch provides slim, multi-variant Docker images on top of the official https://hub.docker.com/r/pytorch/pytorch base. Each image adds only what is needed for real-world deployments:

• System libraries required by OpenCV (libGL, libglib2.0, libpq, libgeos)
• Clean layer — __pycache__ removed at build time to minimize image size
• YOLO variants — pre-downloaded Ultralytics weights bundled inside the image so that ECS/Kubernetes workers have zero outbound dependency at runtime

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Available Tags

GPU (CUDA 12.6 + cuDNN 9)

Built from pytorch/pytorch:2.9.1-cuda12.6-cudnn9-runtime. Requires NVIDIA drivers compatible with CUDA 12.6+.

CPU (Python 3.11 Slim)

Built from python:3.11-slim with CPU-only PyTorch (~1.5 GB lighter than the CUDA variant).

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Quick Start

bash
# GPU — verify CUDA is available
docker pull pytorchlab/pytorch:2.9.1-cuda12.6-cudnn9-runtime
docker run --gpus all --rm pytorchlab/pytorch:2.9.1-cuda12.6-cudnn9-runtime \
  python -c "import torch; print('CUDA:', torch.cuda.is_available())"

# CPU — lightweight inference
docker pull pytorchlab/pytorch:2.4.1-cpu-py3.11-slim
docker run --rm pytorchlab/pytorch:2.4.1-cpu-py3.11-slim \
  python -c "import torch; print('PyTorch:', torch.__version__)"

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Use as a Base Image

GPU workload

dockerfile
FROM pytorchlab/pytorch:2.9.1-cuda12.6-cudnn9-runtime

WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY . .
CMD ["python", "train.py"]

CPU workload / lightweight inference

dockerfile
FROM pytorchlab/pytorch:2.4.1-cpu-py3.11-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY . .
CMD ["python", "inference.py"]

Offline YOLO inference (no internet required at runtime)

dockerfile
FROM pytorchlab/pytorch:2.9.1-cuda12.6-cudnn9-yolo26m

# Weights are pre-downloaded at /app/weights/yolo26m.pt & yolo26n.pt
# YOLO_OFFLINE=1 and YOLO_CONFIG_DIR=/app/weights are already set
WORKDIR /app
COPY . .
CMD ["python", "detect.py"]

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Requirements

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Environment Variables (pre-set in YOLO variants)

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License

• Image build scripts: MIT License
• PyTorch: https://github.com/pytorch/pytorch/blob/main/LICENSE
• Ultralytics YOLO (weights in YOLO variants): https://github.com/ultralytics/ultralytics/blob/main/LICENSE

Note: The YOLO weight files bundled in the YOLO-variant images are subject to the Ultralytics AGPL-3.0 license. Ensure your use case complies with this license.