#!/usr/bin/env bash # BI-V100 patch script for Qwen3.6-35B-A3B (Qwen3_5 MoE architecture) # # Triton situation on BI-V100: # - Standard Triton 2.3.1 is already present in the image. # - HAS_TRITON = False (hardcoded in vendor vllm), but Triton is still used # for TP-mode cache management (custom_cache_manager / libentry). # - The vendor's triton_utils/__init__.py, custom_cache_manager.py, libentry.py # are already correct for standard Triton 2.3.1 — do NOT overwrite them. # - DO NOT install BI-V150 corex Triton 2.1.0 (pkgs/triton): that causes # GPU hang on BI-V100 because the Triton CUDA PTX kernels are incompatible. # Recommended server start command for TP=4 support 256K, needs chunked prefill # CUDA_VISIBLE_DEVICES="4,5,6,7" VLLM_ENGINE_ITERATION_TIMEOUT_S=3600 python3 -m vllm.entrypoints.openai.api_server \ # --model /workspace/models/Qwen3.6-35B-A3B --port 1111 --served-model-name llm \ # --max-model-len 262144 --trust-remote-code -tp 4 --gpu-memory-utilization 0.90 \ # --max-num-seqs 1 --disable-log-requests --disable-frontend-multiprocessing \ # --max-num-batched-tokens 8192 --enable-chunked-prefill --enable-prefix-caching \ # --max-seq-len-to-capture 32768 --enable-auto-tool-choice \ # --tool-call-parser qwen3_coder --reasoning-parser qwen3 # # With prefix caching (GDN align-mode, requires chunked prefill): # CUDA_VISIBLE_DEVICES="4,5,6,7" VLLM_ENGINE_ITERATION_TIMEOUT_S=3600 python3 -m vllm.entrypoints.openai.api_server \ # --model /workspace/models/Qwen3.6-35B-A3B --port 1111 --served-model-name llm \ # --max-model-len 262144 --trust-remote-code -tp 4 --gpu-memory-utilization 0.90 \ # --max-num-seqs 1 --disable-log-requests --disable-frontend-multiprocessing \ # --max-num-batched-tokens 8192 --enable-chunked-prefill --enable-prefix-caching \ # --max-seq-len-to-capture 32768 --enable-auto-tool-choice \ # --tool-call-parser qwen3_coder --reasoning-parser qwen3 set -eo pipefail # cd into this script's directory so ./relative paths work cd "$(dirname "${BASH_SOURCE[0]}")" echo "[patch_ops] working directory: $(pwd)" build_stage() { printf '[BI100 BUILD] %s\n' "$1" >&2; } require_file() { local path=$1 [[ -f "$path" ]] || { printf 'required patch source is missing: %s\n' "$path" >&2 exit 2 } } install_patch_file() { local source=$1 local target=$2 require_file "$source" mkdir -p "$(dirname "$target")" install -m 0644 "$source" "$target" } build_stage "patch script entered" build_stage "checking offline transformers dependency" # --- transformers: Qwen3_5 tokenizer / model files -------------------------- TRANSFORMERS_REQUIRED_VERSION="4.55.3" if ! python3 - "$TRANSFORMERS_REQUIRED_VERSION" <<'PY' import importlib.metadata import sys required = sys.argv[1] try: installed = importlib.metadata.version("transformers") except importlib.metadata.PackageNotFoundError: raise SystemExit(1) raise SystemExit(0 if installed == required else 1) PY then WHEEL_DIR="./wheels" if ! ls "${WHEEL_DIR}/transformers-${TRANSFORMERS_REQUIRED_VERSION}"*.whl >/dev/null 2>&1; then echo "transformers ${TRANSFORMERS_REQUIRED_VERSION} is required, but no offline wheel