[docs][ao] Add missing documentation for torch.quantized_batch_norm

[supriyar]

Stack from ghstack:

• [docs][ao] add missing torch.choose_qparams_optimized documentation #63263
• [docs][ao] Add overload information for fake_quantize_per_tensor_affine #63258
• [docs][ao] Add missing docstrings for quantized_max_pool1d and quantized_max_pool2d #63242
• -> [docs][ao] Add missing documentation for torch.quantized_batch_norm #63240

Summary:
Op is exposed via torch.quantized_batch_norm to the end user without any existing documentation

Test Plan:
CI
Reviewers:

Subscribers:

Tasks:

Tags:

Differential Revision: D30316431

[facebook-github-bot]

🔗 Helpful links

• 🧪 See artifacts and rendered test results at hud.pytorch.org/pr/63240
• 📄 Preview docs built from this PR

💊 CI failures summary and remediations

As of commit 3f292c5 (more details on the Dr. CI page):

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• 1/2 failures introduced in this PR
• 1/2 broken upstream at merge base 2d75703 from Aug 12 until Aug 13

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1 failure not recognized by patterns:

Job	Step	Action
Lint / shellcheck	Assert that regenerating the workflows didn't change them	🔁 rerun

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1 job timed out:

• pytorch_linux_xenial_py3_clang7_asan_test1

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🚧 1 fixed upstream failure:

These were probably caused by upstream breakages that were already fixed.

Please rebase on the viable/strict branch (expand for instructions)

If your commit is older than viable/strict, run these commands:

git fetch https://github.com/pytorch/pytorch viable/strict
git rebase FETCH_HEAD

• pytorch_linux_xenial_py3_clang7_asan_test1 from Aug 12 until Aug 13 (741accb - cb23976)
  • 🔁 rerun

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[supriyar]

@supriyar has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

[raghuramank100]

Can we also specify that weight , bias and other tensors are in floating point?

[supriyar]

@supriyar has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

[facebook-github-bot]

This pull request has been merged in a090073.