Optimize AI Model Zoo Workloads with TensorFlow* for 4th Generation Intel® Xeon® Scalable Processors

ID 772112
Updated 2/10/2023
Version Latest





This document provides links to step-by-step instructions on how to leverage Model Zoo docker containers to run optimized open-source Deep Learning Training and Inference workloads using TensorFlow framework on 4th Generation Intel® Xeon® Scalable processors

Note: The containers below are based on pre-production build for Intel®  Optimization for TensorFlow* and are for customer preview only and are not intended for use in production. 

Use cases

The tables below provide links to run each use case using docker containers. The model scripts run on Linux.

Image Recognition

Model Documentation Link Dataset   
ResNet 50v1.5 Training ImageNet 2012
ResNet 50v1.5 Inference ImageNet 2012
MobileNet V1* Inference ImageNet 2012






Image Segmentation

Model Documentation Link Dataset   
3D U-Net MLPerf* Inference BRATS 2019




Object Detection

Model Documentation Link Dataset   
SSD-ResNet34 Training COCO 2017  
SSD-ResNet34 Inference COCO 2017 
SSD-MobileNet* Inference COCO 2017





Language Modeling

Model Documentation Link Dataset   
BERT large Training SQuAD and MRPC
BERT large Inference SQuAD





Language Translation

Model Documentation Link Dataset   
Transformer_LT_mlperf* Training WMT English-German dataset           
Transformer_LT_mlperf* Inference WMT English-German dataset             






Model Documentation Link Dataset   
DIEN Training DIEN dataset       
DIEN Inference DIEN dataset       





Documentation and Sources 

Get Started                                Code Sources                                              

Main GitHub*                                                         Dockerfiles

Release Notes                                                       Report Issue                                                                         

License Agreement

LEGAL NOTICE: By accessing, downloading or using this software and any required dependent software (the “Software Package”), you agree to the terms and conditions of the software license agreements for the Software Package, which may also include notices, disclaimers, or license terms for third party software included with the Software Package. Please refer to the license file for additional details.

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