深海游弋的鱼 – 第 2 页

ubuntu 22.04升级到cpp-12后flutter编译报错"找不到 -lstdc++"

在今天晚上 ubuntu 22.04 执行如下升级命令之后

$ sudo apt-get dist-upgrade 
正在读取软件包列表... 完成
正在分析软件包的依赖关系树... 完成
正在读取状态信息... 完成                 
正在计算更新... 完成
下列【新】软件包将被安装：
  cpp-12 gcc-12 libasan8 libgcc-12-dev libtsan2
下列软件包将被升级：
  apport apport-gtk dkms firmware-sof-signed libexpat1 libexpat1:i386
  libexpat1-dev libflac8 libfreerdp-client2-2 libfreerdp-server2-2
  libfreerdp2-2 libwinpr2-2 python3-apport python3-problem-report rsync
  xserver-common xserver-xephyr xserver-xorg-core xserver-xorg-legacy xwayland
升级了 20 个软件包，新安装了 5 个软件包，要卸载 0 个软件包，有 0 个软件包未被升级。

$ sudo apt-get dist-upgrade

正在读取软件包列表... 完成

正在分析软件包的依赖关系树... 完成

正在读取状态信息... 完成

正在计算更新... 完成

下列【新】软件包将被安装：

cpp-12 gcc-12 libasan8 libgcc-12-dev libtsan2

下列软件包将被升级：

apport apport-gtk dkms firmware-sof-signed libexpat1 libexpat1:i386

libexpat1-dev libflac8 libfreerdp-client2-2 libfreerdp-server2-2

libfreerdp2-2 libwinpr2-2 python3-apport python3-problem-report rsync

xserver-common xserver-xephyr xserver-xorg-core xserver-xorg-legacy xwayland

升级了 20 个软件包，新安装了 5 个软件包，要卸载 0 个软件包，有 0 个软件包未被升级。

再次执行 flutter 的构建命令，报错。

操作过程如下：

$ flutter run
Launching lib/main.dart on Linux in debug mode...
Building Linux application...
/usr/include/glib-2.0/glib/glib-typeof.h:39:10: fatal error: 'type_traits' file not found
/usr/include/glib-2.0/glib/glib-typeof.h:39:10: fatal error: 'type_traits' file not found
Exception: Build process failed

$ flutter --version
Flutter 3.3.9 • channel stable • https://github.com/flutter/flutter.git
Framework • revision b8f7f1f986 (2 天前) • 2022-11-23 06:43:51 +0900
Engine • revision 8f2221fbef
Tools • Dart 2.18.5 • DevTools 2.15.0

$ flutter clean

$ flutter run
Multiple devices found:
Linux (desktop) • linux  • linux-x64      • Ubuntu 22.04.1 LTS 5.15.0-53-generic
Chrome (web)    • chrome • web-javascript • Chromium 107.0.5304.110
[1]: Linux (linux)
[2]: Chrome (chrome)
Please choose one (To quit, press "q/Q"): 1
Running "flutter pub get" in xxxx...                            6.2s
Launching lib/main.dart on Linux in debug mode...
CMake Error at /usr/share/cmake-3.22/Modules/CMakeTestCXXCompiler.cmake:62 (message):
  The C++ compiler

    "/usr/bin/clang++"

  is not able to compile a simple test program.

  It fails with the following output:

    Change Dir: /home/xxxx/xxxx/xxxxx/build/linux/x64/debug/CMakeFiles/CMakeTmp

    Run Build Command(s):/usr/bin/ninja cmTC_8cfda && [1/2] Building CXX object CMakeFiles/cmTC_8cfda.dir/testCXXCompiler.cxx.o
    [2/2] Linking CXX executable cmTC_8cfda
    FAILED: cmTC_8cfda 
    : && /usr/bin/clang++   CMakeFiles/cmTC_8cfda.dir/testCXXCompiler.cxx.o -o cmTC_8cfda   && :
    /usr/bin/ld: 找不到 -lstdc++: 没有那个文件或目录
    clang: error: linker command failed with exit code 1 (use -v to see invocation)
    ninja: build stopped: subcommand failed.


