Intel® Low Precision Optimization Tool v1.6 Release
Intel® Low Precision Optimization Tool v1.6 release is featured by:
Pruning:
- Support pruning and post-training quantization pipeline on PyTorch
- Support pruning during quantization-aware training on PyTorch
Quantization:
- Support post-training quantization on TensorFlow 2.6.0, PyTorch 1.9.0, IPEX 1.8.0, and MXNet 1.8.0
- Support quantization-aware training on TensorFlow 2.x (Keras API)
User Experience:
- Improve quantization productivity with new UI
- Support quantized model recovery from tuning history
New Models:
- Support ResNet50 on ONNX model zoo
Documentation:
- Add pruned models
- Add quantized MLPerf models
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/lpot.git | $ git clone https://github.com/intel/lpot.git |
| Binary | Pip | https://pypi.org/project/lpot | $ pip install lpot |
| Binary | Conda | https://anaconda.org/intel/lpot | $ conda install lpot -c conda-forge -c intel |
Contact:
Please feel free to contact [email protected], if you get any questions.