Files
project_6/qwen3_6_scripts/patch_ops.sh
Claude ed8bdf8714 fix(CRITICAL): merge 26e6cb40 build pipeline + HEAD features — fix docker build
Key changes:
1. Dockerfile: restore ex_engine COPY + build steps from 26e6cb40 (working),
   add vendor_overrides staging, add ix_unified_bridge build step
2. computility-run.yaml: restore Sub168 proven params (max-model-len=80000,
   gpu-util=0.95, max-num-seqs=2, enforce-eager, dtype=half) + corex env vars
3. patch_ops.sh: make vendor_overrides missing non-fatal (skip instead of exit 2)
4. New: corex_so_loader.py — unified loader for 12 prebuilt .so
5. New: moe_fused_dispatch.py — 3-tier MoE dispatch (CCCL policy_selector)

Docker build was failing because:
- HEAD removed ex_engine COPY and all build steps
- patch_ops.sh exit 2 on missing vendor_overrides killed build
- computility-run.yaml had max-model-len=262144 causing OOM

26e6cb40 scored on competition platform. This commit restores that build
pipeline while adding the new HEAD features (prebuilt .so, vllm_overrides,
corex dispatch env vars).
2026-08-11 07:58:14 +00:00

338 lines
16 KiB
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Executable File

#!/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
# NOTE: intentionally NO set -e — individual patch failures must NOT abort
# the entire build. Each step logs its own errors, and non-critical patches
# (xformers, diagnostics) may legitimately fail if the base image differs.
set -uo pipefail
build_stage() { printf '[BI100 BUILD] %s\n' "$1" >&2; }
require_file() {
local path=$1
[[ -f "$path" ]] || {
printf '[WARN] patch source missing (non-fatal): %s\n' "$path" >&2
return 1
}
}
install_patch_file() {
local source=$1
local target=$2
require_file "$source" || return 0
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-${TRANSFORMERS_REQUIRED_VERSION}"*.whl >/dev/null 2>&1; then
python3 -m pip install --no-index --no-deps --find-links="${WHEEL_DIR}" \
"transformers==${TRANSFORMERS_REQUIRED_VERSION}"
else
echo "[WARN] offline wheel not found, trying pip install" >&2
pip install "transformers==${TRANSFORMERS_REQUIRED_VERSION}" --timeout 30 2>&1 || \
echo "[WARN] transformers install failed (non-fatal, base image may work)" >&2
fi
fi
python3 - "$TRANSFORMERS_REQUIRED_VERSION" <<'PY' || echo "[WARN] transformers version check failed (non-fatal)"
import importlib.metadata
import sys
required = sys.argv[1]
try:
installed = importlib.metadata.version("transformers")
if installed != required:
print(f"[WARN] transformers: expected {required}, got {installed}")
else:
print(f"[ok] transformers {installed}")
except Exception as e:
print(f"[WARN] transformers check error: {e}")
PY
build_stage "discovering Python package roots"
python3 - <<'PY' > /tmp/qwen36_patch_paths.env
from patch_utils import package_root, shell_env_line
print(shell_env_line("VLLM_ROOT", package_root("vllm")))
print(shell_env_line("TRANSFORMERS_ROOT", package_root("transformers")))
PY
source /tmp/qwen36_patch_paths.env
echo "VLLM_ROOT=${VLLM_ROOT}"
echo "TRANSFORMERS_ROOT=${TRANSFORMERS_ROOT}"
[[ -d "$VLLM_ROOT" ]] || {
printf 'vLLM root does not exist: %s\n' "$VLLM_ROOT" >&2
exit 2
}
VLLM_OVERRIDE_ROOT="./vendor_overrides/vllm"
_HAS_OVERRIDES=true
[[ -d "$VLLM_OVERRIDE_ROOT" ]] || {
printf '[WARN] vLLM override directory missing: %s — skipping override installs\n' "$VLLM_OVERRIDE_ROOT" >&2
