Prebuilt Docker images for inference
Prebuilt Docker container images for inference are used when deploying a model with Azure Machine Learning. The images are prebuilt with popular machine learning frameworks and Python packages. You can also extend the packages to add other packages by using one of the following methods:
Why should I use prebuilt images?
- Reduces model deployment latency
- Improves model deployment success rate
- Avoids unnecessary image build during model deployment
- Includes only the required dependencies and access right in the image/container
List of prebuilt Docker images for inference
Important
The list provided in the following table includes only the inference Docker images that Azure Machine Learning currently supports.
- All the Docker images run as non-root user.
- We recommend using the
latesttag for Docker images. Prebuilt Docker images for inference are published to the Microsoft container registry (MCR). For information on how to query the list of tags available, see the MCR GitHub repository. - If you want to use a specific tag for any inference Docker image, Azure Machine Learning supports tags that range from
latestto six months older thanlatest.
Inference minimal base images
| Framework version | CPU/GPU | Pre-installed packages | MCR Path |
|---|---|---|---|
| NA | CPU | NA | mcr.microsoft.com/azureml/minimal-ubuntu20.04-py38-cpu-inference:latest |
| NA | GPU | NA | mcr.microsoft.com/azureml/minimal-ubuntu20.04-py38-cuda11.6.2-gpu-inference:latest |
| NA | CPU | NA | mcr.microsoft.com/azureml/minimal-ubuntu22.04-py39-cpu-inference:latest |
| NA | GPU | NA | mcr.microsoft.com/azureml/minimal-ubuntu22.04-py39-cuda11.8-gpu-inference:latest |
Note
Azure Machine Learning supports Curated environments. You can browse curated environments and add filter for Tags: Inferencing.