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Intel® Neural Compressor v1.8 Release
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@ftian1 ftian1 released this 22 Nov 05:22
· 2358 commits to master since this release
v1.8
d25f0fd

Features

  • Knowledge distillation
    • Implemented the algorithms of paper “Pruning Once For All” accepted by NeurIPS 2021 ENLSP workshop
    • Supported optimization pipelines (knowledge distillation & quantization-aware training) on PyTorch
  • Quantization
    • Added the support of ONNX RT 1.7
    • Added the support of TensorFlow 2.6.2 and 2.7
    • Added the support of PyTorch 1.10
  • Pruning
    • Supported magnitude pruning on TensorFlow
  • Acceleration library
    • Supported Hugging Face top 10 downloaded NLP models

Productivity

  • Added performance profiling feature to INC UI service.
  • Improved ease-of-use user interface for quantization with few clicks

Ecosystem

  • Added notebook of using HuggingFace optimization library (Optimum) to Transformers
  • Enabled top 20 downloaded Hugging Face NLP models with Optimum
  • Upstreamed more INC quantized models to ONNX Model Zoo

Validated Configurations

  • Python 3.6 & 3.7 & 3.8 & 3.9
  • Centos 8.3 & Ubuntu 18.04
  • TensorFlow 2.6.2 & 2.7
  • 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.

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