Fix torchao quantization for deployment targets under iOS18

[metascroy]

_construct_constexpr_dequant_op should use axis = None (default value), rather than -1. This will infer the axis from the shape of scales.

On iOS18, this was not an issue because the axis is not used. For iOS16, the axis is used and the value -1 usually caused an issue during export.

[pytorch-bot]

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As of commit fc4e8fe with merge base b02db12 ():

NEW FAILURES - The following jobs have failed:

• Build documentation / build (buck2) / Build doc (gh)
  At least one of the pre-conditions you specified did not hold
• pull / unittest-arm-backend-with-no-fvp (test_pytest_ops) / linux-job (gh)
  RuntimeError: Command docker exec -t 71421c8a19c32954d6dc8597ad11944a92374156b2a6fa76d8f243fc08b5aeea /exec failed with exit code 1
• pull / unittest-nxp-neutron / linux-job (gh)
  RuntimeError: Command docker exec -t 9e05cd7faea74b1cc7fadf411b3e5a8d2bf9638177f210ed4c073029eb955777 /exec failed with exit code 1

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[metascroy]

Fixes #13122

[metascroy]

FYI to @abhinaykukkadapu. Per-channel 8-bit TorchAO quantization is now supported on iOS16+ with this PR. We can follow up with recipe update.

[jackzhxng]

Passing reminder to use release notes: quantization if you think we should call out this bug fix on the release notes

[metascroy]

@cccclai @digantdesai @abhinaykukkadapu @jackzhxng I need a stamp from someone in PyTorch to merge. The Apple engineer has already approved.