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Deep Learning with MXNet Cookbook

You're reading from   Deep Learning with MXNet Cookbook Discover an extensive collection of recipes for creating and implementing AI models on MXNet

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781800569607
Length 370 pages
Edition 1st Edition
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Author (1):
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Andrés P. Torres Andrés P. Torres
Author Profile Icon Andrés P. Torres
Andrés P. Torres
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Table of Contents (12) Chapters Close

Preface 1. Chapter 1: Up and Running with MXNet FREE CHAPTER 2. Chapter 2: Working with MXNet and Visualizing Datasets – Gluon and DataLoader 3. Chapter 3: Solving Regression Problems 4. Chapter 4: Solving Classification Problems 5. Chapter 5: Analyzing Images with Computer Vision 6. Chapter 6: Understanding Text with Natural Language Processing 7. Chapter 7: Optimizing Models with Transfer Learning and Fine-Tuning 8. Chapter 8: Improving Training Performance with MXNet 9. Chapter 9: Improving Inference Performance with MXNet 10. Index 11. 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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