relax tolerances for all unary float ops #9585
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9585
Note: Links to docs will display an error until the docs builds have been completed. ⏳ No Failures, 37 PendingAs of commit ca9db4c with merge base bc42d8d ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This was referenced May 28, 2025
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manuelcandales
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May 30, 2025
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starting stacked land, noting that CI is green (android / run-emulator was known flaky) |
JacobSzwejbka
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Jun 10, 2025
This reverts commit 2dedc9e.
swolchok
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Jun 24, 2025
…portedTensorDtypes::BOOL (#9584)", new op_mul test (#11206) These were reverted because they were part of a stack with interenal test failures. Original #9585 summary: We were requiring ourselves to compute at double-precision, but ATen actually converts non-floating-point types to `float` by default, not `double`. Use the ATen tolerances everywhere. Original #9584 summary: none Original #11206 summary: This tests a possibly-surprising result: int8(100) * int8(100) with output type of long is 16 in ATen, even though the output type can hold 10000. Differential Revision: [D76754823](https://our.internmc.facebook.com/intern/diff/D76754823/) [ghstack-poisoned]
swolchok
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…portedTensorDtypes::BOOL (#9584)", new op_mul test (#11206) These were reverted because they were part of a stack with interenal test failures. Original #9585 summary: We were requiring ourselves to compute at double-precision, but ATen actually converts non-floating-point types to `float` by default, not `double`. Use the ATen tolerances everywhere. Original #9584 summary: none Original #11206 summary: This tests a possibly-surprising result: int8(100) * int8(100) with output type of long is 16 in ATen, even though the output type can hold 10000. Differential Revision: [D76754823](https://our.internmc.facebook.com/intern/diff/D76754823/) [ghstack-poisoned]
swolchok
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Jun 24, 2025
…portedTensorDtypes::BOOL (#9584)", new op_mul test (#11206) These were reverted because they were part of a stack with interenal test failures. Original #9585 summary: We were requiring ourselves to compute at double-precision, but ATen actually converts non-floating-point types to `float` by default, not `double`. Use the ATen tolerances everywhere. Original #9584 summary: none Original #11206 summary: This tests a possibly-surprising result: int8(100) * int8(100) with output type of long is 16 in ATen, even though the output type can hold 10000. Differential Revision: [D76754823](https://our.internmc.facebook.com/intern/diff/D76754823/) [ghstack-poisoned]
swolchok
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Jun 24, 2025
…portedTensorDtypes::BOOL (#9584)", new op_mul test (#11206) These were reverted because they were part of a stack with interenal test failures. Original #9585 summary: We were requiring ourselves to compute at double-precision, but ATen actually converts non-floating-point types to `float` by default, not `double`. Use the ATen tolerances everywhere. Original #9584 summary: none Original #11206 summary: This tests a possibly-surprising result: int8(100) * int8(100) with output type of long is 16 in ATen, even though the output type can hold 10000. Differential Revision: [D76754823](https://our.internmc.facebook.com/intern/diff/D76754823/) [ghstack-poisoned]
kedarnath03
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Jun 25, 2025
We were requiring ourselves to compute at double-precision, but ATen actually converts non-floating-point types to float by default, not double. Use the ATen tolerances everywhere ghstack-source-id: 8293280 ghstack-comment-id: 2751961338 Pull Request resolved: pytorch/executorch#9585
kedarnath03
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Jun 25, 2025
We were requiring ourselves to compute at double-precision, but ATen actually converts non-floating-point types to float by default, not double. Use the ATen tolerances everywhere ghstack-source-id: 189313b ghstack-comment-id: 2751961338 Pull Request resolved: pytorch/executorch#9585
swolchok
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Jun 26, 2025
…portedTensorDtypes::BOOL (#9584)", new op_mul test (#11206) (#11976) This PR was created by the merge bot to help merge the original PR into the main branch. ghstack PR number: #11942 by @swolchok ^ Please use this as the source of truth for the PR details, comments, and reviews ghstack PR base: https://github.com/pytorch/executorch/tree/gh/swolchok/473/base ghstack PR head: https://github.com/pytorch/executorch/tree/gh/swolchok/473/head Merge bot PR base: https://github.com/pytorch/executorch/tree/main Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/swolchok/473/orig @diff-train-skip-merge Co-authored-by: Scott Wolchok <swolchok@meta.com>
hinriksnaer
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Jun 26, 2025
…Add SupportedTensorDtypes::BOOL (pytorch#9584)", new op_mul test (pytorch#11206) (pytorch#11976) This PR was created by the merge bot to help merge the original PR into the main branch. ghstack PR number: pytorch#11942 by @swolchok ^ Please use this as the source of truth for the PR details, comments, and reviews ghstack PR base: https://github.com/pytorch/executorch/tree/gh/swolchok/473/base ghstack PR head: https://github.com/pytorch/executorch/tree/gh/swolchok/473/head Merge bot PR base: https://github.com/pytorch/executorch/tree/main Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/swolchok/473/orig @diff-train-skip-merge Co-authored-by: Scott Wolchok <swolchok@meta.com>
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We were requiring ourselves to compute at double-precision, but ATen actually converts non-floating-point types to
floatby default, notdouble. Use the ATen tolerances everywhere.