Fix bug for comptime.get_local for cells/closures #126637
Closed
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/126637
Note: Links to docs will display an error until the docs builds have been completed. ❌ 1 New Failure, 3 Unrelated FailuresAs of commit 635aab4 with merge base 5ea956a ( NEW FAILURE - The following job has failed:
FLAKY - The following jobs failed but were likely due to flakiness present on trunk:
UNSTABLE - The following job failed but was 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. |
github-actions
bot
requested review from
SherlockNoMad,
albanD,
antoniojkim,
bdhirsh and
miladm
ezyang
added a commit
that referenced
this pull request
May 19, 2024
I wasn't paying enough attention and didn't notice that LOAD_DEREF is defined differently for InliningInstructionTranslator. Match it up with the code there. This also fixes comptime.print(), which was broken, because closing over an argument turned it into a cell rather than a regular local. Signed-off-by: Edward Z. Yang <ezyang@meta.com> ghstack-source-id: 0656df0 Pull Request resolved: #126637
yanboliang
approved these changes
May 20, 2024
|
@pytorchbot merge -f "unrelated failures in ci" |
Merge startedYour change will be merged immediately since you used the force (-f) flag, bypassing any CI checks (ETA: 1-5 minutes). Please use Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
pytorchmergebot
pushed a commit
that referenced
this pull request
May 22, 2024
…or (#126245) This PR requires a little justification, but let's start with what it does first: 1. When you have a 0d CPU scalar int64/float64 tensor input to a graph, we will preallocate a backed SymInt/SymFloat corresponding to what you would get if you call item() on this tensor. This means you can freely change your input to be a Python int/float or a Tensor with an item() call and end up with exactly the same level of expressivity (specifically, you can guard on the internal SymInt/SymFloat no matter what). By default, the source of the backed SymInt/SymFloat is `L['tensor'].item()`, but if you have promoted a float input into a Tensor, we will cancel out `torch.as_tensor(L['float']).item()` into just `L['float']`. 2. We switch wrap_symfloat to use this, instead of hand crafting the new SymNodeVariable. Everything works out, except that we carefully pass the item() result to tracked fakes (and not the fake Tensor argument) OK, so why do this at all? There is some marginal benefit where now some item() calls on scalar inputs can be guarded on, but IMO this is a pretty marginal benefit, and if it was the only reason, I wouldn't do this. The real reason for this is that I need to be able to propagate fake tensors through the graphs that are produced by Dynamo, and if I am doing the old custom wrap_symfloat logic, there's no way I can do this, because ordinarily an item() call will cause an unbacked SymInt when I reallocate. The other obvious way to solve the problem above is to make a HOP alternative that item() that "bakes in" the backed SymInt its supposed to return. But this strategy seems more parsimonious, and it does have the marginal benefit I mentioned above. The main downside is that what I have to do next, is make it so that when I run tensor computation, I also apply the equivalent operations to the SymInt/SymFloat as well. That's next PR. Signed-off-by: Edward Z. Yang <ezyang@meta.com> Pull Request resolved: #126245 Approved by: https://github.com/eellison ghstack dependencies: #126637
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Stack from ghstack (oldest at bottom):
I wasn't paying enough attention and didn't notice that LOAD_DEREF is
defined differently for InliningInstructionTranslator. Match it up with
the code there.
This also fixes comptime.print(), which was broken, because closing over
an argument turned it into a cell rather than a regular local.
Signed-off-by: Edward Z. Yang ezyang@meta.com
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang