Wide & Deep FP32 Inference TensorFlow* Model Package

Published: 10/23/2020

Last Updated: 06/15/2022

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

Description

This document has instructions to run a Wide & Deep FP32 inference using Intel® Optimizations for TensorFlow*.

Download and preprocess the income census data by running the following Python* script, which is a standalone version of census_dataset.py Please note that below program requires requests module to be installed. You can install is using pip install requests. Dataset will be downloaded in directory provided using --data_dir. If you are behind proxy then you can proxy urls using --http_proxy and --https_proxy arguments.

git clone https://github.com/IntelAI/models.git
cd models
python ./benchmarks/recommendation/tensorflow/wide_deep/inference/fp32/data_download.py --data_dir /home/<user>/widedeep_dataset

Quick Start Scripts

Script name Description
fp32_inference_online Runs Wide & Deep model inference online mode (batch size = 1)
fp32_inference_batch Runs Wide & Deep model inference in batch mode (batch size = 1024)

Bare Metal

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

1. Download and untar the Wide & Deep FP32 inference model package:

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

2. Clone tensorflow/models as a tensorflow-models

# We are going to use a branch based on older version of the tensorflow model repo.
# Since, we need to to use logs utils on that branch, which were removed from
# the latest master
git clone https://github.com/tensorflow/models.git tensorflow-models
cd tensorflow-models
git checkout wide-deep-tf2

3. Once your environment is setup, navigate back to the directory that contains the Wide & Deep FP32 inference model package, set environment variables pointing to your dataset and output directories, and then run a quickstart script.

DATASET_DIR=<path to the Wide & Deep dataset directory>
OUTPUT_DIR=<directory where log files will be written>
TF_MODEL_SOURCE_DIR=<path to tensorflow-models>

quickstart/<script name>.sh

Documentation and Sources

Code Sources
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Product and Performance Information

1

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