was found in ${WHEEL_DIR}" >&2 exit 2 fi python3 -m pip install --no-index --no-deps --find-links="${WHEEL_DIR}" \ "transformers==${TRANSFORMERS_REQUIRED_VERSION}" fi python3 - "$TRANSFORMERS_REQUIRED_VERSION" <<'PY' import importlib.metadata import sys required = sys.argv[1] installed = importlib.metadata.version("transformers") if installed != required: raise SystemExit( f"transformers version mismatch: expected {required}, got {installed}") print(f"[ok] transformers {installed}") PY build_stage "discovering Python package roots" python3 - <<'PY' > /tmp/qwen36_patch_paths.env from patch_utils import package_root, shell_env_line print(shell_env_line("VLLM_ROOT", package_root("vllm"))) print(shell_env_line("TRANSFORMERS_ROOT", package_root("transformers"))) PY source /tmp/qwen36_patch_paths.env echo "VLLM_ROOT=${VLLM_ROOT}" echo "TRANSFORMERS_ROOT=${TRANSFORMERS_ROOT}" [[ -d "$VLLM_ROOT" ]] || { printf 'vLLM root does not exist: %s\n' "$VLLM_ROOT" >&2 exit 2 } VLLM_OVERRIDE_ROOT="./vendor_overrides/vllm" [[ -d "$VLLM_OVERRIDE_ROOT" ]] || { printf 'vLLM override directory missing: %s\n' "$VLLM_OVERRIDE_ROOT" >&2 exit 2 } build_stage "installing authoritative vLLM core block overrides" install_patch_file \ "${VLLM_OVERRIDE_ROOT}/core/evictor_v2.py" \ "${VLLM_ROOT}/core/evictor_v2.py" install_patch_file \ "${VLLM_OVERRIDE_ROOT}/core/block/cpu_kv_content_cache.py" \ "${VLLM_ROOT}/core/block/cpu_kv_content_cache.py" install_patch_file \ "${VLLM_OVERRIDE_ROOT}/core/block/cpu_gpu_block_allocator.py" \ "${VLLM_ROOT}/core/block/cpu_gpu_block_allocator.py" install_patch_file \ "${VLLM_OVERRIDE_ROOT}/core/block/prefix_caching_block.py" \ "${VLLM_ROOT}/core/block/prefix_caching_block.py" install_patch_file \ "${VLLM_OVERRIDE_ROOT}/core/block/block_table.py" \ "${VLLM_ROOT}/core/block/block_table.py" install_patch_file \ "${VLLM_OVERRIDE_ROOT}/core/block_manager_v2.py" \ "${VLLM_ROOT}/core/block_manager_v2.py" install_patch_file \ "${VLLM_OVERRIDE_ROOT}/sampling_params.py" \ "${VLLM_ROOT}/sampling_params.py" install_patch_file \ "${VLLM_OVERRIDE_ROOT}/model_executor/sampling_metadata.py" \ "${VLLM_ROOT}/model_executor/sampling_metadata.py" install_patch_file \ "${VLLM_OVERRIDE_ROOT}/model_executor/layers/sampler.py" \ "${VLLM_ROOT}/model_executor/layers/sampler.py" build_stage "installing hash-pinned CoreX 3.2.3 extensions (16 prebuilt .so)" bash ./install_prebuilt_corex.sh "${VLLM_ROOT}" build_stage "installing BI100 runtime modules" cp ./bi100_env.py "${VLLM_ROOT}/bi100_env.py" cp ./bi100_profile.py "${VLLM_ROOT}/bi100_profile.py" cp ./block_major_kv_cache.py "${VLLM_ROOT}/block_major_kv_cache.py" cp ./gdn_prefix.py "${VLLM_ROOT}/gdn_prefix.py" build_stage "installing CoreX paged-KV swap compatibility" python3 ./patch_corex_swap_blocks.py python3 ./patch_block_major_cache_engine.py python3 ./patch_worker_cache_transfer_order.py # --- paged_attn.py: replace forward_prefix with pure-PyTorch fallback ------- # The Triton context_attention_fwd kernel hangs BI-V100 GPUs permanently # (standard Triton 2.3.1 PTX is not supported by the corex runtime either). # Our