download_and_freeze_pretrained_vgg.py

# Get the "features" portion of VGG19
# The classifier portion is not needed for style transfer
vgg = models.vgg19(pretrained=True).features

# Freeze all VGG parameters
# Since only activations are measured for each conv layer
# Network weights aren't modified
for param in vgg.parameters():
    param.requires_grad_(False)

# Move the model to GPU, if available
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
vgg.to(device)

print(vgg)