[Bugfix][Quantization] Run block kernel post-processing for ModelOpt FP8_PB_WO

[huthvincent]

Purpose

ModelOptFp8PbWoLinearMethod (ModelOpt block-wise weight-only FP8, FP8_PB_WO)
stores its GEMM kernel as self.w8a8_block_fp8_linear (set in
create_weights). But process_weights_after_loading gated the kernel's own
post-load step on the wrong attribute:

if hasattr(self, "fp8_linear"):
    self.fp8_linear.process_weights_after_loading(layer)

self.fp8_linear is never set on this class (only the two sibling per-tensor
methods use that name), so the condition is always False and the kernel's
process_weights_after_loading is silently skipped. That step performs the
mandatory scale/layout relayout the block GEMM requires — deep_gemm's
e8m0/TMA-aligned scale layout on Hopper/Blackwell, and the e4m3fn -> e4m3fnuz
weight conversion on ROCm. With it skipped, apply() runs the GEMM on
unprocessed weights, producing wrong output (or a deep_gemm assert). The two
sibling FP8 methods call process_weights_after_loading unconditionally.

Fix: call self.w8a8_block_fp8_linear.process_weights_after_loading(layer)
unconditionally, matching the siblings.

Test Plan

Added test_modelopt_fp8_pb_wo_runs_block_kernel_process_weights to
tests/quantization/test_modelopt.py, asserting
process_weights_after_loading forwards to the block kernel's own
process_weights_after_loading.

pytest tests/quantization/test_modelopt.py

Test Result

Verified on 1× NVIDIA H200 (torch 2.11.0).

# new test, BEFORE fix (kernel post-processing skipped):
E   AssertionError: Expected 'process_weights_after_loading' to be called once. Called 0 times.
1 failed

# new test, AFTER fix:
1 passed

# full file, AFTER fix:
19 passed, 1 skipped   # the skip is the checkpoint-gated e2e test

pre-commit run --files ... (ruff, ruff-format, mypy) passes.

On end-to-end eval: the fix restores the documented, sibling-consistent
post-load path that was being skipped, and this is a load-time wiring bug
(no numerics changed for valid inputs — the path simply wasn't running). A full
generation eval needs a FP8_PB_WO (block-wise weight-only) ModelOpt
checkpoint; the repo's existing FP8_PB_WO tests are checkpoint-gated and skip
when none is present locally, and I don't have a public one to point at. Happy
to add e2e numbers if a maintainer can share such a checkpoint.

---

AI assistance (Claude) was used to develop this change. The submitter has
reviewed every changed line and run the tests above.

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[claude]

Claude Code Review

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[huthvincent]

@mgoin gentle ping — small ModelOpt FP8_PB_WO fix: the block-scaled kernel's process_weights_after_loading was silently skipped via a wrong hasattr("fp8_linear") name (the kernel is stored as w8a8_block_fp8_linear), so it GEMMs on unprocessed weights. Small change + unit test. I can't trigger CI as a first-time contributor — could you add the ready label when you get a chance? Thanks!

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @huthvincent.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[huthvincent]

Closing this as superseded. The same one-line change (drop the hasattr(self, "fp8_linear") guard and call w8a8_block_fp8_linear.process_weights_after_loading unconditionally) landed on main via #53132 on 2026-08-21, and #49381 has since replaced ModelOptFp8PbWoLinearMethod with the generic ModelOptLinearMethod, which always runs self.kernel.process_weights_after_loading(layer). test_modelopt_fp8_pb_wo_hides_output_padding already asserts that call for FP8_PB_WO, so this patch no longer applies and its test would import a removed class. Thanks to wzhao18 and juhi10071998 for getting the fix in; glad the diagnosis matched. Happy to help with ModelOpt work going forward.