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Deep Learning with MXNet Cookbook

You're reading from  Deep Learning with MXNet Cookbook

Product type Book
Published in Dec 2023
Publisher Packt
ISBN-13 9781800569607
Pages 370 pages
Edition 1st Edition
Languages
Author (1):
Andrés P. Torres Andrés P. Torres
Profile icon Andrés P. Torres

Table of Contents (12) Chapters

Preface Chapter 1: Up and Running with MXNet Chapter 2: Working with MXNet and Visualizing Datasets – Gluon and DataLoader Chapter 3: Solving Regression Problems Chapter 4: Solving Classification Problems Chapter 5: Analyzing Images with Computer Vision Chapter 6: Understanding Text with Natural Language Processing Chapter 7: Optimizing Models with Transfer Learning and Fine-Tuning Chapter 8: Improving Training Performance with MXNet Chapter 9: Improving Inference Performance with MXNet Index Other Books You May Enjoy

Optimizing inference when translating text from English to German

In the initial recipe, we saw how we can leverage MXNet and Gluon to optimize the inference of our models, applying different techniques: improving the runtime performance using hybridization; how using half-precision (float16) in combination with AMP can strongly reduce our inference times; and how to take advantage of further optimizations with data types such as Int8 quantization.

Now, we can revisit a problem we have been working with throughout the book: translating English to German. We have worked with translation tasks in recipes from previous chapters. In Recipe 4, Translating text from Vietnamese to English, from Chapter 6, Understanding Text with Natural Language Processing, we introduced the task of translating text, while also learning how to use pre-trained models from GluonCV Model Zoo.

Furthermore, in Recipe 4, Improving performance for translating English to German, from Chapter 7, Optimizing Models...

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