Remove triton per group quant [ROCm] [Bugfix]

[afriedri]

Purpose

On ROCm, dynamic FP8 per-group (block-scale) activation quant was routed through a
vllm.triton_per_token_group_quant_fp8 custom op whenever the block-scaled linear kernel
chose its tuned Triton GEMM path (AiterFp8BlockScaledMMKernel, use_triton=True). That
op is a thin wrapper that already dispatches to the C++ _C.per_token_group_fp8_quant
kernel on ROCm (#42758) — so it adds no compute, but it blocks RMSNorm + quant fusion.

The fusion matchers (MatcherQuantFP8) only emit rocm_aiter_group_fp8_quant or
_C.per_token_group_fp8_quant, never the triton wrapper. So any layer hitting the
tuned-GEMM list (e.g. DeepSeek-R1 MLA q_b_proj (3072, 1536)) emitted an unmatchable op
and left a standalone group-quant kernel unfused — ~9% of decode GPU time in an 8×TP
DeepSeek-R1 profile.

This PR removes the redundant wrapper so QuantFP8.forward_hip falls through to the
existing aiter/C++ paths the matchers already recognize. No fusion-pass logic changes; the
group RMSNorm+quant fusion simply starts firing on the previously-blocked layers.

Changes

• Delete the triton_per_token_group_quant_fp8 op + impl/fake and its now-unused import (fp8_utils.py).
• Remove the is_group_quant and use_triton early return in QuantFP8.forward_hip (input_quant_fp8.py).
• Update tests/docstring that referenced the removed op (test_fusion.py, test_silu_mul_quant_fusion.py,
  test_fusion_all_reduce.py, allreduce_rms_fusion.py).

Orthogonal to #42758 (which enabled the C++ kernel — that changed what ran inside the
wrapper; this removes the wrapper).

Related open PRs (none duplicate this change):

• [ROCm][Compile] Fuse RMSNorm + MXFP4 quant via AITER Triton kernels (DeepSeek-R1) #44437 (RMSNorm+MXFP4 fusion, actively developed) edits the same fusion files; overlaps only one docstring
  line in allreduce_rms_fusion.py that [ROCm][Compile] Fuse RMSNorm + MXFP4 quant via AITER Triton kernels (DeepSeek-R1) #44437 deletes with its enclosing class — trivial rebase. cc
  @shantipriya-amd
• [ROCm] Add AITER RMSNorm+FP8 quantization fusion for MLA #38299 fuses MLA RMSNorm+FP8 via manual mla.py edits rather than the compile passes — a different
  approach to a similar goal (currently inactive).
• [AMD] Amd/deepseek aiter fusions #30274 (draft, inactive) and Support ROCm aiter specific fusion of per_tensor RMSNorm+QuantFP8 #32419 still reference triton_per_token_group_quant_fp8; this PR removes it
  as redundant on ROCm (Enable perf_token_group_quant/_C_stable_libtorch for ROCm #42758).

Follow-up (separate): the remaining MLA q-path group-quant kernels can be collapsed
into aiter's single fused_qk_rmsnorm_group_quant via a group variant of
MLADualRMSNormFusionPass.

Test Plan

# Fusion unit tests (ROCm + aiter):
VLLM_ROCM_USE_AITER=1 python -m pytest \
  tests/compile/passes/test_fusion.py::test_fusion_rmsnorm_quant \
  tests/compile/passes/test_silu_mul_quant_fusion.py \
  tests/compile/passes/distributed/test_fusion_all_reduce.py -v

# Accuracy A/B (isolated cache per run to force fresh torch.compile):
VLLM_ROCM_USE_AITER=1 VLLM_CACHE_ROOT=/tmp/vllm_cache_run lm_eval --model vllm \
  --model_args "pretrained=deepseek-ai/DeepSeek-R1,tensor_parallel_size=8,quantization=fp8,kv_cache_dtype=fp8
,max_model_len=4096" \
  --tasks gsm8k --num_fewshot 5 --limit 200 --batch_size auto

Test Result

Fusion firing (DeepSeek-R1, 8×TP decode profile): the standalone
per_token_group_quant_8bit_kernel no longer appears as a separate launch on the affected
layers — two ~4 µs kernels (RMSNorm + group quant) become one ~4 µs fused kernel.

Before:

After:

Unit tests (ROCm gfx950, VLLM_ROCM_USE_AITER=1):

• test_fusion.py::test_fusion_rmsnorm_quant — 64 passed, 16 skipped (covers the aiter-quant and
  C++-fallback group paths).
• test_silu_mul_quant_fusion.py::...[TestSiluMulGroupFp8QuantModel-*] — 16 passed.

Pre-existing failures, unrelated (reproduced on base commit with this PR reverted):

• ...[TestSiluMulFp8QuantModel-*] — per-tensor/per-token static path (is_group_quant=False), untouched
  here.
• test_fusion_all_reduce.py::test_rocm_aiter_all_reduce_rmsnorm_group_quant_fp8_fusion_pass_replace —
  numerical assert_close fails on base too.
• test_fusion_all_reduce.py::...[trtllm/mnnvl-...] — FlashInfer/MNNVL backends unavailable here; no quant
  involved.

Accuracy (gsm8k 5-shot, DeepSeek-R1, TP=8, fp8 + fp8 KV, 200 samples): no regression.

	exact_match (strict)	exact_match (flexible)
Baseline (triton wrapper)	0.960 ± 0.014	0.960 ± 0.014
This PR (op removed)	0.960 ± 0.014	0.960 ± 0.014

---

AI assistance (Claude) was used to investigate the fusion gap and draft this change; all lines were reviewed
by the submitter.

[claude]

Claude Code Review

This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

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[Rohan138]

LGTM, thanks!

[dllehr-amd]

Thanks Andy!

[mergify]

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[mergify]

Hi @afriedri, the pre-commit checks have failed. Please run:

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