Download Command
wget https://storage.googleapis.com/intel-optimized-tensorflow/models/v2_3_0/densenet169-fp32-inference.tar.gz
Description
This document has instructions for running DenseNet-169 FP32 inference using Intel® Optimization for TensorFlow*.
Download and preprocess the ImageNet dataset using the instructions. 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 DenseNet-169 .
Quick Start Scripts
| Script name | Description |
|---|---|
fp32_online_inference |
Runs online inference (batch_size=1). |
fp32_batch_inference |
Runs batch inference (batch_size=100). |
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:
- Python* 3
- Intel Optimization for TensorFlow
- Numactl
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/densenet169-fp32-inference.tar.gz
tar -xzf densenet169-fp32-inference.tar.gz
cd densenet169-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.