[Not to Land (Hopefully)]Revert PT Pin to 0912 #5987
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Summary: Original PR: https://github.com/pytorch/executorch/pull/5824/files Changes picked up in the revert: pytorch@f005dd5#diff-3b0b2409eb2a7cb2dfd94e84c17f54f48243649eb0874b78422b2f1411283d43L169 Differential Revision: D64053532
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/5987
Note: Links to docs will display an error until the docs builds have been completed. ❌ 3 New FailuresAs of commit b2e7687 with merge base 77b1f08 ( NEW FAILURES - The following jobs have failed:
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This pull request was exported from Phabricator. Differential Revision: D64053532 |
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Not to land (hopefully) Testing CI sanctity (whether there were stray deps updates being pulled in) |
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Summary: Did a bunch of debugging on OSS CI:https://github.com/pytorch/executorch/actions/runs/11241297226/job/31252590975 Was able to confirm although the problem happens in `ConvertToLinear` but the root cause is we are partitioning the graph differently between these two pytorch nightly: dev20240916 and dev20240917. The exported graph looks the same but the partitioner was behaving differently and causes the `ConvertToLinear` pass to error out. We can't really revert back to dev20240916 nightly because it breaks other CI jobs, see #5987. The current approach I'm taking avoids decomposing linear by using `to_edge_lower_and_transform` API. This avoids jumping into the rabbit hole of debugging the partitioning & tagging logic. Differential Revision: D64074891
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Summary: Pull Request resolved: #6026 Did a bunch of debugging on OSS CI:https://github.com/pytorch/executorch/actions/runs/11241297226/job/31252590975 Was able to confirm although the problem happens in `ConvertToLinear` but the root cause is we are partitioning the graph differently between these two pytorch nightly: dev20240916 and dev20240917. The exported graph looks the same but the partitioner was behaving differently and causes the `ConvertToLinear` pass to error out. We can't really revert back to dev20240916 nightly because it breaks other CI jobs, see #5987. The current approach I'm taking avoids decomposing linear by using `to_edge_lower_and_transform` API. This avoids jumping into the rabbit hole of debugging the partitioning & tagging logic. Differential Revision: D64074891
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Summary: Did a bunch of debugging on OSS CI:https://github.com/pytorch/executorch/actions/runs/11241297226/job/31252590975 Was able to confirm although the problem happens in `ConvertToLinear` but the root cause is we are partitioning the graph differently between these two pytorch nightly: dev20240916 and dev20240917. The exported graph looks the same but the partitioner was behaving differently and causes the `ConvertToLinear` pass to error out. We can't really revert back to dev20240916 nightly because it breaks other CI jobs, see #5987. The current approach I'm taking avoids decomposing linear by using `to_edge_lower_and_transform` API. This avoids jumping into the rabbit hole of debugging the partitioning & tagging logic. Reviewed By: Jack-Khuu Differential Revision: D64074891
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Oct 8, 2024
Summary: Pull Request resolved: #6026 Did a bunch of debugging on OSS CI:https://github.com/pytorch/executorch/actions/runs/11241297226/job/31252590975 Was able to confirm although the problem happens in `ConvertToLinear` but the root cause is we are partitioning the graph differently between these two pytorch nightly: dev20240916 and dev20240917. The exported graph looks the same but the partitioner was behaving differently and causes the `ConvertToLinear` pass to error out. We can't really revert back to dev20240916 nightly because it breaks other CI jobs, see #5987. The current approach I'm taking avoids decomposing linear by using `to_edge_lower_and_transform` API. This avoids jumping into the rabbit hole of debugging the partitioning & tagging logic. Reviewed By: Jack-Khuu Differential Revision: D64074891
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Oct 8, 2024
Summary: Did a bunch of debugging on OSS CI:https://github.com/pytorch/executorch/actions/runs/11241297226/job/31252590975 Was able to confirm although the problem happens in `ConvertToLinear` but the root cause is we are partitioning the graph differently between these two pytorch nightly: dev20240916 and dev20240917. The exported graph looks the same but the partitioner was behaving differently and causes the `ConvertToLinear` pass to error out. We can't really revert back to dev20240916 nightly because it breaks other CI jobs, see #5987. The current approach I'm taking avoids decomposing linear by using `to_edge_lower_and_transform` API. This avoids jumping into the rabbit hole of debugging the partitioning & tagging logic. Reviewed By: Jack-Khuu Differential Revision: D64074891
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Summary: Did a bunch of debugging on OSS CI:https://github.com/pytorch/executorch/actions/runs/11241297226/job/31252590975 Was able to confirm although the problem happens in `ConvertToLinear` but the root cause is we are partitioning the graph differently between these two pytorch nightly: dev20240916 and dev20240917. The exported graph looks the same but the partitioner was behaving differently and causes the `ConvertToLinear` pass to error out. We can't really revert back to dev20240916 nightly because it breaks other CI jobs, see #5987. The current approach I'm taking avoids decomposing linear by using `to_edge_lower_and_transform` API. This avoids jumping into the rabbit hole of debugging the partitioning & tagging logic. Reviewed By: digantdesai, Jack-Khuu, tugsbayasgalan Differential Revision: D64074891
larryliu0820
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Oct 9, 2024
Summary: Did a bunch of debugging on OSS CI:https://github.com/pytorch/executorch/actions/runs/11241297226/job/31252590975 Was able to confirm although the problem happens in `ConvertToLinear` but the root cause is we are partitioning the graph differently between these two pytorch nightly: dev20240916 and dev20240917. The exported graph looks the same but the partitioner was behaving differently and causes the `ConvertToLinear` pass to error out. We can't really revert back to dev20240916 nightly because it breaks other CI jobs, see #5987. The current approach I'm taking avoids decomposing linear by using `to_edge_lower_and_transform` API. This avoids jumping into the rabbit hole of debugging the partitioning & tagging logic. Reviewed By: digantdesai, Jack-Khuu, tugsbayasgalan Differential Revision: D64074891
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Summary: Pull Request resolved: #6026 Did a bunch of debugging on OSS CI:https://github.com/pytorch/executorch/actions/runs/11241297226/job/31252590975 Was able to confirm although the problem happens in `ConvertToLinear` but the root cause is we are partitioning the graph differently between these two pytorch nightly: dev20240916 and dev20240917. The exported graph looks the same but the partitioner was behaving differently and causes the `ConvertToLinear` pass to error out. We can't really revert back to dev20240916 nightly because it breaks other CI jobs, see #5987. The current approach I'm taking avoids decomposing linear by using `to_edge_lower_and_transform` API. This avoids jumping into the rabbit hole of debugging the partitioning & tagging logic. Reviewed By: digantdesai, Jack-Khuu, tugsbayasgalan Differential Revision: D64074891 fbshipit-source-id: c434f9f5fc240b9268a7419fc66ee4a365ae1664
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Summary:
Original PR: https://github.com/pytorch/executorch/pull/5824/files
Changes picked up in the revert:
f005dd5#diff-3b0b2409eb2a7cb2dfd94e84c17f54f48243649eb0874b78422b2f1411283d43L169
Differential Revision: D64053532