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torch 2.14 rejects group_norm inputs with an empty channel or spatial
extent ("Expected number of channels to be greater than 0", "Expected HxW
to be greater than 0"); 2.13 and earlier accepted them. The sample
generator builds shapes from (0, 2) in every dim, so the torch reference
failed on inputs it now refuses. An empty batch is still accepted, so only
channels and the spatial dims are filtered.
The boundary is 2.14, not 2.13, hence the new constant.
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What does this PR do?
Skips the
group_normsamples that torch 2.14 no longer accepts.Problem: torch 2.14 rejects
group_norminputs with an empty channel or spatial dim (Expected number of channels to be greater than 0). The sample generator builds shapes from(0, 2), so torch's reference now fails on some samples. Thunder'sgroup_normis fine.Fix: skip those samples on torch 2.14+, gated on a new
_TORCH_GREATER_EQUAL_2_14inthunder/constants.py. Older torch still covers them, and empty-batch samples stay.Related CI: the only failure in all eight grads and ops jobs:
pytester (ubuntu-22.04 / macOS-15, 3.10, latest / nightly, grads):test_vjp_correctness_group_normpytester (ubuntu-22.04 / macOS-15, 3.10, latest / nightly, ops):test_core_vs_torch_consistency_group_normCI log (
pytester (ubuntu-22.04, 3.10, latest, ops), on #2842)Part 7 of the breakdown of #2832.