8000 Analyze coalesced mem by eellison · Pull Request #153730 · pytorch/pytorch · GitHub
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Analyze coalesced mem #153730

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@eellison eellison commented May 16, 2025 •
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/153730

Note: Links to docs will display an error until the docs builds have been completed.

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❌ 13 New Failures, 1 Unrelated Failure

As of commit f8728a3 with merge base 5d316ce (image):

NEW FAILURES - The following jobs have failed:

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

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eellison added a commit that referenced this pull request May 16, 2025
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Analyze coalesced mem
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ghstack-source-id: 577c64b
Pull Request resolved: #153730
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This PR needs a release notes: label

If your changes are user facing and intended to be a part of release notes, please use a label starting with release notes:.

If not, please add the topic: not user facing label.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "topic: not user facing"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

@eellison eellison requested a review from jansel May 16, 2025 15:18
Skylion007
Skylion007 reviewed May 16, 2025
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torch/_inductor/tiling_utils.py
variables[v] = 1
try:
new_val = sympy_subs(index, variables)
except ZeroDivisionError:
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We don't want to log anything here?

@eellison eellison mentioned this pull request May 16, 2025
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etaf
etaf reviewed May 17, 2025
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test/inductor/test_loop_ordering.py

y_dtype = torch.float if not downcast_transposed_v else torch.float64
foo(
torch.rand(256, 256, device="cuda"),
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Hi, May I suggest we mark this case as requires_cuda or replace the hardcode cuda with GPU_TYPE here? The cuda will fail on XPU.

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@jansel jansel Awaiting requested review from jansel

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