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mysql 5.6 导入sql时提示【MySql】Specified key was too long; max key length is 767 bytes

关闭此限制后,索引前缀的大小将可以达到3072字节。

SHOW variables like 'innodb_large_prefix';
1.如果查询的值是OFF的话 执行下面命令

SET GLOBAL INNODB_LARGE_PREFIX = ON;
1.另外,innodb_large_prefix这个属性在5.6上是默认关闭的,而在5.7上是默认开启的。

执行完了 之后 还得查看当前的innodb_file_format引擎格式类型是不是BARRACUDA

执行SHOW variables like 'innodb_file_format';

1.如果不是的话则需要修改

SET GLOBAL innodb_file_format = BARRACUDA;

docker 启动数据库 :service mysql start

docker 启动ssh服务:service ssh start

飞牛docker 安装显卡,https://club.fnnas.com/forum.php?mod=viewthread&tid=14106&highlight=

飞牛docker 显卡启动报错无权限,参考:https://club.fnnas.com/forum.php?mod=viewthread&tid=19860

cmake -D CMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \

  -D CMAKE_BUILD_TYPE=Release \
  -D CMAKE_INSTALL_PREFIX=install \
  -D ANDROID_ABI=armeabi-v7a \
  -D ANDROID_PLATFORM=android-21 \
  -D BUILD_SHARED_LIBS=ON \
  -D BUILD_opencv_core=ON \
  -D BUILD_opencv_imgproc=ON \
  -D BUILD_opencv_features2d=ON \
  -D BUILD_opencv_world=OFF \
  -D BUILD_TESTS=OFF \
  -D BUILD_PERF_TESTS=OFF \
  -D BUILD_EXAMPLES=OFF \
  -D BUILD_opencv_calib3d=OFF \
  -D BUILD_opencv_dnn=OFF \
  -D BUILD_opencv_ml=OFF \
  -D BUILD_opencv_objdetect=OFF \
  -D BUILD_opencv_photo=OFF \
  -D BUILD_opencv_video=OFF \
  -D BUILD_opencv_videoio=OFF \
  -D BUILD_opencv_highgui=OFF \
  -D BUILD_opencv_imgcodecs=OFF \
  -D BUILD_opencv_shape=OFF \
  -D BUILD_opencv_stitching=OFF \
  -D BUILD_opencv_superres=OFF \
  -D BUILD_opencv_ts=OFF \
  -D BUILD_opencv_flann=OFF \
  -D BUILD_opencv_gapi=OFF \
  -D BUILD_opencv_java=OFF \
  -D OPENCV_ENABLE_NONFREE=OFF \
  -D BUILD_ANDROID_PROJECTS=OFF \
  ..




nmcli接管无线网卡
sudo nmcli device set wlp0s20f3 managed yes

nmcli连接网络
nmcli device wifi connect ChinaNet-9RSk password 123456

断开网络
nmcli connection down ChinaNet-9RSk

连接网络
nmcli connection up ChinaNet-9RSk

自动连接脚本

!/bin/bash

INTERFACE="wlp0s20f3"
CONNECTION_NAME="ChinaNet-9RSk"
if ! nmcli device status | grep "$INTERFACE" | grep -q "connected"; then

echo "WiFi down, reconnecting..."
sudo nmcli connection down "$CONNECTION_NAME"
sudo nmcli connection up "$CONNECTION_NAME"

fi

创建虚拟环境指定版本:virtualenv venv --python=pythonx.x.x

CPU使用率高
./build/examples/alpha_zero_torch_example --game=new_game --actors=28 --evaluators=4 --inference_threads=4 --inference_batch_size=1 --train_batch_size=1024 --inference_cache=2621440 --max_simulations=100 --path=./point --checkpoint_freq=10 --max_steps=100 --verbose=false --devices=cuda:0,cpu --replay_buffer_size=655360 --explicit_learning=true

GPU利用率高
./build/examples/alpha_zero_torch_example --game=new_game --actors=20 --inference_batch_size=6 --inference_threads=3 --evaluators=4 --inference_cache=2621440 --max_simulations=100 --path=./point --checkpoint_freq=10 --max_steps=100 --devices=cuda:0,cpu --replay_buffer_size=655360 --explicit_learning=true

查看GPU驱动
watch -n 1 nvidia-smi
watch -n 1 gpustat

安装gpu驱动
sudo apt purge '^nvidia-.*'
sudo apt purge '^cuda-.*'
sudo apt purge '^libcuda.*'
sudo apt autoremove
sudo apt clean
ubuntu-drivers devices
nvcc -V
export PATH=/usr/local/cuda-12.1/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-12.1/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

开启Cmake 调试日志
-DCMAKE_CXX_FLAGS="-fsanitize=address -g" \
-DCMAKE_CXX_FLAGS_DEBUG="-O0" \

在alpha_zero训练时无法显示错误,如何定位错误
1.检查coredump设置,如果输出为0,则表示coredump被禁用了。
ulimit -c

2.启用coredump
ulimit -c unlimited

3.配置coredump文件的保存位置
echo "/tmp/core.%e.%p" | sudo tee /proc/sys/kernel/core_pattern

4.修改open_spiel/scripts/build_and_run_tests.sh 199行-DBUILD_TYPE=Debug

5.修改open_spiel/CMakeLists.txt 46行,set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -g -O0")

6.运行gdb ./build/examples/alpha_zero_torch_example /tmp/core.alpha_zero_torc.444708

7.bt显示错误信息

8.frame 0定位错误

9.list 上下文错误位置