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1.1. Prerequisites
1.2. Install from Binary
1.3. Install from Source
1.4. Install from AI Kit
You can install Neural Compressor using one of three options: Install single component from binary or source, or get the Intel-optimized framework together with the library by installing the Intel® oneAPI AI Analytics Toolkit.
The following prerequisites and requirements must be satisfied for a successful installation:
- Python version: 3.8 or 3.9 or 3.10 or 3.11
Notes:
- If you get some build issues, please check frequently asked questions at first.
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Install from Pypi
# install stable basic version from pypi pip install neural-compressor
# [Experimental] install stable basic + PyTorch framework extension API from pypi pip install neural-compressor[pt]
# [Experimental] install stable basic + TensorFlow framework extension API from pypi pip install neural-compressor[tf]
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Install from test Pypi
# install nightly version git clone https://github.com/intel/neural-compressor.git cd neural-compressor pip install -r requirements.txt # install nightly basic version from pypi pip install -i https://test.pypi.org/simple/ neural-compressor
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Install from Conda
# install on Linux OS conda install opencv-python-headless -c fastai conda install neural-compressor -c conda-forge -c intel
# install on Windows OS conda install pycocotools -c esri conda install opencv-python-headless -c fastai conda install neural-compressor -c conda-forge -c intel
git clone https://github.com/intel/neural-compressor.git
cd neural-compressor
pip install -r requirements.txt
# build with basic functionality
python setup.py install
The Intel® Neural Compressor library is released as part of the Intel® oneAPI AI Analytics Toolkit (AI Kit). The AI Kit provides a consolidated package of Intel's latest deep learning and machine optimizations all in one place for ease of development. Along with Neural Compressor, the AI Kit includes Intel-optimized versions of deep learning frameworks (such as TensorFlow and PyTorch) and high-performing Python libraries to streamline end-to-end data science and AI workflows on Intel architectures.
The AI Kit is distributed through many common channels, including from Intel's website, YUM, APT, Anaconda, and more. Select and download the AI Kit distribution package that's best suited for you and follow the Get Started Guide for post-installation instructions.
Download | Guide |
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Download AI Kit | AI Kit Get Started Guide |
Intel® Neural Compressor supports CPUs based on Intel 64 architecture or compatible processors:
- Intel Xeon Scalable processor (formerly Skylake, Cascade Lake, Cooper Lake, Ice Lake, and Sapphire Rapids)
- Intel Xeon CPU Max Series (formerly Sapphire Rapids HBM)
- Intel Data Center GPU Flex Series (formerly Arctic Sound-M)
- Intel Data Center GPU Max Series (formerly Ponte Vecchio)
Intel® Neural Compressor quantized ONNX models support multiple hardware vendors through ONNX Runtime:
- Intel CPU, AMD/ARM CPU, and NVidia GPU. Please refer to the validated model list.
- OS version: CentOS 8.4, Ubuntu 22.04, MacOS Ventura 13.5
- Python version: 3.8, 3.9, 3.10, 3.11
Framework | TensorFlow | Intel TensorFlow |
Intel® Extension for TensorFlow* |
PyTorch | Intel® Extension for PyTorch* |
ONNX Runtime |
MXNet |
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Version | 2.15.0 2.14.1 2.13.0 |
2.14.0 2.13.0 2.12.0 |
2.14.0.1 2.13.0.0 1.2.0 |
2.1.0+cpu 2.0.1+cpu 1.13.1+cpu |
2.1.0+cpu 2.0.1+cpu 1.13.1+cpu |
1.16.3 1.15.1 1.14.1 |
1.9.1 |
Note: Set the environment variable
TF_ENABLE_ONEDNN_OPTS=1
to enable oneDNN optimizations if you are using TensorFlow before v2.9. oneDNN is the default for TensorFlow since v2.9 (Intel Cascade Lake and newer CPUs).