[ET Device Support] Add NonConstBufferDevice schema for per-buffer device mapping

[Gasoonjia]

Stack from ghstack (oldest at bottom):

• -> [ET Device Support] Add NonConstBufferDevice schema for per-buffer device mapping #18330
• [ET Device Support] DeviceAllocator interface and DeviceAllocatorRegistry #17535
• [ET Device Support] Annotate device attributes of CUDA backend IO tensors cuda device #18080
• [ET Device Support] Parse device info from serialized tensor in tensor_parser #18328
• [ET Device Support] Propagate device info from TensorSpec into serialized Tensor #18079
• [executorch] Propagate device metadata from partitioner result onto TensorSpecs #18078
• [ET Device Support] TensorImpl carries device info #17534
• [ET Device Support] Schema changes: device info on Tensor and buffer-level device array #17533

Adds the NonConstBufferDevice table to the FlatBuffer schema (program.fbs) and the
corresponding Python dataclass to schema.py. This enables mapping each non-constant
planned memory buffer to a specific device type (CPU, CUDA, etc.).

The field is optional and absent for CPU-only programs, ensuring zero binary size regression.

Differential Revision: D97335597

[pytorch-bot]

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❌ 1 New Failure, 3 Pending, 1 Unrelated Failure

As of commit c2cb7ac with merge base bf2243a ():

NEW FAILURE - The following job has failed:

• pull / test-multimodal-linux (gemma3-4b) / linux-job (gh)
  RuntimeError: Command docker exec -t f9eada7ac024ca8e52763fd083e0596d3e64bb995ff9dc6c6f4955c8af0b2a06 /exec failed with exit code 139

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

• pull / unittest-arm-backend-with-no-deps (test_pytest_models_tosa) / linux-job (gh) (detected as infra flaky with no log or failing log classifier)

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