paged_attn.py bypasses it entirely via _forward_prefix_pytorch, which # utilizes K-tiling techniques, and also have _forward_decode_pytorch to bypass kernel # when context length is high cp ./paged_attn.py "${VLLM_ROOT}/attention/ops/paged_attn.py" # --- model_runner.py: fix prefix_cache_hit stays True in chunked-prefill chunk 2+ --- # Bug: _compute_for_prefix_cache_hit Case 1 (prefix_cache_len <= context_len) # leaves prefix_cache_hit=True. Then _add_seq_group uses block_table=computed_block_nums # (only the original prefix blocks), ignoring chunk-1 KV cache blocks. # _forward_prefix_pytorch then gets an undersized block_tables and crashes with # "amax(): Expected reduction dim -1 to have non-zero size" on the 2nd tile. # Fix: set prefix_cache_hit=False for Case 1 so the full block_tables is used. python3 ./patch_model_runner.py build_stage "installing executor startup diagnostics" python3 ./patch_executor_startup_debug.py python3 ./patch_worker_startup_profile_guard.py python3 ./patch_block_major_worker_capacity.py build_stage "installing transformers Qwen3.5 model support" cp -r ./qwen3_5 "${TRANSFORMERS_ROOT}/models/" cp -r ./qwen3_5_moe "${TRANSFORMERS_ROOT}/models/" python3 ./patch_transformers_qwen3_5.py build_stage "installing vLLM Qwen3.6 model implementation" # --- vllm model: Qwen3.6-35B-A3B (Qwen3_5 MoE arch) ------------------------- cp ./mamba_cache.py "${VLLM_ROOT}/model_executor/models/" cp ./qwen3_5.py "${VLLM_ROOT}/model_executor/models/qwen3_5.py" cp ./ix_fused_moe.py "${VLLM_ROOT}/model_executor/models/ix_fused_moe.py" || true python3 ./patch_vllm_qwen3_5.py # --- Deploy prebuilt .so into vllm package for import ----------------------- PREBUILT_DIR="./prebuilt/corex-3.2.3-ivcore10" if [ -d "$PREBUILT_DIR" ]; then for so_file in "$PREBUILT_DIR"/*.so; do base=$(basename "$so_file" .so) # Deploy corex_*.so as vllm submodules (import from vllm import corex_xxx) cp "$so_file" "${VLLM_ROOT}/${base}.so" 2>/dev/null || true echo "[patch_ops] deployed ${base}.so → ${VLLM_ROOT}/" done fi # --- Rebuild corex_moe_direct_routed.so for BI-V100 warp_size=64 ----------- # The prebuilt .so was compiled with kWarpSize=32 which silently corrupts # results on BI-V100 (64-wide warps). Rebuild from the fixed .cu source # that uses kWarpSize=64 and 6-step shuffle reductions. build_stage "rebuilding corex_moe_direct_routed.so (warp64)" COREX_ROOT="${COREX_ROOT:-/usr/local/corex-3.2.3}" if [ ! -d "$COREX_ROOT" ]; then COREX_ROOT="/usr/local/corex" fi TORCH_ROOT="${TORCH_ROOT:-$(python3 -c 'import torch,os;print(os.path.dirname(torch.__file__))' 2>/dev/null || echo "${COREX_ROOT}/lib64/python3/dist-packages/torch")}" DIRECT_ROUTED_SRC="./corex_moe_direct_routed.cu" DIRECT_ROUTED_DST="${VLLM_ROOT}/corex_moe_direct_routed.so" if [ -f "$DIRECT_ROUTED_SRC" ] && [ -x "${COREX_ROOT}/bin/clang++" ]; then "${COREX_ROOT}/bin/clang++" \ -std=c++17 -O3 -shared -fPIC \ --cuda-path="${COREX_ROOT}" --cuda-gpu-arch=ivcore10 \ --no-cuda-version-check -D_GLIBCXX_USE_CXX11_ABI=0 \ -DTORCH_EXTENSION_NAME=corex_moe_direct_routed \ -DTORCH_API_INCLUDE_EXTENSION_H \ -I"${TORCH_ROOT}/include" \ -I"${TORCH_ROOT}/include/torch/csrc/api/include" \ -I"${TORCH_ROOT}/include/TH" -I"${TORCH_ROOT}/include/THC" \ -I/usr/local/include/python3.10 \ "$DIRECT_ROUTED_SRC" \ -L"${TORCH_ROOT}/lib" -L"${COREX_ROOT}/lib64" \ -Wl,-rpath,"${TORCH_ROOT}/lib" -Wl,-rpath,"${COREX_ROOT}/lib64" \ -ltorch_python -ltorch_cuda -ltorch_cpu -ltorch \ -lc10_cuda -lc10 -lcudart \ -o "$DIRECT_ROUTED_DST" 2>&1 && \ echo "[patch_ops] REBUILT corex_moe_direct_routed.so (warp64) → ${DIRECT_ROUTED_DST}" || \ echo "[patch_ops] WARNING: corex_moe_direct_routed.so rebuild FAILED, using prebuilt" elif [ ! -x "${COREX_ROOT}/bin/clang++" ]; then echo "[patch_ops] WARNING: CoreX clang++ not found at ${COREX_ROOT}/bin/clang++, cannot rebuild direct_routed" else echo "[patch_ops] WARNING: ${DIRECT_ROUTED_SRC} not found, cannot rebuild direct_routed" fi # --- Deploy ix_bridge Python integration layer -------------------------------- build_stage "deploying ix_bridge operator replacements" EX_ENGINE_DIR="$(cd "$(dirname "$0")/ex_engine" 2>/dev/null && pwd || echo "")" if [ -z "$EX_ENGINE_DIR" ] || [ ! -d "$EX_ENGINE_DIR/python" ]; then EX_ENGINE_DIR="$(cd "$(dirname "$0")/../ex_engine" 2>/dev/null && pwd || echo "")" fi if [ -z "$EX_ENGINE_DIR" ] || [ ! -d "$EX_ENGINE_DIR/python" ]; then EX_ENGINE_DIR="/workspace/ex_engine" fi if [ -d "$EX_ENGINE_DIR/python" ]; then # Create ex_engine package inside vllm with correct Python package structure mkdir -p "${VLLM_ROOT}/ex_engine/python" mkdir -p "${VLLM_ROOT}/ex_engine/csrc" # __init__.py with re-exports so both import styles work: # from ex_engine.python import ix_ops_dispatch (direct) # from vllm.ex_engine import ix_ops_dispatch (via re-export) cat > "${VLLM_ROOT}/ex_engine/__init__.py" << 'INIT_EOF' """ex_engine — Algorithm factor replacement for BI-V100.""" # Re-export python subpackage members at top level for backward compat # Allows: from vllm.ex_engine import ix_ops_dispatch try: from ex_engine.python.ix_ops_dispatch import * from ex_engine.python import ix_ops_dispatch from ex_engine.python import ix_ops from ex_engine.python import patch_vllm_ops except ImportError: pass INIT_EOF echo '"""ex_engine.python — dispatch and bridge modules."""' > "${VLLM_ROOT}/ex_engine/python/__init__.py" # Deploy ALL Python modules cp "$EX_ENGINE_DIR/python/"*.py "${VLLM_ROOT}/ex_engine/python/" echo "[patch_ops] deployed $(ls -1 "${VLLM_ROOT}/ex_engine/python/"*.py | wc -l) modules → ${VLLM_ROOT}/ex_engine/python/" # Deploy bridge C++ source for JIT fallback for cpp in "$EX_ENGINE_DIR"/csrc/ix_full_bridge*.cpp "$EX_ENGINE_DIR"/csrc/ix_moe_bridge.cpp; do [ -f "$cpp" ] && cp "$cpp" "${VLLM_ROOT}/ex_engine/csrc/" && \ echo "[patch_ops] deployed $(basename $cpp) for JIT fallback" done # Create startup hook that patches vllm ops at import time cat > "${VLLM_ROOT}/ix_startup_patch.py" << 'STARTUP_EOF' """Apply ix_ops patches at vllm startup.""" import logging _logger = logging.getLogger("ix_startup_patch") _applied = False def apply(): global _applied if _applied: return 0 _applied = True import sys, os # Ensure ex_engine is importable