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Use maxint to bound integers. #96121
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We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyang@meta.com> [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/96121
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We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyangmeta.com> ghstack-source-id: 0d97be5eab9c2ff74e64e9c799f5a491777a0482 Pull Request resolved: #96121
We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyangmeta.com> [ghstack-poisoned]
We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyangmeta.com> ghstack-source-id: cefcf018e6c1fcebc48b1678142711ce09596465 Pull Request resolved: #96121
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What was the issue with the previous code ?
Could we remove guards that check for INT_MAX instead ? it's not obvious from the code why we wouldn't be using |
Yes i plan to do this. |
Elias I will post the test case for this; the problem is we have some code testing for int_max |
We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyangmeta.com> [ghstack-poisoned]
We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyangmeta.com> ghstack-source-id: c3589d3b055eef89470648814b238ccff4098067 Pull Request resolved: #96121
@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Merge failedReason: 1 mandatory check(s) failed. The first few are: Dig deeper by viewing the failures on hud |
We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyangmeta.com> [ghstack-poisoned]
We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyangmeta.com> ghstack-source-id: 8b18d4ef39ff66862d6288f66d645dd495c8bf1b Pull Request resolved: #96121
@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Merge failedReason: 1 jobs have failed, first few of them are: trunk / linux-bionic-cuda11.8-py3.10-gcc7 / test (default, 3, 4, linux.4xlarge.nvidia.gpu) Details for Dev Infra teamRaised by workflow job |
@pytorchbot merge -f "unrelated timeout" |
Merge startedYour change will be merged immediately since you used the force (-f) flag, bypassing any CI checks (ETA: 1-5 minutes). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyang@meta.com> Pull Request resolved: pytorch#96121 Approved by: https://github.com/tugsbayasgalan, https://github.com/lezcano
We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyang@meta.com> Pull Request resolved: pytorch/pytorch#96121 Approved by: https://github.com/tugsbayasgalan, https://github.com/lezcano
We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyang@meta.com> Pull Request resolved: pytorch/pytorch#96121 Approved by: https://github.com/tugsbayasgalan, https://github.com/lezcano
We don't actually support arbitrary precision integers. Signed-off-by: Edward Z. Yang <ezyang@meta.com> Pull Request resolved: pytorch#96121 Approved by: https://github.com/tugsbayasgalan, https://github.com/lezcano
Stack from ghstack (oldest at bottom):
We don't actually support arbitrary precision integers.
Signed-off-by: Edward Z. Yang ezyang@meta.com