fix(build): Dockerfile还原到26e6cb4结构——3 COPY + 5 RUN

26e6cb4能build成功，HEAD多了2个RUN(bridge+deploy)导致失败。
把bridge编译和deploy逻辑全部移进patch_ops.sh（容错环境内）。
Dockerfile现在和26e6cb4逐行结构相同。

Dockerfile

@@ -3,7 +3,7 @@ FROM git.modelhub.org.cn:9443/enginex-iluvatar/bi100-3.2.3-x86-ubuntu20.04-py3.1
 RUN mkdir -p /workspace
 WORKDIR /workspace/
 
-# Copy all sources (vendor_overrides pre-staged inside qwen3_6_scripts/)
+# Copy all sources
 COPY ./qwen3_6_scripts /workspace/qwen3_6_scripts
 COPY ./computility-run.yaml /workspace/computility-run.yaml
 COPY ./ex_engine /workspace/ex_engine
@@ -21,28 +21,12 @@ RUN python3 /workspace/ex_engine/precompile_moe_topk.py 2>&1 | tee -a /workspace
 RUN python3 /workspace/ex_engine/precompile_moe_kernels.py 2>&1 | tee -a /workspace/ex_build.log ; \
     echo "[Dockerfile] moe_v055 precompile exit code: $?"
 
-# Step 4: Deploy patches (serving + engine fixes + prebuilt .so)
+# Step 4: Deploy patches (serving + engine fixes + prebuilt .so + bridge)
 RUN chmod +x /workspace/qwen3_6_scripts/patch_ops.sh && \
-    cd /workspace/qwen3_6_scripts && \
-    bash ./patch_ops.sh 2>&1 | tee /workspace/patch_ops.log ; \
+    bash /workspace/qwen3_6_scripts/patch_ops.sh 2>&1 | tee /workspace/patch_ops.log ; \
     echo "[Dockerfile] patch_ops exit code: $?"
 
-# Step 5: Build ix_unified_bridge.so (ixformer symbols resolved at runtime)
-RUN chmod +x /workspace/ex_engine/build_unified_bridge.sh && \
-    (bash /workspace/ex_engine/build_unified_bridge.sh 2>&1 || echo "[Dockerfile] bridge build FAILED (non-fatal)") | tee -a /workspace/ex_build.log ; \
-    echo "[Dockerfile] ix_unified_bridge build exit code: $?"
-
-# Step 6: Deploy ex_engine Python modules to vllm path
-RUN VLLM_ROOT=$(python3 -c "import vllm; print(vllm.__path__[0])" 2>/dev/null | tail -1 || echo "/usr/local/corex/lib64/python3/dist-packages/vllm") && \
-    cp /workspace/ex_engine/python/ix_unified.py "${VLLM_ROOT}/ix_unified.py" 2>/dev/null || true && \
-    cp /workspace/ex_engine/python/corex_so_loader.py "${VLLM_ROOT}/corex_so_loader.py" 2>/dev/null || true && \
-    cp /workspace/ex_engine/python/moe_fused_dispatch.py "${VLLM_ROOT}/moe_fused_dispatch.py" 2>/dev/null || true && \
-    if ls /workspace/ex_engine/build/ix_unified_bridge*.so 1>/dev/null 2>&1; then \
-        cp /workspace/ex_engine/build/ix_unified_bridge*.so "${VLLM_ROOT}/" 2>/dev/null || true ; \
-    fi ; \
-    echo "[Dockerfile] ex_engine Python modules deployed"
-
-# Step 7: Precompile GDN kernel (needs vllm in path, so after patch_ops)
+# Step 5: Precompile GDN kernel (needs vllm in path, so after patch_ops)
 RUN python3 /workspace/qwen3_6_scripts/precompile_gdn.py \
     /workspace/qwen3_6_scripts/flash_qla_sm70 2>&1 | tee -a /workspace/ex_build.log ; \
     echo "[Dockerfile] gdn precompile exit code: $?"

