installation_guide.md

Installation

1. Installation

   1.1. Prerequisites

   1.2. Install from Binary

   1.3. Install from Source

   1.4. Install from AI Kit

2. System Requirements

   2.1. Validated Hardware Environment

   2.2. Validated Software Environment

Installation

Prerequisites

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.

Install Framework

Install torch for CPU

pip install torch --index-url https://download.pytorch.org/whl/cpu

Use Docker Image with torch installed for HPU

https://docs.habana.ai/en/latest/Installation_Guide/Bare_Metal_Fresh_OS.html#bare-metal-fresh-os-single-click

Install torch/intel_extension_for_pytorch for Intel GPU

https://intel.github.io/intel-extension-for-pytorch/index.html#installation

Install torch for other platform

https://pytorch.org/get-started/locally

Install tensorflow

pip install tensorflow

Install from Binary

• Install from Pypi

# Install 2.X API + Framework extension API + PyTorch dependency
pip install neural-compressor[pt]

# Install 2.X API + Framework extension API + TensorFlow dependency
pip install neural-compressor[tf]

# Install 2.X API + Framework extension API
# With this install CMD, some dependencies for framework extension API not installed, 
# you can install them separately by `pip install -r requirements_pt.txt` or `pip install -r requirements_tf.txt`.
pip install neural-compressor

# Framework extension API + TensorFlow dependency
pip install neural-compressor-pt

# Framework extension API + TensorFlow dependency
pip install neural-compressor-tf

Install from Source

git clone https://github.com/intel/neural-compressor.git
cd neural-compressor
pip install -r requirements.txt
python setup.py install
[optional] pip install -r requirements_pt.txt # for PyTorch framework extension API
[optional] pip install -r requirements_tf.txt # for TensorFlow framework extension API

Install from AI Kit

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
Download AI Kit	AI Kit Get Started Guide

System Requirements

Validated Hardware Environment

Intel® Neural Compressor supports HPUs based on heterogeneous architecture with two compute engines (MME and TPC):

• Intel Gaudi Al Accelerators (Gaudi2)

Intel® Neural Compressor supports CPUs based on Intel 64 architecture or compatible processors:

• Intel Xeon Scalable processor (Skylake, Cascade Lake, Cooper Lake, Ice Lake, and Sapphire Rapids)
• Intel Xeon CPU Max Series (Sapphire Rapids HBM)
• Intel Core Ultra Processors (Meteor Lake)

Intel® Neural Compressor supports GPUs built on Intel's Xe architecture:

• Intel Data Center GPU Flex Series (Arctic Sound-M)
• Intel Data Center GPU Max Series (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.

Validated Software Environment

• OS version: CentOS 8.4, Ubuntu 22.04, MacOS Ventura 13.5, Windows 11
• Python version: 3.8, 3.9, 3.10, 3.11

Framework	TensorFlow	Intel® Extension for TensorFlow*	PyTorch	Intel® Extension for PyTorch*	ONNX Runtime
Version	2.16.1 2.15.0 2.14.1	2.15.0.0 2.14.0.1 2.13.0.0	2.3.0 2.2.2 2.1.1	2.3.0 2.2.0 2.1.100	1.18.0 1.17.3 1.16.3