mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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67 lines
1.8 KiB
Bash
67 lines
1.8 KiB
Bash
#!/bin/bash
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set -e
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# Test splitwise deployment
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# v0 requires prefill and decode in one node and it uses local scheduler
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# v1 supports prefill and decode in multi node and it uses splitwise scheduler
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# v2 supports prefill and decode in multi node and it uses router and local scheduler
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wait_for_health() {
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local server_port=$1
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while true; do
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status_code=$(curl -s -o /dev/null -w "%{http_code}" "http://0.0.0.0:${server_port}/health" || echo "000")
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if [ "$status_code" -eq 200 ]; then
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break
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else
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echo "Service not ready. Retrying in 2s..."
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sleep 2
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fi
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done
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}
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MODEL_NAME="PaddlePaddle/ERNIE-4.5-0.3B-Paddle"
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# MODEL_NAME="baidu/ERNIE-4.5-21B-A3B-Paddle"
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aistudio download --model ${MODEL_NAME}
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unset http_proxy && unset https_proxy
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rm -rf log_*
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# start prefill
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export FD_LOG_DIR="log_prefill"
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mkdir -p ${FD_LOG_DIR}
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export CUDA_VISIBLE_DEVICES=0
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export FD_DEBUG=1
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export ENABLE_V1_KVCACHE_SCHEDULER=0
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nohup python -m fastdeploy.entrypoints.openai.api_server \
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--model ${MODEL_NAME} \
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--port 8100 \
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--metrics-port 8101 \
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--engine-worker-queue-port 8102 \
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--cache-queue-port 8103 \
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--max-model-len 32768 \
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--splitwise-role "prefill" \
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2>&1 >${FD_LOG_DIR}/nohup &
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wait_for_health 8100
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# start decode
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export FD_LOG_DIR="log_decode"
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mkdir -p ${FD_LOG_DIR}
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export CUDA_VISIBLE_DEVICES=1
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export FD_DEBUG=1
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export ENABLE_V1_KVCACHE_SCHEDULER=0
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nohup python -m fastdeploy.entrypoints.openai.api_server \
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--model ${MODEL_NAME} \
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--port 9000 \
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--metrics-port 9001 \
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--engine-worker-queue-port 9002 \
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--cache-queue-port 9003 \
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--max-model-len 32768 \
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--splitwise-role "decode" \
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--innode-prefill-ports 8102 \
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2>&1 >${FD_LOG_DIR}/nohup &
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wait_for_health 9000
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