for p in ["/workspace/qwen3_6_scripts", "/workspace"]: rp = os.path.realpath(p) if os.path.isdir(rp) and rp not in sys.path: sys.path.insert(0, rp) n = 0 try: from ex_engine.python.patch_vllm_ops import apply_all_patches k = apply_all_patches() n += k if k > 0: _logger.info("ix_startup_patch: %d bridge patches applied", k) except Exception as e: _logger.warning("ix_startup_patch: bridge patches failed: %s", e) try: from ex_engine.python.patch_vllm_hot_path import apply as apply_hot k = apply_hot(strict=False) n += k if k > 0: _logger.info("ix_startup_patch: %d hot-path patches applied", k) except Exception as e: _logger.warning("ix_startup_patch: hot-path patches failed: %s", e) try: from ex_engine.python.patch_fused_linear_allreduce import apply_patch as apply_fused_ar apply_fused_ar() n += 1 _logger.info("ix_startup_patch: fused linear_allreduce patch applied") except Exception as e: _logger.warning("ix_startup_patch: fused linear_allreduce patch failed: %s", e) return n # DO NOT call apply() at import time — registry subprocess would crash. # apply() is called from qwen3_5.py model init instead. STARTUP_EOF echo "[patch_ops] deployed ix_startup_patch.py" # Hook into vllm __init__.py to auto-apply patches on import VLLM_INIT="${VLLM_ROOT}/__init__.py" if [ -f "$VLLM_INIT" ]; then if ! grep -q "ix_startup_patch" "$VLLM_INIT" 2>/dev/null; then echo "" >> "$VLLM_INIT" echo "# Auto-apply ix_bridge operator patches" >> "$VLLM_INIT" echo "try:" >> "$VLLM_INIT" echo " from vllm import ix_startup_patch" >> "$VLLM_INIT" echo "except Exception:" >> "$VLLM_INIT" echo " pass" >> "$VLLM_INIT" echo "[patch_ops] hooked ix_startup_patch into vllm/__init__.py" fi fi else echo "[patch_ops] WARN: ex_engine/python not found, skip ix_bridge deployment" fi # --- sequence.py: fix completion_tokens inflation under chunked prefill ------ # Bug: get_output_token_ids_to_return(delta=True) with num_new_tokens=0 # returns _cached_all_token_ids[-0:] == [0:] (the ENTIRE prompt+output list). # Each prefill chunk step adds prompt_len to previous_num_tokens, so a 10K # prompt processed in 3 chunks inflates completion_tokens by ~30K. # Also adds num_cached_tokens field to RequestMetrics for prefix-cache stats. cp ./sequence.py "${VLLM_ROOT}/sequence.py" # --- scheduler.py: record num_cached_tokens in RequestMetrics ---------------- # Reports only the longest prefix backed by both live KV blocks and an exact # GDN restore state. Raw KV-only hits must not inflate cached_tokens. # serving_chat.py exposes the value in the OpenAI-compatible usage details. cp ./scheduler.py "${VLLM_ROOT}/core/scheduler.py" build_stage "installing diagnostic initial allocation trace" python3 ./patch_block_manager_cache_trace.py build_stage "installing scheduler and attention patches" # --- xformers: bypass cudnnFlashAttnForward (head_dim=256 > 128 limit) ------ # Injects _run_sdpa_fallback (pure matmul+softmax) into xformers.py. # Required because head_dim=256 > 128 and ixformer flash attention either # crashes (is_causal=True) or produces wrong output (attn_mask path). # The fallback uses query_start_loc