_HAS_OVERRIDES=false
}
# --- Mirror path: base image may have TWO vllm installs ---
# VLLM_ROOT (from importlib) is typically /usr/local/lib/python3.10/site-packages/vllm
# but PYTHONPATH puts /usr/local/corex/lib/python3/dist-packages/vllm first at runtime.
# We must deploy to BOTH or the runtime loads the unpatched copy.
VLLM2=""
for _candidate in \
/usr/local/corex/lib/python3/dist-packages/vllm \
/usr/local/corex/lib64/python3/dist-packages/vllm \
/usr/local/lib/python3.10/site-packages/vllm; do
if [[ -d "$_candidate" && "$_candidate" != "$VLLM_ROOT" ]]; then
VLLM2="$_candidate"
break
fi
done
if [[ -n "$VLLM2" ]]; then
echo "VLLM2=${VLLM2} (will mirror all patches)"
else
echo "VLLM2=<none> (single vllm install)"
fi
# Helper: copy to VLLM_ROOT and VLLM2 (if exists)
deploy_both() {
local src="$1" rel="$2"
cp "$src" "${VLLM_ROOT}/${rel}"
[[ -n "$VLLM2" ]] && cp "$src" "${VLLM2}/${rel}" 2>/dev/null || true
}
if $_HAS_OVERRIDES; then
build_stage "installing authoritative vLLM core block overrides"
install_patch_file \
"${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" \
"${VLLM_ROOT}/model_executor/layers/sampler.py"
else
build_stage "skipping vLLM core block overrides (vendor_overrides not found)"
fi
build_stage "installing hash-pinned CoreX 3.2.3 extensions"
bash ./install_prebuilt_corex.sh "${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 2>&1 || echo "[WARN] patch_corex_swap_blocks failed (non-fatal)"
python3 ./patch_block_major_cache_engine.py 2>&1 || echo "[WARN] patch_block_major_cache_engine failed (non-fatal)"
python3 ./patch_worker_cache_transfer_order.py 2>&1 || echo "[WARN] patch_worker_cache_transfer_order failed (non-fatal)"
# --- 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 "${VLLM_ROOT}/attention/ops/paged_attn.py"
# --- model_runner.py: fix prefix_cache_hit stays True in chunked-prefill chunk 2+ ---
# Bug: _compute_for_prefix_cache_hit Case 1 (prefix_cache_len <= context_len)
# leaves prefix_cache_hit=True. Then _add_seq_group uses block_table=computed_block_nums
# (only the original prefix blocks), ignoring chunk-1 KV cache blocks.
# _forward_prefix_pytorch then gets an undersized block_tables and crashes with
# "amax(): Expected reduction dim -1 to have non-zero size" on the 2nd tile.
# Fix: set prefix_cache_hit=False for Case 1 so the full block_tables is used.
python3 ./patch_model_runner.py 2>&1 || echo "[WARN] patch_model_runner failed (non-fatal)"
build_stage "installing executor startup diagnostics"
python3 ./patch_executor_startup_debug.py 2>&1 || echo "[WARN] patch_executor_startup_debug failed (non-fatal)"
python3 ./patch_worker_startup_profile_guard.py 2>&1 || echo "[WARN] patch_worker_startup_profile_guard failed (non-fatal)"
python3 ./patch_block_major_worker_capacity.py 2>&1 || echo "[WARN] patch_block_major_worker_capacity failed (non-fatal)"
build_stage "installing transformers Qwen3.5 model support"
cp -r ./qwen3_5 "${TRANSFORMERS_ROOT}/models/"
cp -r ./qwen3_5_moe "${TRANSFORMERS_ROOT}/models/"
python3 ./patch_transformers_qwen3_5.py 2>&1 || echo "[WARN] patch_transformers_qwen3_5 failed (non-fatal)"
build_stage "installing vLLM Qwen3.6 model implementation"
# --- vllm model: Qwen3.6-35B-A3B (Qwen3_5 MoE arch) -------------------------
cp ./mamba_cache.py "${VLLM_ROOT}/model_executor/models/"
cp ./qwen3_5.py "${VLLM_ROOT}/model_executor/models/qwen3_5.py"
python3 ./patch_vllm_qwen3_5.py 2>&1 || echo "[WARN] patch_vllm_qwen3_5 failed (non-fatal)"
# --- sequence.py: fix completion_tokens inflation under chunked prefill ------
# Bug: get_output_token_ids_to_return(delta=True) with num_new_tokens=0
# returns _cached_all_token_ids[-0:] == [0:] (the ENTIRE prompt+output list).
# Each prefill chunk step adds prompt_len to previous_num_tokens, so a 10K
# prompt processed in 3 chunks inflates completion_tokens by ~30K.
# Also adds num_cached_tokens field to RequestMetrics for prefix-cache stats.
cp ./sequence.py "${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 "${VLLM_ROOT}/core/scheduler.py"
build_stage "installing diagnostic initial allocation trace"
python3 ./patch_block_manager_cache_trace.py 2>&1 || echo "[WARN] patch_block_manager_cache_trace failed (non-fatal)"
build_stage "installing scheduler and attention patches"
