From 94096a47c92c4a53ad44cfffdca918669c0f89e0 Mon Sep 17 00:00:00 2001
From: Michael Goin <mgoin64@gmail.com>
Date: Sat, 16 Aug 2025 22:16:42 -0400
Subject: [PATCH] [UX] Separate marlin moe config logic from triton moe
 (#23006)

---
 .../layers/fused_moe/fused_marlin_moe.py      | 20 ++++++-------------
 .../layers/fused_moe/fused_moe.py             |  9 +--------
 2 files changed, 7 insertions(+), 22 deletions(-)

diff --git a/vllm/model_executor/layers/fused_moe/fused_marlin_moe.py b/vllm/model_executor/layers/fused_moe/fused_marlin_moe.py
index a49d41c18438e..3c6ece6737e4d 100644
--- a/vllm/model_executor/layers/fused_moe/fused_marlin_moe.py
+++ b/vllm/model_executor/layers/fused_moe/fused_marlin_moe.py
@@ -1,14 +1,12 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """Fused MoE utilities for GPTQ."""
-import functools
 from typing import Optional
 
 import torch
 
 import vllm._custom_ops as ops
-from vllm.model_executor.layers.fused_moe.fused_moe import (
-    moe_align_block_size, try_get_optimal_moe_config)
+from vllm.model_executor.layers.fused_moe.fused_moe import moe_align_block_size
 from vllm.model_executor.layers.quantization.utils.marlin_utils import (
     marlin_make_workspace_new, maybe_warn_marlin_atomic_add)
 from vllm.scalar_type import ScalarType, scalar_types
@@ -98,17 +96,11 @@ def fused_marlin_moe(hidden_states: torch.Tensor,
     N = w2.shape[1] * 16
     topk = topk_ids.shape[1]
 
-    get_config_func = functools.partial(
-        try_get_optimal_moe_config,
-        w1.shape,
-        w2.shape,
-        topk_ids.shape[1],
-        None,
-        is_marlin=True,
-    )
-    config = get_config_func(M)
-
-    block_size_m = config["BLOCK_SIZE_M"]
+    # M block size selection logic
+    # TODO: tune this further for specific models
+    for block_size_m in [8, 16, 32, 48, 64]:
+        if M * topk / E / block_size_m < 0.9:
+            break
 
     if global_num_experts == -1:
         global_num_experts = E
diff --git a/vllm/model_executor/layers/fused_moe/fused_moe.py b/vllm/model_executor/layers/fused_moe/fused_moe.py
index e58a9e568d4a4..3579ca22bafc7 100644
--- a/vllm/model_executor/layers/fused_moe/fused_moe.py
+++ b/vllm/model_executor/layers/fused_moe/fused_moe.py
@@ -801,7 +801,6 @@ def get_default_config(
     K: int,
     topk: int,
     dtype: Optional[str],
-    is_marlin: bool,
     block_shape: Optional[list[int]] = None,
 ) -> dict[str, int]:
     if dtype == "fp8_w8a8" and block_shape is not None:
@@ -832,11 +831,6 @@ def get_default_config(
             config = {"BLOCK_SIZE_M": 32, "GROUP_SIZE_M": 1}
         else:
             config = {"BLOCK_SIZE_M": 64, "GROUP_SIZE_M": 1}
-    elif is_marlin:
-        for block_size_m in [8, 16, 32, 48, 64]:
-            if M * topk / E / block_size_m < 0.9:
-                break
-        return {"BLOCK_SIZE_M": block_size_m}
     elif M <= E:
         config = {
             "BLOCK_SIZE_M": 16,
@@ -860,7 +854,6 @@ def try_get_optimal_moe_config(
     top_k: int,
     dtype: Optional[str],
     M: int,
-    is_marlin: bool = False,
     block_shape: Optional[list[int]] = None,
 ) -> dict[str, int]:
     from vllm.model_executor.layers.fused_moe import get_config
@@ -883,7 +876,7 @@ def try_get_optimal_moe_config(
         else:
             # Else use the default config
             config = get_default_config(M, E, N, w1_shape[2], top_k, dtype,
-                                        is_marlin, block_shape)
+                                        block_shape)
     return config