mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 11:56:44 +08:00
64 lines
1.5 KiB
Bash
64 lines
1.5 KiB
Bash
#!/bin/bash
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set -x
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set -e
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cd FastDeploy
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export no_proxy=agent.baidu.com:8118,localhost,127.0.0.1,localaddress,.localdomain.com,.cdn.bcebos.com,.baidu.com,bcebos.com
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export https_proxy=
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export http_proxy=
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export LC_ALL=en_US.UTF-8
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export LANG=en_US.UTF-8
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export LD_LIBRARY_PATH=/usr/local/cuda/compat/:/usr/lib64/:$LD_LIBRARY_PATH
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ldconfig
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python -V
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pwd
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git config --global --add safe.directory /workspace1/FastDeploy
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python -m pip install --force-reinstall --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
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python -m pip install --upgrade --force-reinstall -r requirements/unittest/requirements.txt
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bash tools/build_wheel.sh
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# 获取显存占用最小的gpu
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gpu_info=$(nvidia-smi --query-gpu=index,memory.used --format=csv,noheader,nounits 2>/dev/null)
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if [ -z "$gpu_info" ]; then
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echo "错误: 未找到 GPU 或 nvidia-smi 不可用。"
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exit 1
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fi
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min_vram=999999
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min_gpu=-1
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while read -r line; do
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gpu_id=$(echo "$line" | awk -F', ' '{print $1}' | tr -d ' ')
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vram=$(echo "$line" | awk -F', ' '{print $2}' | tr -d ' ')
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if [ "$vram" -lt "$min_vram" ]; then
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min_vram=$vram
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min_gpu=$gpu_id
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fi
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done <<< "$gpu_info"
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export CUDA_VISIBLE_DEVICES=${min_gpu}
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# 使用 find 命令查找 test 目录下的 .py 文件
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test_files=$(find test -type f -name "test*.py")
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# 遍历每个找到的测试文件
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for test_file in $test_files; do
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python $test_file
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# 检查前一个命令的退出状态码
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if [ $? -ne 0 ]; then
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echo $test_file
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exit 1
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fi
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done
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echo "All tests passed."
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exit 0
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