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Deep Learning with PyTorch Lightning

You're reading from   Deep Learning with PyTorch Lightning Swiftly build high-performance Artificial Intelligence (AI) models using Python

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781800561618
Length 366 pages
Edition 1st Edition
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Authors (2):
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Dheeraj Arremsetty Dheeraj Arremsetty
Author Profile Icon Dheeraj Arremsetty
Dheeraj Arremsetty
Kunal Sawarkar Kunal Sawarkar
Author Profile Icon Kunal Sawarkar
Kunal Sawarkar
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Kickstarting with PyTorch Lightning
2. Chapter 1: PyTorch Lightning Adventure FREE CHAPTER 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

Building a Hello World MLP model

Welcome to the world of PyTorch Lightning!

Finally, it's time for us to build our first model using PyTorch Lightning. In this section, we will build a simple MLP model to accomplish the XOR operator. This is like a Hello World introduction to the world of NNs as well as PyTorch Lightning. We will follow these steps to build our first XOR operator:

  1. Importing libraries
  2. Preparing the data
  3. Configuring the model
  4. Training the model
  5. Loading the model
  6. Making predictions

Importing libraries

We begin by first importing the necessary libraries and printing their package versions, as follows:

import pytorch_lightning as pl
import torch
from torch import nn, optim
from torch.autograd import Variable
import pytorch_lightning as pl
from pytorch_lightning.callbacks import ModelCheckpoint
from torch.utils.data import DataLoader
print("torch version:",torch.__version__)
print("pytorch ligthening version...
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