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* Add debug environment variable exports Added debug environment variable exports for CLANG_PATH and XVLLM_PATH. * Lock paddlepaddle-xpu version in CI script Temporarily lock paddlepaddle-xpu version due to framework update issues. * Update no_proxy environment variable in CI workflow * Install lsof tool in run_ci_xpu.sh * Update dependency versions for stable release * Update paddlepaddle-xpu installation command
168 lines
4.9 KiB
Bash
168 lines
4.9 KiB
Bash
#!/bin/bash
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DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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echo "$DIR"
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#安装lsof工具
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apt install -y lsof
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#先kill一遍
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ps -efww | grep -E 'api_server' | grep -v grep | awk '{print $2}' | xargs kill -9 || true
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ps -efww | grep -E '8188' | grep -v grep | awk '{print $2}' | xargs kill -9 || true
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lsof -t -i :8188 | xargs kill -9 || true
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export model_path=${MODEL_PATH}/data/eb45t_4_layer
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echo "pip requirements"
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python -m pip install -r requirements.txt
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echo "uninstall org"
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python -m pip uninstall paddlepaddle-xpu -y
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python -m pip uninstall fastdeploy-xpu -y
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# 由于主框架更新存在问题,暂时锁死版本
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python -m pip install paddlepaddle-xpu -i https://www.paddlepaddle.org.cn/packages/nightly/xpu-p800/
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# python -m pip install https://paddle-whl.bj.bcebos.com/nightly/xpu-p800/paddlepaddle-xpu/paddlepaddle_xpu-3.0.0.dev20250901-cp310-cp310-linux_x86_64.whl
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echo "build whl"
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bash custom_ops/xpu_ops/src/download_dependencies.sh develop
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export CLANG_PATH=$(pwd)/custom_ops/xpu_ops/src/third_party/xtdk
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export XVLLM_PATH=$(pwd)/custom_ops/xpu_ops/src/third_party/xvllm
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bash build.sh || exit 1
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echo "pip others"
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python -m pip install openai -U
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python -m pip uninstall -y triton
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python -m pip install triton==3.3.0
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unset http_proxy
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unset https_proxy
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unset no_proxy
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# 起服务
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rm -rf log/*
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rm -f core*
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# pkill -9 python #流水线不执行这个
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#清空消息队列
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ipcrm --all=msg
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export XPU_VISIBLE_DEVICES="0,1,2,3"
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python -m fastdeploy.entrypoints.openai.api_server \
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--model ${model_path} \
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--port 8188 \
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--tensor-parallel-size 4 \
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--num-gpu-blocks-override 16384 \
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--max-model-len 32768 \
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--max-num-seqs 128 \
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--quantization wint4 > server.log 2>&1 &
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sleep 60
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# 探活
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TIMEOUT=$((5 * 60))
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INTERVAL=10 # 检查间隔(秒)
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ENDPOINT="http://0.0.0.0:8188/health"
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START_TIME=$(date +%s) # 记录开始时间戳
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echo "开始服务健康检查,最长等待时间:${TIMEOUT}秒"
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while true; do
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# 计算已耗时
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CURRENT_TIME=$(date +%s)
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ELAPSED=$((CURRENT_TIME - START_TIME))
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# 超时判断
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if [ $ELAPSED -ge $TIMEOUT ]; then
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echo -e "\n服务启动超时:经过 $((TIMEOUT/60)) 分钟服务仍未启动!"
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cat server.log
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cat log/workerlog.0
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exit 1
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fi
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HTTP_CODE=$(curl -s -o /dev/null -w "%{http_code}" -m 2 "$ENDPOINT" || true)
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if [ "$HTTP_CODE" = "200" ]; then
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echo -e "\n服务启动成功!耗时 ${ELAPSED} 秒"
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break
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else
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sleep $INTERVAL
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fi
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done
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cat server.log
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# 执行服务化推理
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python tests/ci_use/XPU_45T/run_45T.py
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exit_code=$?
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echo exit_code is ${exit_code}
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ps -efww | grep -E 'api_server' | grep -v grep | awk '{print $2}' | xargs kill -9 || true
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ps -efww | grep -E '8188' | grep -v grep | awk '{print $2}' | xargs kill -9 || true
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lsof -t -i :8188 | xargs kill -9 || true
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if [ ${exit_code} -ne 0 ]; then
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echo "log/workerlog.0"
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cat log/workerlog.0
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echo "模型起服务失败,请检查pr代码"
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exit 1
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fi
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sleep 5
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#0731新增kv block集中式管理相关测试,在起服务时启用对应环境变量 export ENABLE_V1_KVCACHE_SCHEDULER=True
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# 起服务
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rm -rf log/*
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rm -f core*
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# pkill -9 python #流水线不执行这个
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#清空消息队列
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ipcrm --all=msg
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export ENABLE_V1_KVCACHE_SCHEDULER=1
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export XPU_VISIBLE_DEVICES="0,1,2,3"
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python -m fastdeploy.entrypoints.openai.api_server \
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--model ${model_path} \
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--port 8188 \
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--tensor-parallel-size 4 \
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--num-gpu-blocks-override 16384 \
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--max-model-len 32768 \
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--max-num-seqs 128 \
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--quantization wint4 > server.log 2>&1 &
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sleep 60
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# 探活
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TIMEOUT=$((5 * 60))
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INTERVAL=10 # 检查间隔(秒)
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ENDPOINT="http://0.0.0.0:8188/health"
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START_TIME=$(date +%s) # 记录开始时间戳
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echo "开始服务健康检查,最长等待时间:${TIMEOUT}秒"
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while true; do
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# 计算已耗时
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CURRENT_TIME=$(date +%s)
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ELAPSED=$((CURRENT_TIME - START_TIME))
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# 超时判断
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if [ $ELAPSED -ge $TIMEOUT ]; then
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echo -e "\n服务启动超时:经过 $((TIMEOUT/60)) 分钟服务仍未启动!"
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cat server.log
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cat log/workerlog.0
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exit 1
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fi
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HTTP_CODE=$(curl -s -o /dev/null -w "%{http_code}" -m 2 "$ENDPOINT" || true)
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if [ "$HTTP_CODE" = "200" ]; then
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echo -e "\n服务启动成功!耗时 ${ELAPSED} 秒"
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break
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else
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sleep $INTERVAL
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fi
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done
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cat server.log
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# 执行服务化推理
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python tests/ci_use/XPU_45T/run_45T.py
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kv_block_test_exit_code=$?
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echo kv_block_test_exit_code is ${kv_block_test_exit_code}
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unset ENABLE_V1_KVCACHE_SCHEDULER
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ps -efww | grep -E 'api_server' | grep -v grep | awk '{print $2}' | xargs kill -9 || true
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ps -efww | grep -E '8188' | grep -v grep | awk '{print $2}' | xargs kill -9 || true
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lsof -t -i :8188 | xargs kill -9 || true
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if [ ${kv_block_test_exit_code} -ne 0 ]; then
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echo "log/workerlog.0"
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cat log/workerlog.0
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echo "kv block相关测试失败,请检查pr代码"
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exit 1
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fi
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