Optimize a ResNet50* V1.5 Bfloat16 Inference Model with TensorFlow*

Published: 11/09/2020  

Last Updated: 06/15/2022

Download Command

wget https://storage.googleapis.com/intel-optimized-tensorflow/models/v2_3_0/resnet50v1-5-bfloat16-inference.tar.gz


This document has instructions for running ResNet50* v1.5 bfloat16 inference using Intel® Optimization for TensorFlow*.

Download and preprocess the ImageNet dataset using the instructions here. After running the conversion script you should have a directory with the ImageNet dataset in the TF records format.

Set the DATASET_DIR to point to this directory when running ResNet50 v1.5.

Quick Start Scripts

Script name Description
bfloat16_online_inference Runs online inference (batch_size=1).
bfloat16_batch_inference Runs batch inference (batch_size=128).
bfloat16_accuracy Measures the model accuracy (batch_size=100).

Bare Metal

To run on bare metal, the following prerequisites must be installed in your environment:

Download and untar the model package. Set environment variables for the path to your DATASET_DIR and an OUTPUT_DIR where log files will be written, then run a quick start script.

DATASET_DIR=<path to the dataset>
OUTPUT_DIR=<directory where log files will be written>

wget https://storage.googleapis.com/intel-optimized-tensorflow/models/v2_3_0/resnet50v1-5-bfloat16-inference.tar.gz
tar -xzf resnet50v1_5-bfloat16-inference.tar.gz
cd resnet50v1_5-bfloat16-inference

quickstart/<script name>.sh


Documentation and Sources

Get Started​
Main GitHub*
Release Notes
Get Started Guide

Code Sources
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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ResNet50 V1.5 BFloat Inference TensorFlow* Container

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Product and Performance Information


Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.