to derive actual query lengths, so it # works correctly during profiling runs with chunked-prefill-style batches. # also bypasses auto chunked prefill on python3 ./patch_xformers_sdpa_seq.py python3 ./patch_xformers_profile.py build_stage "installing API parsers and serving modules" # --- tool parser: Qwen3 XML tool call format --------------------------------- # Registers "qwen3_coder" parser for Qwen3.6 XML-style tool calls: # \nvalue\n # Use at server start: --tool-call-parser qwen3_coder --enable-auto-tool-choice cp ./qwen3coder_tool_parser.py "${VLLM_ROOT}/entrypoints/openai/tool_parsers/" python3 ./patch_vllm_tool_parser.py # --- reasoning parser: Qwen3 ... split ------------------------ # Adds --reasoning-parser qwen3 support. # Routes thinking tokens to reasoning_content, rest to content in the delta. # Works together with --tool-call-parser qwen3_coder (think → tool call flow). cp -r ./reasoning "${VLLM_ROOT}/" cp ./protocol.py "${VLLM_ROOT}/entrypoints/openai/protocol.py" cp ./cli_args.py "${VLLM_ROOT}/entrypoints/openai/cli_args.py" cp ./serving_chat.py "${VLLM_ROOT}/entrypoints/openai/serving_chat.py" cp ./serving_tokenization.py \ "${VLLM_ROOT}/entrypoints/openai/serving_tokenization.py" cp ./api_server.py "${VLLM_ROOT}/entrypoints/openai/api_server.py" cp ./chat_utils.py "${VLLM_ROOT}/entrypoints/chat_utils.py" python3 - ./api_server.py \ "${VLLM_ROOT}/entrypoints/openai/api_server.py" <<'PY' from pathlib import Path import sys source = Path(sys.argv[1]).read_bytes() installed = Path(sys.argv[2]).read_bytes() if source != installed: raise SystemExit("runtime api_server overlay identity mismatch") PY # --- protocol.py identity check: ensure max_completion_tokens is accepted --- python3 - ./protocol.py \ "${VLLM_ROOT}/entrypoints/openai/protocol.py" <<'PY' from pathlib import Path import sys source = Path(sys.argv[1]).read_bytes() installed = Path(sys.argv[2]).read_bytes() if source != installed: raise SystemExit("runtime protocol overlay identity mismatch") # Verify max_completion_tokens field is declared (not just extra=allow) if b"max_completion_tokens" not in installed: raise SystemExit("protocol.py missing max_completion_tokens field") PY build_stage "building CUTLASS grouped GEMM (gemm_grouped.so)" if [[ -f "${EX_ENGINE_DIR}/build_gemm_grouped.sh" ]]; then bash "${EX_ENGINE_DIR}/build_gemm_grouped.sh" 2>&1 || { echo "[WARN] gemm_grouped build failed — will use torch.mm fallback" } # Deploy compiled .so if it exists for so in "${EX_ENGINE_DIR}"/gemm_grouped.so "${EX_ENGINE_DIR}"/csrc/gemm_grouped.so; do if [[ -f "$so" ]]; then cp "$so" "${VLLM_ROOT}/gemm_grouped.so" echo "[patch_ops] deployed gemm_grouped.so → ${VLLM_ROOT}/" break fi done fi build_stage "building CUTLASS batched GEMM (corex_batched_gemm.so)" if [[ -f "${EX_ENGINE_DIR}/xllm_kernels/cuda/corex_batched_gemm_kernel.cu" ]]; then python3 << PYEOF import os, sys, shutil try: from torch.utils.cpp_extension import load ex = "${EX_ENGINE_DIR}" cutlass_inc = "" for d in ["/usr/local/corex-samples-3.2.3_x86_64/samples/cutlass/include", "/usr/local/corex/include/cutlass", "/usr/include/cutlass"]: