Top-K Accuracy Computation

Implement top-k accuracy metric used for evaluating classification models.

Top-k accuracy checks if the correct class is among the k highest-probability predictions:

$\text{Top-k Acc} = \frac{1}{N} \sum_{i=1}^{N} \mathbf{1}[y_i \in \text{top}_k(\hat{y}_i)]$

For ImageNet, top-5 accuracy is standard (correct class in top 5 predictions).

Implementation:

1. For each sample, get indices of k largest logits (argsort descending)
2. Check if true label is in these k indices
3. Average across all samples