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Deep Learning with PyTorch Lightning

You're reading from  Deep Learning with PyTorch Lightning

Product type Book
Published in Apr 2022
Publisher Packt
ISBN-13 9781800561618
Pages 366 pages
Edition 1st Edition
Languages
Author (1):
Kunal Sawarkar Kunal Sawarkar
Profile icon Kunal Sawarkar

Table of Contents (15) Chapters

Preface 1. Section 1: Kickstarting with PyTorch Lightning
2. Chapter 1: PyTorch Lightning Adventure 3. Chapter 2: Getting off the Ground with the First Deep Learning Model 4. Chapter 3: Transfer Learning Using Pre-Trained Models 5. Chapter 4: Ready-to-Cook Models from Lightning Flash 6. Section 2: Solving using PyTorch Lightning
7. Chapter 5: Time Series Models 8. Chapter 6: Deep Generative Models 9. Chapter 7: Semi-Supervised Learning 10. Chapter 8: Self-Supervised Learning 11. Section 3: Advanced Topics
12. Chapter 9: Deploying and Scoring Models 13. Chapter 10: Scaling and Managing Training 14. Other Books You May Enjoy

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "You can use the gpus argument passed to Trainer to specify the number of GPUs."

A block of code is set as follows:

import pytorch_lightning as pl
...
# use only 10% of the training data for each epoch
trainer = pl.Trainer(limit_train_batches=0.1)
# use only 10 batches per epoch
trainer = pl.Trainer(limit_train_batches=10)

Any command-line input or output is written as follows:

pip install pytorch-lightning

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: "For example, in Google Colab, you can Change Runtime Type to set Runtime shape to High-RAM instead of Standard so that you can increase the value of the num_workers argument to DataLoader "

Tips or Important Notes

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