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Drop two no-op cpu() calls in the k-means cuda path #2835

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Drop two no-op cpu() calls in the k-means cuda path #2835

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4 changes: 0 additions & 4 deletions coremltools/optimize/torch/_utils/k_means.py
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Expand Up @@ -675,10 +675,6 @@ def _cluster_weights_2d(
max_iter=300,
).fit(weight_2d, sample_weight=importance_2d)

weight_2d.cpu()

@TobyRoseman TobyRoseman Sep 30, 2026

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Looks like weight_2d could potentially be running on CUDA, see line 666.

@darkdi darkdi Oct 1, 2026

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Yes, it can be on CUDA. Tensor.cpu() returns a CPU copy without changing the source tensor, so these two calls discard that copy and leave weight_2d and importance_2d on CUDA. The .cpu() calls on the returned centers and labels are still there. PyTorch docs.

if importance_2d is not None:
importance_2d.cpu()

return kmeans_results.cluster_centers_.cpu(), kmeans_results.labels_.cpu()

@classmethod
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