Please see appendix (attached in the Canvas comment) for usage instructions

example.py

# example.py

from common import setup
import torch.nn.functional as F

args, model, data_module = setup()
test_data_loader = data_module.test_dataloader()

for batch in iter(test_data_loader):
    inputs, targets = batch
    logits = model(inputs).view(-1, 8 * 8)
    y = F.softmax(logits, dim=1)

    preds = y.argmax(dim=1)
    top3 = logits.topk(k=3, dim=1).indices.t()
    top1_acc = (preds == targets).sum().item() / len(targets)
    top3_acc = (top3 == targets).sum().item() / len(targets)

    print("labels:      {}".format(targets))
    print("predictions: {}".format(preds))
    print("top-1 acc: {:.3f}".format(top1_acc))
    print("top-3 acc: {:.3f}".format(top3_acc))

    break

Please see appendix on page 7 for instructions:

https://canvas.sfu.ca/courses/59125/assignments/624347/submissions/120605?comment_id=4027731&download=15818284