Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Transfer Learning in Practice
In Chapter 6, we created our own model to classify images in the Rock Paper Scissors
dataset. We’ll use the same dataset here, but, instead of creating another model,
we’ll take AlexNet for a spin!
It all starts with loading a pre-trained model, which can be easily done using
Torchvision’s library of models. There, we find AlexNet, a PyTorch model that
implements the architecture designed by Alex Krizhevsky et al., and alexnet, a
helper function that creates an instance of AlexNet and, optionally, downloads and
loads its pre-trained weights.
Pre-Trained Model
We’ll start by creating an instance of AlexNet without loading its pre-trained
weights just yet:
Loading AlexNet Architecture
1 alex = alexnet(pretrained=False)
2 print(alex)
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