if os.path.isdir(d): cutlass_inc = d break if not cutlass_inc: print("[batched_gemm] No cutlass headers — skip"); sys.exit(0) mod = load( name="corex_batched_gemm", sources=[ os.path.join(ex, "xllm_kernels/cuda/corex_batched_gemm_kernel.cu"), os.path.join(ex, "xllm_kernels/cuda/bindings/corex_batched_gemm_bind.cpp"), ], extra_include_paths=[cutlass_inc], extra_cflags=["-O2", "-std=c++17"], extra_cuda_cflags=["-O2", f"-I{cutlass_inc}"], extra_ldflags=["/usr/local/corex/lib64/libcuinfer.so", "-Wl,-rpath,/usr/local/corex/lib64"], verbose=False, ) print("[batched_gemm] ✓ Compiled") import importlib spec = importlib.util.find_spec("corex_batched_gemm") if spec and spec.origin: shutil.copy2(spec.origin, "${VLLM_ROOT}/corex_batched_gemm.so") print("[batched_gemm] ✓ Deployed to ${VLLM_ROOT}/") except Exception as e: print(f"[batched_gemm] WARN: {e}") PYEOF fi build_stage "building MoE bridge (ix_moe_bridge.so)" if [[ -f "${EX_ENGINE_DIR}/csrc/ix_moe_bridge.cpp" ]]; then SCRIPT_DIR="${EX_ENGINE_DIR}" bash "${EX_ENGINE_DIR}/build_moe_bridge.sh" "${VLLM_ROOT}" 2>&1 || { echo "[WARN] MoE bridge build failed — will use Python fallback" } # Deploy .so to all paths ix_fused_moe.py searches for src in "${VLLM_ROOT}/ex_engine/ix_moe_bridge.so" \ "${EX_ENGINE_DIR}/prebuilt/ix_moe_bridge.so"; do if [[ -f "$src" ]]; then cp "$src" "${VLLM_ROOT}/ix_moe_bridge.so" 2>/dev/null || true cp "$src" "${VLLM_ROOT}/model_executor/models/ix_moe_bridge.so" 2>/dev/null || true echo "[patch_ops] deployed ix_moe_bridge.so to vllm search paths" break fi done fi build_stage "deploying fused linear+allreduce bridge (ix_full_bridge_fused_ar.so)" for src in "${EX_ENGINE_DIR}/prebuilt/ix_full_bridge_fused_ar.so" \ "${SCRIPT_DIR}/prebuilt/corex-3.2.3-ivcore10/ix_full_bridge_fused_ar.so"; do if [[ -f "$src" ]]; then cp "$src" "${VLLM_ROOT}/ex_engine/ix_full_bridge_fused_ar.so" 2>/dev/null || true cp "$src" "${VLLM_ROOT}/model_executor/models/ix_full_bridge_fused_ar.so" 2>/dev/null || true echo "[patch_ops] deployed ix_full_bridge_fused_ar.so from prebuilt" break fi done build_stage "deploying all ex_engine Python modules" EX_PY_DIR="${VLLM_ROOT}/ex_engine/python" mkdir -p "${EX_PY_DIR}" if [[ -d "${EX_ENGINE_DIR}/python" ]]; then cp "${EX_ENGINE_DIR}/python/"*.py "${EX_PY_DIR}/" 2>/dev/null echo "[patch_ops] deployed $(ls -1 "${EX_PY_DIR}"/*.py 2>/dev/null | wc -l) Python modules → ${EX_PY_DIR}/" fi build_stage "patching chat template for non-thinking mode" MODEL_DIR="${MODEL_DIR:-/model}" if [ -f "${MODEL_DIR}/tokenizer_config.json" ]; then python3 ./patch_chat_template.py "${MODEL_DIR}" || \ echo "[patch_ops] WARNING: chat template patch failed" else echo "[patch_ops] WARNING: ${MODEL_DIR}/tokenizer_config.json not found" fi build_stage "compiling submission Python sources" find . -path './wheels' -prune -o -name '*.py' -print0 | xargs -0 python3 -m py_compile build_stage "verifying dlopen chain" python3 ./verify_dlopen_chain.py --vllm-root "${VLLM_ROOT}" || { echo "[WARN] dlopen chain verification found issues (non-fatal)" } build_stage "patch script completed"