From 4a91c31ffc7a7f4aaa2da70f79b580f9dce4f010 Mon Sep 17 00:00:00 2001
From: project6-dev <dev@project6.ai>
Date: Mon, 10 Aug 2026 06:41:52 +0000
Subject: [PATCH] debug: probe base image vllm FusedMoE actual dispatch chain

---
 probe_base_moe.py | 126 ++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 126 insertions(+)
 create mode 100644 probe_base_moe.py

diff --git a/probe_base_moe.py b/probe_base_moe.py
new file mode 100644
index 00000000..0e1d2ac0
--- /dev/null
+++ b/probe_base_moe.py
@@ -0,0 +1,126 @@
+#!/usr/bin/env python3
+"""
+probe_base_moe.py — Find how base image vllm's FusedMoE actually works
+
+The key question: when vllm calls FusedMoE on BI-V100, what kernel does it use?
+comp 168 log shows "expert-grouped-wmma" — this is a WMMA (tensor core) kernel.
+"""
+import sys, os, traceback
+
+print("=" * 60)
+print("PROBE: Base image vllm FusedMoE dispatch chain")
+print("=" * 60)
+
+# 1. Check what _custom_ops.py does for topk_softmax
+print("\n--- 1. vllm._custom_ops topk_softmax ---")
+try:
+    from vllm._custom_ops import topk_softmax
+    print(f"  topk_softmax: {topk_softmax}")
+    import inspect
+    src = inspect.getsource(topk_softmax)
+    # Print first 20 lines
+    for i, line in enumerate(src.split('\n')[:20]):
+        print(f"    {line}")
+except Exception as e:
+    print(f"  {e}")
+
+# 2. Check FusedMoE layer
+print("\n--- 2. vllm FusedMoE layer ---")
+try:
+    from vllm.model_executor.layers.fused_moe import FusedMoE
+    print(f"  FusedMoE: {FusedMoE}")
+    import inspect
+    src_file = inspect.getfile(FusedMoE)
+    print(f"  File: {src_file}")
+    # Check forward method
+    if hasattr(FusedMoE, 'forward'):
+        src = inspect.getsource(FusedMoE.forward)
+        for i, line in enumerate(src.split('\n')[:30]):
+            print(f"    {line}")
+except Exception as e:
+    print(f"  {e}")
+
+# 3. Check fused_moe function (the one that actually runs)
+print("\n--- 3. vllm fused_moe function ---")
+try:
+    from vllm.model_executor.layers.fused_moe.fused_moe import fused_moe
+    import inspect
+    src = inspect.getsource(fused_moe)
+    for i, line in enumerate(src.split('\n')[:40]):
+        print(f"    {line}")
+except Exception as e:
+    try:
+        from vllm.model_executor.layers.fused_moe import fused_moe
+        import inspect
+        src = inspect.getsource(fused_moe)
+        for i, line in enumerate(src.split('\n')[:40]):
+            print(f"    {line}")
+    except Exception as e2:
+        print(f"  {e2}")
+
+# 4. Check what torch.ops.vllm has
+print("\n--- 4. torch.ops.vllm MoE ops ---")
+try:
+    import torch
+    vllm_ops = torch.ops.vllm
+    for name in dir(vllm_ops):
+        if 'moe' in name.lower() or 'topk' in name.lower() or 'expert' in name.lower():
+            print(f"  torch.ops.vllm.{name}")
+except Exception as e:
+    print(f"  {e}")
+
+# 5. Check ixformer_torch_ext for any MoE-related ops
+print("\n--- 5. _ixformer_torch MoE symbols (demangled) ---")
+os.system("nm -D /usr/local/corex/lib64/python3/dist-packages/ixformer/_ixformer_torch.cpython-310-x86_64-linux-gnu.so 2>/dev/null | grep -i 'moe\\|expert\\|topk\\|gemm' | c++filt | head -20")
+
+# 6. Check if there's a Triton-based MoE
+print("\n--- 6. Triton MoE kernels ---")
+try:
+    from vllm.model_executor.layers.fused_moe import fused_moe as fm_module
+    import inspect
+    src_file = inspect.getfile(fm_module)
+    print(f"  Module file: {src_file}")
+except:
+    pass
+
+# Check for any .so with group_gemm
+print("\n--- 7. group_gemm in any system .so ---")
+os.system("find /usr/local/corex -name '*.so*' -exec sh -c 'nm -D \"$1\" 2>/dev/null | grep -q group_gemm && echo \"  $1\"' _ {} \\;")
+
+# 8. Check the actual _custom_ops topk_softmax implementation
+print("\n--- 8. _custom_ops.py full topk_softmax chain ---")
+try:
+    custom_ops_path = None
+    for p in ["/usr/local/corex/lib64/python3/dist-packages/vllm/_custom_ops.py",
+              "/usr/local/corex/lib/python3/dist-packages/vllm/_custom_ops.py"]:
+        if os.path.exists(p):
+            custom_ops_path = p
+            break
+    if custom_ops_path:
+        with open(custom_ops_path) as f:
+            content = f.read()
+        # Find topk_softmax function
+        lines = content.split('\n')
+        in_func = False
+        for i, line in enumerate(lines):
+            if 'def topk_softmax' in line or 'topk_softmax' in line:
+                in_func = True
+            if in_func:
+                print(f"  {i+1}: {line}")
+                if line.strip() == '' and in_func:
+                    in_func = False
+            if i > 0 and in_func and not line.startswith(' ') and not line.startswith('\t') and line.strip():
+                in_func = False
+except Exception as e:
+    print(f"  {e}")
+
+# 9. What does ixformer.functions.vllm do?
+print("\n--- 9. ixformer.functions.vllm module ---")
+try:
+    import ixformer.functions.vllm as ixf_vllm
+    print(f"  Module: {ixf_vllm}")
+    for attr in dir(ixf_vllm):
+        if not attr.startswith('_'):
+            print(f"    {attr}")
+except Exception as e:
+    print(f"  {e}")