[ROCm][Test] Use platform FP8 dtype in ModelOpt FP8_PB_WO test

[djramic]

Purpose

quantization/test_modelopt.py::test_modelopt_fp8_pb_wo_checkpoint_setup failed on MI300. The test loads a ModelOpt FP8_PB_WO checkpoint and checks that the linear layer weights have the expected FP8 dtype, but it hardcoded torch.float8_e4m3fn.

On ROCm, FP8 weights are stored as e4m3fnuz. After #53132, the ModelOpt FP8_PB_WO weight post-processing path started running on load and converted the weights to the platform FP8 dtype. The test still expected the old hardcoded dtype, so it failed with: assert torch.float8_e4m3fnuz == torch.float8_e4m3fn

This change updates the test to resolve the expected dtype via current_platform.fp8_dtype() and compare the loaded weight dtypes against the platform FP8 dtype instead of hardcoded torch.float8_e4m3fn

Test Plan

pytest tests/quantization/test_modelopt.py on MI300X.

Test Result

Before:
1 failed, 19 passed, 4 skipped
After:
20 passed, 4 skipped

Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

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[claude]

Claude Code Review

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[AndreasKaratzas]

/ci run

[github-actions]

✅ Triggered Buildkite CI #85032 for commit 6c496f61b13a.