fix(inductor): ForeachKernelSchedulerNode group shape should be opaque for graph debug
#110336
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/110336
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ForeachKernelSchedulerNode group shape should be opaque for graph debug
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Oct 11, 2023
I think let's leave opaque for now. It'll be quite difficult to read when listing all shapes. |
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…que for graph debug (pytorch#110336) ~~Shape is assumed by `TensorMetadata` to be torch.Shape/tuple, however, some of the scheduler node groups utilize `int`, so convert to tuple.~~ Root cause is actually `foreach` scheduler node having silent-error group of int, when in fact it ought to be opaque `foreach`. **Previously:** silent error / confusing shape of (0,)  **Now:** clear that it is foreach which does not have well-defined shape:  ~~Alternate might be to create list of shapes for each of its subnodes. Actually, for debuggability sake, I may prefer this. We can ensure that the recursive generation of this string is only done dynamically in a debug code path. Else, incrementally computing it on initialization of ForeachKernel may also be feasible.~~ This is quite infeasible for 100s of params. Pull Request resolved: pytorch#110336 Approved by: https://github.com/mlazos
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…que for graph debug (pytorch#110336) ~~Shape is assumed by `TensorMetadata` to be torch.Shape/tuple, however, some of the scheduler node groups utilize `int`, so convert to tuple.~~ Root cause is actually `foreach` scheduler node having silent-error group of int, when in fact it ought to be opaque `foreach`. **Previously:** silent error / confusing shape of (0,)  **Now:** clear that it is foreach which does not have well-defined shape:  ~~Alternate might be to create list of shapes for each of its subnodes. Actually, for debuggability sake, I may prefer this. We can ensure that the recursive generation of this string is only done dynamically in a debug code path. Else, incrementally computing it on initialization of ForeachKernel may also be feasible.~~ This is quite infeasible for 100s of params. Pull Request resolved: pytorch#110336 Approved by: https://github.com/mlazos
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Shape is assumed byTensorMetadatato be torch.Shape/tuple, however, some of the scheduler node groups utilizeint, so convert to tuple.Root cause is actually
foreachscheduler node having silent-error group of int, when in fact it ought to be opaqueforeach.Previously: silent error / confusing shape of (0,)
Now: clear that it is foreach which does not have well-defined shape:
Alternate might be to create list of shapes for each of its subnodes. Actually, for debuggability sake, I may prefer this. We can ensure that the recursive generation of this string is only done dynamically in a debug code path. Else, incrementally computing it on initialization of ForeachKernel may also be feasible.This is quite infeasible for 100s of params.cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @Xia-Weiwen @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @aakhundov @ColinPeppler