Intel® Neural Compressor v1.7 Release
Intel® Neural Compressor(formerly known as Intel® Low Precision Optimization Tool) v1.7 release is featured by:
Features
- Quantization
- Improved quantization accuracy in SSD-Reset34 and MobileNet v3 on TensorFlow
- Pruning
- Supported magnitude pruning on TensorFlow
- Knowledge distillation
- Supported knowledge distillation on PyTorch
- Multi-node support
- Supported multi-node pruning with distributed dataloader on PyTorch
- Supported multi-node inference for benchmark on PyTorch
- Acceleration library
- Added a domain-specific acceleration library for NLP models
Productivity
- Supported the configuration-free (pure Python) quantization
- Improved ease-of-use user interface for quantization with few clicks
Ecosystem
- Integrated into HuggingFace optimization library (Optimum)
- Upstreamed INC quantized models (RN50, VGG16) to ONNX Model Zoo
Documentation
- Add tutorial and examples for knowledge distillation
- Add tutorial and examples for multi-node training
- Add tutorial and examples for acceleration library
Validated Configurations
- Python 3.6 & 3.7 & 3.8 & 3.9
- Centos 8.3 & Ubuntu 18.04
- TensorFlow 2.6.0
- Intel TensorFlow 2.4.0, 2.5.0 and 1.15.0 UP3
- PyTorch 1.8.0+cpu, 1.9.0+cpu, IPEX 1.8.0
- MxNet 1.6.0, 1.7.0, 1.8.0
- ONNX Runtime 1.6.0, 1.7.0, 1.8.0
Distribution:
| Channel | Links | Install Command | |
|---|---|---|---|
| Source | Github | https://github.com/intel/neural-compressor.git | $ git clone https://github.com/intel/neural-compressor.git |
| Binary | Pip | https://pypi.org/project/neural-compressor | $ pip install neural-compressor |
| Binary | Conda | https://anaconda.org/intel/neural-compressor | $ conda install neural-compressor -c conda-forge -c intel |
Contact:
Please feel free to contact [email protected], if you get any questions.