[executorch][native] Add Node to the in-memory IR - #22102
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/22102
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Stack from ghstack (oldest at bottom):
Adds
ptn::Node, the central IR element: one fx node = one op invocation(
CallFunction) or a graph-boundary marker (Placeholder/Output). It pullstogether the value layer landed so far --
NamedArgument/Argumentforoperands,
ValueReffor produced values -- and mirrors the schemaNode.Nodeis a plain struct (name,OpKind, target fqn,inputs,outputs, and atransient
attrsscratch map, the fxnode.metaanalog). Two satellite typesland with it:
OpKind(CallFunction / Placeholder / Output), pinned to the schema ids.Output+OutputValueKind(Tensor / TensorList / Int / Bool / Float). Thereturn-ABI grouping is preserved so a later engine-translation stage can tell
a single result from a tuple / list:
topkemits twoTensoroutputs,splitemits oneTensorListoutput,sym_sizeemits anIntoutput.OutputValueKinddeliberately matches the schema's node-level enum name toavoid colliding with the graph-level
OutputKind(user output vs buffermutation) that lands with
Method. The storage-alias fact stays on theproduced
Value, not onOutput..cppholds the two non-trivial members:input_value_refs()walks theArgumentvariants and collects every consumedValueRef(tensor args,tensor-list / optional-list elements, and symbolic scalar refs;
kInvalidskipped) for (re)building def-use wiring; and
to_string()renders a singlecompact line for debugging.
Pure std only (no ExecuTorch, no flatbuffers), consistent with the rest of the
standalone
ptnruntime.Differential Revision: D114396763