Optimize a ResNet50* FP32 Model Package with TensorFlow*

Published: 10/23/2020  

Last Updated: 06/15/2022

Download Command

wget https://storage.googleapis.com/intel-optimized-tensorflow/models/v2_3_0/resnet50-fp32-inference.tar.gz

Description

This document has instructions for running ResNet50* FP32 inference using Intel® Optimization for TensorFlow*.

Note that the ImageNet dataset is used in these ResNet50 examples. 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.

Quick Start Scripts

Script name Description
fp32_online_inference Runs online inference (batch_size=1).
fp32_batch_inference Runs batch inference (batch_size=128).
fp32_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 and then run a quick start script.

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

wget https://storage.googleapis.com/intel-optimized-tensorflow/models/v2_3_0/resnet50-fp32-inference.tar.gz
tar -xzf resnet50-fp32-inference.tar.gz
cd resnet50-fp32-inference

quickstart/<script name>.sh

Documentation and Sources

Get Started​
Main GitHub*
Readme
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.


Related Containers and Solutions

ResNet50 FP32 Inference TensorFlow* Container

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Product and Performance Information

1

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