Intel® AI Analytics Toolkit Release Notes

Overview

This document provides details about new features and known issues for the Intel® AI Analytics Toolkit. The toolkit includes the following components:

• Intel® Optimization for TensorFlow*

• Intel® Optimization for PyTorch*

• Intel® Distribution for Python*

• Intel® Low Precision Optimization Tool

• Model Zoo for Intel® Architecture

• Intel® Distribution for Modin*

Version History

Where to Find the Release

Please check the release page for more information on how to acquire the package.

Compatibility Notes

• Intel® Optimization for TensorFlow* is compatible with version 2.3

• Intel® Optimization for PyTorch * is compatible with version 1.7

• Intel® Distribution for Python* is compatible with cpython version 3.7

• Intel® Optimization of Modin* is compatible with version 0.8.2

What's New

• Intel® Optimization for TensorFlow* 

  • ​oneDNN - moved from 0.x to version 1.4

  • Support for Intel® MKL-DNN version 0.x is still available.
  • Issues resolved in TensorFlow 2.3
  • oneDNN resolved issues
    • 1.4 resolved issues
    • 1.3 resolved issues
    • 1.2 resolved issues

• Intel® Optimization for PyTorch * 

  • ​New PyTorch * 1.7.0 was newly supported by Intel extension for PyTorch *.

  • Device name was changed from DPCPP to XPU.

  • Enabled the launcher for end users.

  • Improvement for INT8 optimization with refined auto mixed precision API.

  • More operators are optimized for the int8 inference and bfp16 training of some key workloads, like: MaskRCNN, SSD-ResNet34, DLRM, RNNT.

  • New custom operators: ROIAlign, RNN, FrozenBatchNorm, nms.

  • Performance improvement for several operators: tanh, log_softmax, upsample, embeddingbad and enables int8 linear fusion.

  • Bug fixes

• Intel® Model Zoo

  • Several new TensorFlow* and PyTorch* models added to the Intel® Model Zoo.
  • Ten new TensorFlow workload containers and model packages that are available on the Intel® oneContainer Portal
  • Two new PyTorch workload containers and model packages that are available on the Intel® oneContainer Portal
  • Three new TensorFlow Kubernetes packages that are available on the Intel® oneContainer Portal:
  • A new Helm chart to deploy TensorFlow Serving on a K8s cluster
  • Bug-fixes, improvements to documentations

• Intel® Low Precision Optimization Tool

  • New backends (PyTorch/IPEX, ONNX Runtime) preview support
  • Add built-in industry dataset/metric and custom registration
  • Preliminary input/output node auto-detection on TensorFlow models
  • New INT8 quantization recipes: bias correction and label balance
  • 30+ OOB models validated

System Requirements

Please see system requirements.

How to Start Using the Tools

Please reference the usage guides for each of the included tools:

• Intel® Optimization for TensorFlow* - See Performance Considerations
• Intel® Optimization for PyTorch * - See Performance Considerations

Known Limitation

• Intel® Optimization for PyTorch* 
  • Multi-node training still encounter hang issues after several iterations. The fix will be included in the next official release.

Notices and Disclaimers

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