[executorch][native] Add native runtime Program reader + DOT visualizer

[SS-JIA]

Stack from ghstack (oldest at bottom):

• [executorch][native] Add Argument tagged union to the in-memory IR #22235
• [executorch][native] Add Value + index-arena ids to the in-memory IR #22221
• [executorch][native] Add Scalar value type to the in-memory IR #22220
• [executorch][native] Add TensorMeta + ScalarType in-memory IR types #22219
• -> [executorch][native] Add native runtime Program reader + DOT visualizer #22218

First C++ runtime components for the native backend, under
backends/native/runtime/:

• ptn::Program (Program.h / Program.cpp): a standalone reader that parses
  and verifies a serialized native graph (*.nptg). Program::load() copies
  the bytes, checks the NPTG FlatBuffer file identifier, runs the FlatBuffer
  verifier, and exposes a zero-copy view of the root; it throws
  std::runtime_error on failure. No ExecuTorch or torch dependency
  (flatbuffers only); exceptions allowed. Our sources build as C++20 -- the
  --cpp-std c++11 in the genrule sets the feature level of the generated
  accessors, not ours (flatc accepts only c++0x / c++11 / c++17).
• ptn::to_dot(const Program&) (utils/ToDot.h / utils/ToDot.cpp): renders
  the program to Graphviz DOT text -- methods as clusters, dataflow / def-use
  as labeled edges, tensor metadata, constants, alias / mutation facts, quant,
  and HOP subgraphs. Pure string builder, no I/O. Doubles as the reference walk
  of native_backend::Program.

The renderer is a free function in its own :to_dot target rather than a
Program member, so a link that only reads programs does not carry it:
:runtime depends on the generated schema alone, while :to_dot pulls in
graph:format.

Also wires a --dot flag into the native_executor tool: load + verify via the
reader, then print the DOT to stdout.

The schema header is generated from serialization/native_graph.fbs via a
flatc genrule (:native_graph_schema). Mirrored into both the fbcode/ and
xplat/ trees to match the native backend layout.

Authored with Claude Code.

Differential Revision: D114396768

[pytorch-bot]

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