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TensorFlow DIEN Training

Description

This document has instructions for running DIEN training using Intel-optimized TensorFlow.

Enviromnment setup

  • Create a virtual environment venv-tf using Python 3.8:
pip install virtualenv
# use `whereis python` to find the `python3.8` path in the system and specify it. Please install `Python3.8` if not installed on your system.
virtualenv -p /usr/bin/python3.8 venv-tf
source venv-tf/bin/activate

# If git, numactl and wget were not installed, please install them using
yum update -y && yum install -y git numactl wget

# Install Intel Optimized TensorFlow
pip install intel-tensorflow==2.11.dev202242
pip install keras-nightly==2.11.0.dev2022092907

Note: For kernel version 5.16, AVX512_CORE_AMX is turned on by default. If the kernel version < 5.16 , please set the following environment variable for AMX environment: DNNL_MAX_CPU_ISA=AVX512_CORE_AMX. To run VNNI, please set DNNL_MAX_CPU_ISA=AVX512_CORE_BF16.

Quick Start Scripts

Script name Description
training.sh Runs training with a batch size of 128 for the specified precisions fp32, bfloat16 and bfloat32.

Datasets

Use prepare_data.sh to get a subset of the Amazon book reviews data and process it. Or download and extract the preprocessed data files directly:

wget https://zenodo.org/record/3463683/files/data.tar.gz
wget https://zenodo.org/record/3463683/files/data1.tar.gz
wget https://zenodo.org/record/3463683/files/data2.tar.gz

tar -jxvf data.tar.gz
mv data/* .
tar -jxvf data1.tar.gz
mv data1/* .
tar -jxvf data2.tar.gz
mv data2/* .

Set the DATASET_DIR to point to the directory with the dataset files when running .

Run the model

After you've followed the instructions to prepare the dataset using real data, set environment variables to specify the path to the dataset directory, precision to run, and an output directory.

# Set the required environment vars
export PRECISION=<supported precisions are fp32, bfloat16, bfloat32>
export DATASET_DIR=<path to the dataset>
export OUTPUT_DIR=<directory where log files will be written>

Navigate to the models directory to training.

cd models

Run training:

./quickstart/recommendation/tensorflow/dien/training/cpu/training.sh

License

Licenses can be found in the model package, in the licenses directory.