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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 8, 07:30 UTC

Revert "[Bugfix] Fix fused MoE IMA (sans chunking) by using int64 for strides" (#34530)

Michael Goin committed Feb 13, 2026 at 13:35 UTC bfaa5593050ec9bf60e2361b3b9dc575efeee83f
1 file changed +27 -27
vllm/model_executor/layers/fused_moe/fused_moe.py
+27 -27
@@ -98,19 +98,19 @@ def fused_moe_kernel_gptq_awq(
98 # moving by 1 element in a particular dimension. E.g. `stride_am` is
99 # how much to increase `a_ptr` by to get the element one row down
100 # (A has M rows).
101 - stride_am: tl.int64,
102 - stride_ak: tl.int64,
103 - stride_be: tl.int64,
104 - stride_bk: tl.int64,
105 - stride_bn: tl.int64,
106 - stride_cm: tl.int64,
107 - stride_cn: tl.int64,
108 - stride_bse: tl.int64,
109 - stride_bsk: tl.int64,
110 - stride_bsn: tl.int64,
111 - stride_bze: tl.int64,
112 - stride_bzk: tl.int64,
113 - stride_bzn: tl.int64,
101 + stride_am,
102 + stride_ak,
103 + stride_be,
104 + stride_bk,
105 + stride_bn,
106 + stride_cm,
107 + stride_cn,
108 + stride_bse,
109 + stride_bsk,
110 + stride_bsn,
111 + stride_bze,
112 + stride_bzk,
113 + stride_bzn,
114 block_k_diviable: tl.constexpr,
115 group_size: tl.constexpr,
116 # Meta-parameters
@@ -332,20 +332,20 @@ def fused_moe_kernel(
332 # moving by 1 element in a particular dimension. E.g. `stride_am` is
333 # how much to increase `a_ptr` by to get the element one row down
334 # (A has M rows).
335 - stride_am: tl.int64,
336 - stride_ak: tl.int64,
337 - stride_be: tl.int64,
338 - stride_bk: tl.int64,
339 - stride_bn: tl.int64,
340 - stride_cm: tl.int64,
341 - stride_cn: tl.int64,
342 - stride_asm: tl.int64,
343 - stride_ask: tl.int64,
344 - stride_bse: tl.int64,
345 - stride_bsk: tl.int64,
346 - stride_bsn: tl.int64,
347 - stride_bbe: tl.int64, # bias expert stride
348 - stride_bbn: tl.int64, # bias N stride
335 + stride_am,
336 + stride_ak,
337 + stride_be,
338 + stride_bk,
339 + stride_bn,
340 + stride_cm,
341 + stride_cn,
342 + stride_asm,
343 + stride_ask,
344 + stride_bse,
345 + stride_bsk,
346 + stride_bsn,
347 + stride_bbe, # bias expert stride
348 + stride_bbn, # bias N stride
349 # Block size for block-wise quantization
350 group_n: tl.constexpr,
351 group_k: tl.constexpr,