Metal backend: track tensors

[manuelcandales]

This pull request refactors and improves the memory management and reference counting system for tensors in the Metal backend. The main change is the replacement of the previous ownership tracking (is_tensor_own_memory) with a more robust reference counting map (memory_to_n_tensor), which tracks how many tensors share a memory address and whether the memory is owned or not. Additional improvements include safer tensor deletion, proper Metal buffer deallocation, and consistent handling of tensor views and resource cleanup.

[manuelcandales]

Stack from ghstack (oldest at bottom):

• Metal backend: Add MPSGraph caching #15346
• Metal backend: eliminate memory leak #15343
• -> Metal backend: track tensors #15342
• Metal backend: store weights outside .so #15341

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15342

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❌ 1 New Failure, 3 Pending, 2 Unrelated Failures

As of commit 5bd34ee with merge base 5d71c9b ():

NEW FAILURE - The following job has failed:

• pull / unittest-nxp-neutron / linux-job (gh)
  RuntimeError: Command docker exec -t f00a9215ce4155a6b95faf21a9ddf346ec7007693272a157772b60d2e51c48f4 /exec failed with exit code 1

BROKEN TRUNK - The following jobs failed but were present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

• pull / unittest / linux / linux-job (gh) (trunk failure)
• pull / unittest-editable / linux / linux-job (gh) (trunk failure)

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