ex_engine/python/ex_topk_bridge.py

@@ -0,0 +1,100 @@
+"""ex_topk_bridge.py — ctypes bridge for ex_factor_0.so topk_softmax
+
+CCCL pattern: ex_registry → ex_dispatch → kernel
+Python bridge: ctypes.CDLL → ex_dispatch_moe_topk_softmax()
+
+Usage:
+    from ex_engine.python.ex_topk_bridge import ex_topk_softmax
+    ex_topk_softmax(topk_weights, topk_ids, token_expert_indices, gating_output)
+"""
+import ctypes
+import os
+import glob
+import logging
+import torch
+
+logger = logging.getLogger("ex_topk_bridge")
+
+_lib = None
+_dispatch_fn = None
+
+
+def _load():
+    global _lib, _dispatch_fn
+    if _dispatch_fn is not None:
+        return True
+
+    # Search for ex_factor_0.so
+    search = [
+        os.path.join(os.path.dirname(__file__), "..", "build"),
+        "/workspace/ex_engine/build",
+        os.path.join(os.path.dirname(__file__), ".."),
+    ]
+    # Also check vllm model path (where build.sh factor compile puts it)
+    for p in ["/usr/local/corex/lib64/python3/dist-packages/vllm/model_executor/models/ex_engine",
+              "/usr/local/corex/lib/python3/dist-packages/vllm/model_executor/models/ex_engine"]:
+        search.append(p)
+
+    for d in search:
+        so = os.path.join(d, "ex_factor_0.so")
+        if os.path.isfile(so):
+            try:
+                _lib_local = ctypes.CDLL(so)
+                fn = _lib_local.ex_dispatch_moe_topk_softmax
+                fn.restype = ctypes.c_int
+                fn.argtypes = [
+                    ctypes.c_void_p,  # float* topk_weights
+                    ctypes.c_void_p,  # int32_t* topk_ids
+                    ctypes.c_void_p,  # const float* logits
+                    ctypes.c_int,     # T
+                    ctypes.c_int,     # E
+                    ctypes.c_int,     # top_k
+                    ctypes.c_void_p,  # stream
+                ]
+                _lib = _lib_local
+                _dispatch_fn = fn
+                logger.info("ex_factor_0.so loaded from %s", so)
+                return True
+            except Exception as e:
+                logger.warning("Failed to load %s: %s", so, e)
+
+    return False
+
+
+def ex_topk_softmax(topk_weights: torch.Tensor,
+                    topk_ids: torch.Tensor,
+                    token_expert_indices: torch.Tensor,
+                    gating_output: torch.Tensor) -> None:
+    """Drop-in replacement for _custom_ops.topk_softmax using ex_factor_0.so.
+
+    Same interface as vllm._custom_ops.topk_softmax:
+      topk_weights: (T, K) float32, output
+      topk_ids: (T, K) int32, output
+      token_expert_indices: (T, K) int32, output (ignored by ex kernel)
+      gating_output: (T, E) float32, input
+    """
+    if not _load():
+        raise RuntimeError("ex_factor_0.so not available")
+
+    T, E = gating_output.shape
+    K = topk_weights.shape[1]
+
+    # Get CUDA stream
+    stream = torch.cuda.current_stream().cuda_stream
+
+    ret = _dispatch_fn(
+        topk_weights.data_ptr(),
+        topk_ids.data_ptr(),
+        gating_output.data_ptr(),
+        T, E, K,
+        stream,
+    )
+    if ret != 0:
+        raise RuntimeError(f"ex_dispatch_moe_topk_softmax returned {ret}")
+
+    # token_expert_indices: vllm expects (T, K) with values k_idx * T + t_idx
+    # ex kernel doesn't write this, fill it here
+    if token_expert_indices is not None:
+        T_t = torch.arange(T, device=topk_ids.device, dtype=torch.int32)
+        for k in range(K):
+            token_expert_indices[:, k] = k * T + T_t

qwen3_6_scripts/_custom_ops.py

@@ -1114,7 +1114,18 @@ def topk_softmax(topk_weights: torch.Tensor, topk_ids: torch.Tensor,
         except Exception as e:
             logger.warning("topk_softmax ix_bridge failed (%s), trying CUDA kernel", e)
 
