WaveNet FP32 Inference Tensorflow* Container

Published: 10/23/2020  

Last Updated: 06/15/2022

Pull Command

docker pull intel/text-to-speech:tf-latest-wavenet-fp32-inference

Description

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

Quick Start Scripts

Script name Description
fp32_inference Runs inference with a pretrained model

Docker*

The model container intel/text-to-speech:tf-1.15.2-imz-2.0.0-wavenet-fp32-inference includes the scripts and libraries needed to run WaveNet FP32 inference. To run one of the quickstart scripts using this container, you'll need to provide volume mounts for the output directory.

OUTPUT_DIR=<directory where log files will be written>

docker run \
  --env OUTPUT_DIR=${OUTPUT_DIR} \
  --env http_proxy=${http_proxy} \
  --env https_proxy=${https_proxy} \
  --volume ${OUTPUT_DIR}:${OUTPUT_DIR} \
  --privileged --init -t \
  intel/text-to-speech:tf-latest-wavenet-fp32-inference \
  /bin/bash quickstart/fp32_inference.sh

Documentation and Sources

Get Started
Docker* Repository
Main GitHub*
Readme
Release Notes
Get Started Guide

Code Sources
Dockerfile
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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Product and Performance Information

1

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