[executorch][native] Add Node to the in-memory IR

[SS-JIA]

Stack from ghstack (oldest at bottom):

• [executorch][native] Add Method + ValueRole to the in-memory IR #22281
• [executorch][native] Add Graph index arena to the in-memory IR #22280
• -> [executorch][native] Add Node to the in-memory IR #22279
• [executorch][native] Add Argument tagged union to the in-memory IR #22278
• [executorch][native] Add Value + index-arena ids to the in-memory IR #22277
• [executorch][native] Add Scalar value type to the in-memory IR #22276
• [executorch][native] Add TensorMeta + ScalarType in-memory IR types #22275
• [executorch][native] Add native runtime Program reader + DOT visualizer #22274

Adds ptn::Node, the central IR element: one fx node = one op invocation
(CallFunction) or a graph-boundary marker (Placeholder / Output). It pulls
together the value layer landed so far -- NamedArgument / Argument for
operands, ValueId for produced values -- and mirrors the schema Node.

Node is a plain struct (name, OpKind, target fqn, inputs, outputs, and a
transient attrs scratch map, the fx node.meta analog). Two satellite types
land with it:

• OpKind (CallFunction / Placeholder / Output), pinned to the schema ids.
• Output + OutputValueKind (Tensor / TensorList / Int / Bool / Float). The
  return-ABI grouping is preserved so a later engine-translation stage can tell
  a single result from a tuple / list: topk emits two Tensor outputs,
  split emits one TensorList output, sym_size emits an Int output.
  OutputValueKind deliberately matches the schema's node-level enum name to
  avoid colliding with the graph-level OutputKind (user output vs buffer
  mutation) that lands with Method. The storage-alias fact stays on the
  produced Value, not on Output.

.cpp holds the one non-trivial member: input_value_ids() walks the
Argument variants and collects every consumed ValueId (tensor args,
tensor-list / optional-list elements, and symbolic scalar ids; kInvalid
skipped) for (re)building def-use wiring. The IR printer gains
to_string(const Node&), which renders a single compact line for debugging.

Pure std only (no ExecuTorch, no flatbuffers), consistent with the rest of the
standalone ptn runtime.

Differential Revision: D114396763

[pytorch-bot]

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✅ You can merge normally! (1 Unrelated Failure)

As of commit f1cdf75 with merge base a5f15b5 ():

FLAKY - The following job failed but was likely due to flakiness present on trunk:

• pull / test-qnn-testsuite-linux / test-backend-linux (qnn, models) / linux-job (gh) (detected as infra flaky with no log or failing log classifier)

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