TensorFlow is an open-source high-performance machine learning framework. This image has been optimized using oneAPI Deep Neural Network Library (oneDNN) primitives.
Overview of TensorFlow for Intel
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$ docker run -it --name tensorflow-intel bitnami/tensorflow-intel$ curl -sSL https://raw.githubusercontent.com/bitnami/bitnami-docker-tensorflow-intel/master/docker-compose.yml > docker-compose.yml
$ docker-compose up -dNew instructions, coupled with algorithmic and software innovations, deliver breakthrough performance for the industry's most widely deployed cryptographic ciphers. Encryption is becoming pervasive with most organizations increasingly adopting encryption for application execution, data in flight, and data storage. 3rd gen Intel® Xeon® Scalable Processor (Ice Lake) cores and architecture, offers several new instructions for encryption acceleration.
This solution requires 3rd gen Intel Xeon Scalable Processor (Ice Lake) to get a breakthrough performance improvement.
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Subscribe to project updates by watching the bitnami/tensorflow-intel GitHub repo.
The recommended way to get the Bitnami tensorflow-intel Docker Image is to pull the prebuilt image from the Docker Hub Registry.
$ docker pull bitnami/tensorflow-intel:latestTo 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/tensorflow-intel:[TAG]If you wish, you can also build the image yourself.
$ docker build -t bitnami/tensorflow-intel 'https://github.com/bitnami/bitnami-docker-tensorflow-intel.git#master:2/debian-10'By default, running this image will drop you into the Python REPL, where you can interactively test and try things out with TensorFlow for Intel in Python.
$ docker run -it --name tensorflow-intel bitnami/tensorflow-intelThe default work directory for the TensorFlow for Intel image is /app. You can mount a folder from your host here that includes your TensorFlow for Intel script, and run it normally using the python command.
$ docker run -it --name tensorflow-intel -v /path/to/app:/app bitnami/tensorflow-intel \
python script.pyIf your TensorFlow for Intel app has a requirements.txt defining your app's dependencies, you can install the dependencies before running your app.
$ docker run -it --name tensorflow-intel -v /path/to/app:/app bitnami/tensorflow-intel \
sh -c "pip install -r requirements.txt && python script.py"Further Reading:
Bitnami provides up-to-date versions of TensorFlow for Intel, including security patches, soon after they are made upstream. We recommend that you follow these steps to upgrade your container.
$ docker pull bitnami/tensorflow-intel:latestor if you're using Docker Compose, update the value of the image property to bitnami/tensorflow-intel:latest.
$ docker rm -v tensorflow-intelor using Docker Compose:
$ docker-compose rm -v tensorflow-intelRe-create your container from the new image.
$ docker run --name tensorflow-intel bitnami/tensorflow-intel:latestor using Docker Compose:
$ docker-compose up tensorflow-intelWe'd love for you to contribute to this container. You can request new features by creating an issue, or submit 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 include the following information in your issue:
- Host OS and version
- Docker version (
$ docker version) - Output of
$ docker info - Version of this container
- The command you used to run the container, and any relevant output you saw (masking any sensitive information)
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