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pytorch-bot bot commented Jan 23, 2026

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/16833

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❌ 2 New Failures, 1 Unrelated Failure

As of commit dbf00c4 with merge base b928496 (image):

NEW FAILURES - The following jobs have failed:

FLAKY - The following job failed but was likely due to flakiness present on trunk:

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@meta-cla meta-cla bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Jan 23, 2026
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This PR needs a release notes: label

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cccclai commented Jan 23, 2026

@haowhsu-quic @winskuo-quic @shewu-quic @DannyYuyang-quic any chance you know a good way to handle this patch?

@JacobSzwejbka JacobSzwejbka marked this pull request as ready for review January 23, 2026 19:21
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meta-codesync bot commented Jan 23, 2026

@JacobSzwejbka has imported this pull request. If you are a Meta employee, you can view this in D91345139.

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Thanks for fixing it.

start, end = node.args[0:2]
step = node.args[2] if len(node.args) > 2 else 1
out_tensor = torch.arange(start, end, step)
dtype = node.kwargs.get("dtype")
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How about use node.meta["val"].dtype? I think it will not be None.

f"Output {i} mismatch: got {out}, expected {ref}",
)

def test_arange_dtype_from_kwargs(self):
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Could you reuse original unit test for arange op?
Such as add more dtype coverage.

def test_qnn_backend_arange(self):

def test_qnn_backend_arange(self):

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