<pip install> – My Lightning adventure

Getting started with PyTorch Lightning is very easy. You can use the Anaconda distribution to set up your environment locally or use a cloud option such as Google Colaboratory (Google Colab), Amazon Web Services (AWS), Azure, or IBM Watson Studio to get started. (It is recommended that you use a cloud environment to run some of the more complex models.) Most of the code in this book is run on Google Collab or Anaconda using Python 3.6 with Mac OS. Please make appropriate changes to your env on other systems for installation.

PyTorch Lightning can be installed using pip in your Jupyter notebook environment, like this:

pip install pytorch-lightning

In addition to importing PyTorch Lightning (the first import statement can be seen in the following code snippet), the following import block shows statements that are usually part of the code:

import pytorch_lightning as pl
import torch
from torch import nn
import torch.nn.functional as F
from torchvision import transforms

The torch package is used for defining tensors and for performing mathematical operations on the tensors. The torch.nn package is used for constructing neural networks, which is what nn stands for. torch.nn.functional contains functions including activation and loss functions, whereas torchvision.transforms is a separate library that provides common image transformations. Once the PyTorch Lightning framework and all packages are installed, you should see the completion log, as illustrated in the following screenshot:

Figure 1.5 – Installation result for PyTorch Lightning

Once PyTorch Lightning is installed you can check the version for PyTorch and torch

Figure 1.6 – Verifying the installation

That's it! Now, you are all set to begin your Lightning adventure!