# Optimize a ResNet101* FP32 Inference Model Package with TensorFlow*

Published: 12/09/2020

Last Updated: 06/15/2022

wget https://storage.googleapis.com/intel-optimized-tensorflow/models/v2_3_0/resnet101-fp32-inference.tar.gz

## Description

This document has instructions for running ResNet101* FP32 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 ResNet101*.

#### 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. 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>

tar -xzf resnet101-fp32-inference.tar.gz
cd resnet101-fp32-inference

quickstart/<script name>.sh


## Documentation and Sources

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## Related Containers and Solutions

ResNet101* FP32 Inference TensorFlow* Container

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#### Product and Performance Information

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