WaveNet FP32 Inference Tensorflow* Model Package

Download Command

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

Description

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

Quick Start Scripts

Bare Metal

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

• Python* 3
• intel-tensorflow
• librosa==0.5
• numactl
• Clone the tensorflow-wavenet repo and get pull request #352 for the CPU optimizations. The path to the cloned repo will be passed as the model source directory when running the launch script.

git clone https://github.com/ibab/tensorflow-wavenet.git
cd tensorflow-wavenet/

git fetch origin pull/352/head:cpu_optimized
git checkout cpu_optimized

After installing the prerequisites, download and untar the model package. Set environment variables for the path to your TF_WAVENET_DIR and an OUTPUT_DIR where log files will be written, then run a quickstart script.

TF_WAVENET_DIR=<tensorflow-wavenet directory>
OUTPUT_DIR=<directory where log files will be written>

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

quickstart/fp32_inference.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.

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WaveNet FP32 Inference TensorFlow* Container

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