[5951713] Fix benchmark allocation failure

[willg-nv]

What does this PR do?

[modelopt][onnx] - ERROR - Benchmark failed: Converting dtype('float16') to a ctypes type
Traceback (most recent call last):
...
    raise NotImplementedError(
NotImplementedError: Converting dtype('float16') to a ctypes type

Usage

# Add a code snippet demonstrating how to use this

Testing

Before your PR is "Ready for review"

Make sure you read and follow Contributor guidelines and your commits are signed (git commit -s -S).

Make sure you read and follow the Security Best Practices (e.g. avoiding hardcoded trust_remote_code=True, using torch.load(..., weights_only=True), avoiding pickle, etc.).

• Is this change backward compatible?: ✅ / ❌ / N/A
• If you copied code from any other source, did you follow IP policy in CONTRIBUTING.md?: ✅ / ❌ / N/A
• Did you write any new necessary tests?: ✅ / ❌ / N/A
• Did you update Changelog?: ✅ / ❌ / N/A

Additional Information

Summary by CodeRabbit

Release Notes

• Bug Fixes
  • Improved dtype handling robustness in host memory allocation to avoid failures for uncommon numeric types.
  • Added fallback support for 2-byte floating-point formats (float16, bfloat16); clearer errors now raised when a dtype is unsupported.

[copy-pr-bot]

This pull request requires additional validation before any workflows can run on NVIDIA's runners.

Pull request vetters can view their responsibilities here.

Contributors can view more details about this message here.

[coderabbitai]

No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Pro

Run ID: 3287b5fa-98e6-430e-a6d8-68244fbe7a7d

📥 Commits

Reviewing files that changed from the base of the PR and between 06ce30b and 7345b99.

📒 Files selected for processing (1)

• modelopt/onnx/quantization/autotune/benchmark.py

🚧 Files skipped from review as they are similar to previous changes (1)

• modelopt/onnx/quantization/autotune/benchmark.py

---

📝 Walkthrough

Walkthrough

Normalize dtype to np.dtype in _alloc_pinned_host, attempt a ctypes-based view of allocated host memory, fall back to allocating as uint16 and viewing as the requested 2-byte dtype when ctypes mapping is missing, and raise TypeError if neither is possible; return path unchanged on success.

Changes

Cohort / File(s)	Summary
Dtype / Memory-allocation logic modelopt/onnx/quantization/autotune/benchmark.py	Explicitly convert dtype to np.dtype before computing itemsize; try to create a ctypes-based view of allocated host memory; if no ctypes mapping for 2-byte float types, allocate as uint16 and view as requested dtype; raise TypeError when unsupported. Highlights: ctypes fallback for 2-byte types, unchanged success/error return behavior.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~10 minutes

🚥 Pre-merge checks | ✅ 4

✅ Passed checks (4 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly identifies the specific issue being fixed (benchmark allocation failure) and matches the core change in the changeset (fixing NotImplementedError in memory allocation).
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.
Security Anti-Patterns	✅ Passed	The pull request introduces no new security anti-patterns. Modifications to benchmark.py are limited to the _alloc_pinned_host function, adding dtype normalization and ctypes-based fallback for 2-byte float types, with no involvement of critical security patterns.

_{✏️ Tip: You can configure your own custom pre-merge checks in the settings.}

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment

---

_{Comment @coderabbitai help to get the list of available commands and usage tips.}

[willg-nv]

@gcunhase please help review this PR.

[gcunhase]

/ok to test 06ce30b

[codecov]

Codecov Report

❌ Patch coverage is 0% with 10 lines in your changes missing coverage. Please review.
✅ Project coverage is 72.08%. Comparing base (a34d613) to head (7345b99).
⚠️ Report is 9 commits behind head on main.

Files with missing lines	Patch %	Lines
modelopt/onnx/quantization/autotune/benchmark.py	0.00%	10 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #978      +/-   ##
==========================================
- Coverage   72.10%   72.08%   -0.02%     
==========================================
  Files         209      209              
  Lines       23628    23638      +10     
==========================================
+ Hits        17036    17040       +4     
- Misses       6592     6598       +6     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

[gcunhase]

/ok to test 7345b99