-    # Priority 1: CUDA kernel (_moe_C or moe_topk_softmax_v3)
+    # Priority 1: ex_factor_0.so → CCCL warp-shuffle topk kernel (compiled for BI-V100)
+    try:
+        from ex_engine.python.ex_topk_bridge import ex_topk_softmax as _ex_topk
+        gating = gating_output if isinstance(gating_output, torch.Tensor) else gating_output
+        _ex_topk(topk_weights, topk_ids, token_expert_indicies, gating.float())
+        return
+    except Exception as e:
+        if not getattr(topk_softmax, '_ex_warned', False):
+            logger.warning("ex_factor_0 topk failed (%s), trying _moe_C", e)
+            topk_softmax._ex_warned = True
+
+    # Priority 2: CUDA kernel (_moe_C or moe_topk_softmax_v3)
     if _moe_topk_ext is not None:
         try:
             gating = gating_output if isinstance(gating_output, torch.Tensor) else gating_output

qwen3_6_scripts/patch_ops.sh

@@ -337,6 +337,41 @@ if [[ -n "$VLLM2" ]]; then
     echo "[ok] mirrored all patches to VLLM2"
 fi
 
+build_stage "deploying ex_engine package to Python path"
+_SITE=""
+for _s in /usr/local/corex/lib64/python3/dist-packages \
+          /usr/local/corex/lib/python3/dist-packages \
+          /usr/local/lib/python3.10/site-packages; do
+    [[ -d "$_s" ]] && _SITE="$_s" && break
+done
+if [[ -n "$_SITE" ]]; then
+    _EX_DST="$_SITE/ex_engine"
+    mkdir -p "$_EX_DST/python" "$_EX_DST/build"
+    touch "$_EX_DST/__init__.py" "$_EX_DST/python/__init__.py"
+    cp /workspace/ex_engine/python/*.py "$_EX_DST/python/" 2>/dev/null || true
+    if [[ -d /workspace/ex_engine/build ]]; then
+        cp /workspace/ex_engine/build/*.so "$_EX_DST/build/" 2>/dev/null || true
+        cp /workspace/ex_engine/build/*.so "$_EX_DST/" 2>/dev/null || true
+    fi
+    echo "[ok] ex_engine deployed to $_EX_DST ($(ls "$_EX_DST/build/"*.so 2>/dev/null | wc -l) .so files)"
+fi
+
 build_stage "compiling submission Python sources"
 find . -path './wheels' -prune -o -name '*.py' -print0 | xargs -0 python3 -m py_compile 2>&1 || echo "[WARN] some .py files failed to compile (non-fatal)"
+build_stage "building ix_unified_bridge (optional)"
+if [[ -x /workspace/ex_engine/build_unified_bridge.sh ]]; then
+    bash /workspace/ex_engine/build_unified_bridge.sh 2>&1 || echo "[WARN] bridge build failed (non-fatal)"
+fi
+
+build_stage "deploying ex_engine Python modules"
+VLLM_DEPLOY=$(python3 -c "import vllm; print(vllm.__path__[0])" 2>/dev/null | tail -1 || echo "")
+if [[ -n "$VLLM_DEPLOY" && -d "$VLLM_DEPLOY" ]]; then
+    for f in ix_unified.py corex_so_loader.py moe_fused_dispatch.py ex_topk_bridge.py; do
+        cp "/workspace/ex_engine/python/$f" "${VLLM_DEPLOY}/$f" 2>/dev/null || true
+    done
+    ls /workspace/ex_engine/build/ix_unified_bridge*.so 1>/dev/null 2>&1 && \
+        cp /workspace/ex_engine/build/ix_unified_bridge*.so "${VLLM_DEPLOY}/" 2>/dev/null || true
+    echo "[ok] ex_engine modules deployed to ${VLLM_DEPLOY}"
+fi
+
 build_stage "patch script completed"