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Update CIFAR10 tutorial to use torchvision v2 transforms and torch.ac… #3882

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sekyondaMeta merged 2 commits into from
May 8, 2026
+10 −9
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Update CIFAR10 tutorial to use torchvision v2 transforms and torch.ac… #3882

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Update CIFAR10 tutorial to use torchvision v2 transforms and torch.ac…
saurabhkthakur May 8, 2026
b30474b
Merge branch 'main' into update_classifier_tutorial
sekyondaMeta May 8, 2026
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19 changes: 10 additions & 9 deletions beginner_source/blitz/cifar10_tutorial.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,7 @@
"""
import torch
import torchvision
import torchvision.transforms as transforms
from torchvision.transforms import v2

########################################################################
# The output of torchvision datasets are PILImage images of range [0, 1].
Expand All @@ -69,9 +69,10 @@
# BrokenPipeError or RuntimeError related to multiprocessing, try setting
# the num_worker of torch.utils.data.DataLoader() to 0.

transform = transforms.Compose(
[transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])
transform = v2.Compose([
v2.ToImage(),
v2.ToDtype(torch.float32, scale=True),
v2.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])

batch_size = 4

Expand Down Expand Up @@ -191,7 +192,7 @@ def forward(self, x):
########################################################################
# Let's quickly save our trained model:

PATH = './cifar_net.pth'
PATH = './cifar_net.pt'
torch.save(net.state_dict(), PATH)

########################################################################
Expand Down Expand Up @@ -302,7 +303,7 @@ def forward(self, x):
# Let's first define our device as the first visible cuda device if we have
# CUDA available:

device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
device = torch.device(torch.accelerator.current_accelerator().type if torch.accelerator.is_available() else 'cpu')

# Assuming that we are on a CUDA machine, this should print a CUDA device:

Expand Down Expand Up @@ -355,9 +356,9 @@ def forward(self, x):
# - `Discuss PyTorch on the Forums`_
# - `Chat with other users on Slack`_
#
# .. _Train a state-of-the-art ResNet network on imagenet: https://github.com/pytorch/examples/tree/master/imagenet
# .. _Train a face generator using Generative Adversarial Networks: https://github.com/pytorch/examples/tree/master/dcgan
# .. _Train a word-level language model using Recurrent LSTM networks: https://github.com/pytorch/examples/tree/master/word_language_model
# .. _Train a state-of-the-art ResNet network on imagenet: https://github.com/pytorch/examples/tree/main/imagenet
# .. _Train a face generator using Generative Adversarial Networks: https://github.com/pytorch/examples/tree/main/dcgan
# .. _Train a word-level language model using Recurrent LSTM networks: https://github.com/pytorch/examples/tree/main/word_language_model
# .. _More examples: https://github.com/pytorch/examples
# .. _More tutorials: https://github.com/pytorch/tutorials
# .. _Discuss PyTorch on the Forums: https://discuss.pytorch.org/
Expand Down
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