bitnami/pytorch
Bitnami container image for PyTorch
1M+
PyTorch is a deep learning platform that accelerates the transition from research prototyping to production deployment. Bitnami image includes Torchvision for specific computer vision support.
Overview of PyTorch Trademarks: This software listing is packaged by Bitnami. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.
docker run -it --name pytorch bitnami/pytorch
Looking to use PyTorch in production? Try VMware Tanzu Application Catalog, the commercial edition of the Bitnami catalog.
Non-root container images add an extra layer of security and are generally recommended for production environments. However, because they run as a non-root user, privileged tasks are typically off-limits. Learn more about non-root containers in our docs.
Starting December 10th 2024, only the latest stable branch of any container will receive updates in the free Bitnami catalog. To access up-to-date releases for all upstream-supported branches, consider upgrading to Bitnami Premium. Previous versions already released will not be deleted. They are still available to pull from DockerHub.
Please check the Bitnami Premium page in our partner Arrow Electronics for more information.
Dockerfile
linksLearn more about the Bitnami tagging policy and the difference between rolling tags and immutable tags in our documentation page.
You can see the equivalence between the different tags by taking a look at the tags-info.yaml
file present in the branch folder, i.e bitnami/ASSET/BRANCH/DISTRO/tags-info.yaml
.
Subscribe to project updates by watching the bitnami/containers GitHub repo.
The recommended way to get the Bitnami Pytorch Docker Image is to pull the prebuilt image from the Docker Hub Registry.
docker pull bitnami/pytorch:latest
To use a specific version, you can pull a versioned tag. You can view the list of available versions in the Docker Hub Registry.
docker pull bitnami/pytorch:[TAG]
If you wish, you can also build the image yourself by cloning the repository, changing to the directory containing the Dockerfile and executing the docker build
command. Remember to replace the APP
, VERSION
and OPERATING-SYSTEM
path placeholders in the example command below with the correct values.
git clone https://github.com/bitnami/containers.git
cd bitnami/APP/VERSION/OPERATING-SYSTEM
docker build -t bitnami/APP:latest .
By default, running this image will drop you into the Python REPL, where you can interactively test and try things out with PyTorch in Python.
docker run -it --name pytorch bitnami/pytorch
The default work directory for the PyTorch image is /app
. You can mount a folder from your host here that includes your PyTorch script, and run it normally using the python
command.
docker run -it --name pytorch -v /path/to/app:/app bitnami/pytorch \
python script.py
If your PyTorch app has a requirements.txt
defining your app's dependencies, you can install the dependencies before running your app.
docker run -it --name pytorch -v /path/to/app:/app bitnami/pytorch \
sh -c "conda install -y --file requirements.txt && python script.py"
Further Reading:
Bitnami provides up-to-date versions of PyTorch, including security patches, soon after they are made upstream. We recommend that you follow these steps to upgrade your container.
Step 1: Get the updated image
docker pull bitnami/pytorch:latest
or if you're using Docker Compose, update the value of the image property to bitnami/pytorch:latest
.
Step 2: Remove the currently running container
docker rm -v pytorch
or using Docker Compose:
docker-compose rm -v pytorch
Step 3: Run the new image
Re-create your container from the new image.
docker run --name pytorch bitnami/pytorch:latest
or using Docker Compose:
docker-compose up pytorch
This version removes miniconda in favour of pip. This creates a smaller container and least prone to security issues. Users extending this container with other packages will need to switch from conda to pip commands.
docker-compose.yaml
Please be aware this file has not undergone internal testing. Consequently, we advise its use exclusively for development or testing purposes. For production-ready deployments, we highly recommend utilizing its associated Bitnami Helm chart.
If you detect any issue in the docker-compose.yaml
file, feel free to report it or contribute with a fix by following our Contributing Guidelines.
We'd love for you to contribute to this Docker image. You can request new features by creating an issue or submitting a pull request with your contribution.
If you encountered a problem running this container, you can file an issue. For us to provide better support, be sure to fill the issue template.
Copyright © 2025 Broadcom. The term "Broadcom" refers to Broadcom Inc. and/or its subsidiaries.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.