# --- xformers: bypass cudnnFlashAttnForward (head_dim=256 > 128 limit) ------
# Injects _run_sdpa_fallback (pure matmul+softmax) into xformers.py.
# Required because head_dim=256 > 128 and ixformer flash attention either
# crashes (is_causal=True) or produces wrong output (attn_mask path).
# The fallback uses query_start_loc to derive actual query lengths, so it
# works correctly during profiling runs with chunked-prefill-style batches.
# also bypasses auto chunked prefill on
python3 ./patch_xformers_sdpa_seq.py 2>&1 || echo "[WARN] patch_xformers_sdpa_seq failed (non-fatal)"
python3 ./patch_xformers_profile.py 2>&1 || echo "[WARN] patch_xformers_profile failed (non-fatal)"
build_stage "installing API parsers and serving modules"
# --- tool parser: Qwen3 XML tool call format ---------------------------------
# Registers "qwen3_coder" parser for Qwen3.6 XML-style tool calls:
# <tool_call><function=name><parameter=key>\nvalue\n</parameter></function></tool_call>
# Use at server start: --tool-call-parser qwen3_coder --enable-auto-tool-choice
cp ./qwen3coder_tool_parser.py "${VLLM_ROOT}/entrypoints/openai/tool_parsers/"
python3 ./patch_vllm_tool_parser.py 2>&1 || echo "[WARN] patch_vllm_tool_parser failed (non-fatal)"
# --- reasoning parser: Qwen3 <think>...</think> 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' || echo "[WARN] api_server identity check failed"
from pathlib import Path
import sys
source = Path(sys.argv[1]).read_bytes()
installed = Path(sys.argv[2]).read_bytes()
if source != installed:
print("[WARN] runtime api_server overlay identity mismatch")
PY
# --- Mirror ALL patched files to VLLM2 (if a second vllm install exists) ---
if [[ -n "$VLLM2" ]]; then
build_stage "mirroring patches to VLLM2=${VLLM2}"
# Critical: paged_attn.py (context_attention_fwd NameError without this)
cp "${VLLM_ROOT}/attention/ops/paged_attn.py" \
"${VLLM2}/attention/ops/paged_attn.py" 2>/dev/null || true
# Model
cp "${VLLM_ROOT}/model_executor/models/qwen3_5.py" \
"${VLLM2}/model_executor/models/qwen3_5.py" 2>/dev/null || true
cp "${VLLM_ROOT}/model_executor/models/mamba_cache.py" \
"${VLLM2}/model_executor/models/mamba_cache.py" 2>/dev/null || true
# Runtime modules
for f in bi100_env.py bi100_profile.py block_major_kv_cache.py \
gdn_prefix.py sequence.py; do
cp "${VLLM_ROOT}/${f}" "${VLLM2}/${f}" 2>/dev/null || true
done
# Core
cp "${VLLM_ROOT}/core/scheduler.py" \
"${VLLM2}/core/scheduler.py" 2>/dev/null || true
# Serving
for f in protocol.py cli_args.py serving_chat.py serving_tokenization.py \
api_server.py; do
cp "${VLLM_ROOT}/entrypoints/openai/${f}" \
"${VLLM2}/entrypoints/openai/${f}" 2>/dev/null || true
done
cp "${VLLM_ROOT}/entrypoints/chat_utils.py" \
"${VLLM2}/entrypoints/chat_utils.py" 2>/dev/null || true
# Tool parsers
cp "${VLLM_ROOT}/entrypoints/openai/tool_parsers/qwen3coder_tool_parser.py" \
"${VLLM2}/entrypoints/openai/tool_parsers/qwen3coder_tool_parser.py" 2>/dev/null || true
# Reasoning
cp -r "${VLLM_ROOT}/reasoning" "${VLLM2}/" 2>/dev/null || true
# Prebuilt CoreX .so extensions
for so in "${VLLM_ROOT}"/corex_*.so; do
[[ -f "$so" ]] && cp "$so" "${VLLM2}/" 2>/dev/null || true
done
# Block overrides
for f in core/evictor_v2.py core/block_manager_v2.py \
core/block/cpu_kv_content_cache.py core/block/cpu_gpu_block_allocator.py \
core/block/prefix_caching_block.py core/block/block_table.py \
model_executor/sampling_metadata.py model_executor/layers/sampler.py \
sampling_params.py; do
if [[ -f "${VLLM_ROOT}/${f}" ]]; then
mkdir -p "$(dirname "${VLLM2}/${f}")"
cp "${VLLM_ROOT}/${f}" "${VLLM2}/${f}" 2>/dev/null || true
fi
done
echo "[ok] mirrored all patches to VLLM2"
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 "patch script completed"