dockerRun

#!/bin/bash
export MY_CONTAINER="QwQ_env"
num=`sudo docker ps -a|grep "$MY_CONTAINER"|wc -l`
echo $num
echo $MY_CONTAINER

if [ 0 -eq $num ]; then
    sudo xhost +
    sudo docker run \
    --gpus all \
    --net=host --pid=host \
    --shm-size=256G \  # 设置为 512GB 共享内存
    -e DISPLAY=$DISPLAY \
    -v /home/cas/cupming/Qwen:/workspace/Qwen \
    -p 10086:10086 \  # 端口映射，假设你要映射 10086 端口
	-p 8000:8000 \  # 端口映射，假设你要映射 8000端口
    --ulimit memlock=-1:-1 \  # 取消内存锁定限制
    --ulimit stack=536870912  \  # 设置线程的最大栈大小为512MB
    --ipc=host \  # 允许共享主机的共享内存
    -it --privileged --name $MY_CONTAINER \
    -w /workspace/dataset \
    nvcr.io/nvidia/pytorch:25.02-py3 \
    /bin/bash
else
    sudo docker start $MY_CONTAINER
    #sudo docker attach $MY_CONTAINER
    sudo docker exec -w /workspace/dataset/  -ti $MY_CONTAINER /bin/bash
fi

#!/bin/bash
set -x  # 启用调试模式
export MY_CONTAINER="QwQ_env"
num=$(sudo docker ps -a | grep "$MY_CONTAINER" | wc -l)
echo $num
echo $MY_CONTAINER

if [ 0 -eq $num ]; then
    sudo xhost +local:docker
    export DISPLAY=$(echo $DISPLAY)
    if [ -z "$DISPLAY" ]; then
        export DISPLAY=:0
    fi
    sudo docker run \
        --gpus all \
        --net=host \
        --pid=host \
        --shm-size=256G \
        -e DISPLAY=$DISPLAY \
        -v /home/cas/cupming/Qwen:/workspace/Qwen \
        -p 10086:10086 \
        -p 8000:8000 \
        --ulimit memlock=-1:-1 \
        --ulimit stack=536870912 \
        --ipc=host \
        -it \
        --privileged \
        --name $MY_CONTAINER \
        -w /workspace/Qwen \
        nvcr.io/nvidia/pytorch:25.02-py3 \
        /bin/bash
else
    sudo docker start $MY_CONTAINER
    sudo docker exec -w /workspace/Qwen -ti $MY_CONTAINER /bin/bash
fi