Verified Hardware Platforms:
- 2nd Generation Intel® Xeon® Scalable Processors.
- 3rd Generation Intel® Xeon® Scalable Processors.
- 4th Generation Intel® Xeon® Scalable Processors.
- Ubuntu 20.04 (64-bit), Ubuntu 22.04 (64-bit) or CentOS Linux 8 (64-bit), and Sapphire Rapids requires Ubuntu 22.04 or CentOS Linux 8 with kernel version >= 5.16
- Python 3.9-3.10
- pip 19.0 or later (requires manylinux2014 support)
Run the following Dockerfile build procedure to build the pip based deployment container.
Pre-built docker images are available at DockerHub. Run the following command to pull the CPU Docker container image to your local machine.
$ docker pull intel/intel-extension-for-tensorflow:cpu
$ docker run -it -p 8888:8888 intel/intel-extension-for-tensorflow:cpu
Then go to your browser on http://localhost:8888/
The Python development and virtual environment setup recommendation by TensorFlow to isolate package installation from the system.
The Intel® Extension for TensorFlow* requires stock TensorFlow, and the version should be == 2.15.0.
You can follow the instructions in stock tensorflow install to activate the virtual environment.
On Linux, it is often necessary to first update pip to a version that supports manylinux2014 wheels.
(tf)$ pip install --upgrade pip
To install in virtual environment, you can run
(tf)$ pip install tensorflow==2.15.0
If you prefer install tensorflow in $HOME, append --user
to the commands.
$ pip3 install --user tensorflow==2.15.0
And the following system environment install for Intel® Extension for TensorFlow* will also append --user
to the command.
To install a CPU-only version in virtual environment, you can run
(tf)$ pip install --upgrade intel-extension-for-tensorflow[cpu]
python -c "import intel_extension_for_tensorflow as itex; print(itex.__version__)"