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[PT2][Optimus][Reliability]Fix a bug in gradients computation for runtime numeric check #118105

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[PT2][Optimus][Reliability]Fix a bug in gradients computation for runtime numeric check #118105

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@mengluy0125 mengluy0125 commented Jan 23, 2024 •
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Summary:
We observed the following error when launch e2e AFOC model test

RuntimeError: Trying to backward through the graph a second time (or directly access saved tensors after they have already been freed). Saved intermediate values of the graph are freed when you call .backward() or autograd.grad(). Specify retain_graph=True if you need to backward through the graph a second time or if you need to access saved tensors after calling backward.

f524190245

Differential Revision: D53011463

cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @aakhundov @ColinPeppler

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pytorch-bot bot commented Jan 23, 2024 •
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/118105

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

✅ You can merge normally! (2 Unrelated Failures)

As of commit 2f16436 with merge base 5b671ce (image):

UNSTABLE - The following jobs failed but were likely due to flakiness present on trunk and has been marked as unstable:

This comment was automatically generated by Dr. CI and updates every 15 minutes.

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This pull request was exported from Phabricator. Differential Revision: D53011463

mengluy0125 added a commit to mengluy0125/pytorch that referenced this pull request Jan 23, 2024
@mengluy0125 @facebook-github-bot
[PT2][Optimus][Reliability]Fix a bug in gradients computation for run…
aa35ad1 
…time numeric check (pytorch#118105)

Summary:

We observed the following error when launch e2e AFOC model test
```
RuntimeError: Trying to backward through the graph a second time (or directly access saved tensors after they have already been freed). Saved intermediate values of the graph are freed when you call .backward() or autograd.grad(). Specify retain_graph=True if you need to backward through the graph a second time or if you need to access saved tensors after calling backward.
```
f524190245

Test Plan:
'training_platform:c640e3f93574472da8894d9a0365f6a0'

f524376722
P1086047304

Differential Revision: D53011463
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This pull request was exported from Phabricator. Differential Revision: D53011463

@pytorch-bot pytorch-bot bot added the ciflow/trunk Trigger trunk jobs on your pull request label Jan 23, 2024
@mengluy0125 @facebook-github-bot
[PT2][Optimus][Reliability]Fix a bug in gradients computation for run…
2f16436 
…time numeric check (pytorch#118105)

Summary:

We observed the following error when launch e2e AFOC model test
```
RuntimeError: Trying to backward through the graph a second time (or directly access saved tensors after they have already been freed). Saved intermediate values of the graph are freed when you call .backward() or autograd.grad(). Specify retain_graph=True if you need to backward through the graph a second time or if you need to access saved tensors after calling backward.
```
f524190245

Test Plan:
'training_platform:c640e3f93574472da8894d9a0365f6a0'

f524376722
P1086047304

Reviewed By: jackiexu1992

Differential Revision: D53011463
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This pull request was exported from Phabricator. Differential Revision: D53011463

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@pytorchbot merge -f 'Landed internally'

(Initiating merge automatically since Phabricator Diff has merged, using force because this PR might not pass merge_rules.json but landed internally)

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Merge started

Your change will be merged immediately since you used the force (-f) flag, bypassing any CI checks (ETA: 1-5 minutes). Please use -f as last resort and instead consider -i/--ignore-current to continue the merge ignoring current failures. This will allow currently pending tests to finish and report signal before the merge.

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