  CMake will not be able to correctly generate this project.
Call Stack (most recent call first):
  CMakeLists.txt:3 (project)

Building Linux application...                                           
Exception: Unable to generate build files

$ flutter run

Launching lib/main.dart on Linux in debug mode...

Building Linux application...

/usr/include/glib-2.0/glib/glib-typeof.h:39:10: fatal error: 'type_traits' file not found

Exception: Build process failed

$ flutter --version

Flutter 3.3.9 • channel stable • https://github.com/flutter/flutter.git

Framework • revision b8f7f1f986 (2 天前) • 2022-11-23 06:43:51 +0900

Engine • revision 8f2221fbef

Tools • Dart 2.18.5 • DevTools 2.15.0

$ flutter clean

$ flutter run

Multiple devices found:

Linux (desktop) • linux • linux-x64 • Ubuntu 22.04.1 LTS 5.15.0-53-generic

Chrome (web) • chrome • web-javascript • Chromium 107.0.5304.110

[1]: Linux (linux)

[2]: Chrome (chrome)

Please choose one (To quit, press "q/Q"): 1

Running "flutter pub get" in xxxx... 6.2s

Launching lib/main.dart on Linux in debug mode...

CMake Error at /usr/share/cmake-3.22/Modules/CMakeTestCXXCompiler.cmake:62 (message):

The C++ compiler

"/usr/bin/clang++"

is not able to compile a simple test program.

It fails with the following output:

Change Dir: /home/xxxx/xxxx/xxxxx/build/linux/x64/debug/CMakeFiles/CMakeTmp

Run Build Command(s):/usr/bin/ninja cmTC_8cfda && [1/2] Building CXX object CMakeFiles/cmTC_8cfda.dir/testCXXCompiler.cxx.o

[2/2] Linking CXX executable cmTC_8cfda

FAILED: cmTC_8cfda

: && /usr/bin/clang++ CMakeFiles/cmTC_8cfda.dir/testCXXCompiler.cxx.o -o cmTC_8cfda && :

/usr/bin/ld: 找不到 -lstdc++: 没有那个文件或目录

clang: error: linker command failed with exit code 1 (use -v to see invocation)

ninja: build stopped: subcommand failed.

CMake will not be able to correctly generate this project.

Call Stack (most recent call first):

CMakeLists.txt:3 (project)

Building Linux application...

Exception: Unable to generate build files

解决方法是手工安装依赖：

$ sudo apt install lib32stdc++-12-dev

1	$ sudo apt install lib32stdc++-12-dev

之后再执行构建命令。

参考链接

联想T440在ubuntu 22.04系统上安装配置指纹

家里有一台旧的联想T440笔记本，某天来了兴致安装了ubuntu 22.04，默认情况下指纹识别是无法使用的。

查看硬件属于 Elan 指纹识别设备，Ubuntu 自带的 Libfprint 已经提供了支持。

安装前端工具

$ sudo apt install fprintd libpam-fprintd

1	$ sudo apt install fprintd libpam-fprintd

执行

$ sudo pam-auth-update

1	$ sudo pam-auth-update

将第一项，用空格勾选上，然后点“确定”。这样就授权指纹识别登录设备。

录入指纹

打开“设置---用户---指纹登录”，此时就可以打开了。点击“+”，录入第一个指纹吧

参考链接

联想小新Air2020锐龙版在Ubuntu下添加指纹识别

Flutter The Linux toolchain CMake build dependency (CMake 3.14 or higher is required. You are running version 3.10.2)

在 ubuntu 22.04 通过 snap 安装了 Flutter SDK（当前是Flutter 3.3.4)，如果第三方的依赖了 CMake 3.10.2 更高的版本，会在编译的时候报错：

CMake 3.14 or higher is required. You are running version 3.10.2

1	CMake 3.14 or higher is required. You are running version 3.10.2

这个报错的原因是由于 snap 安装的 Flutter SDK 构建了一个沙箱环境，在这个环境中的 CMake 是 3.10.2 版本，不管系统安装的是哪个版本的 CMake ，都是无效的。

要解决这个问题，或者等待 snap 的 Flutter SDK 更新版本，或者参照 Linux install Flutter 的说明，手工安装并配置 Flutter SDK 。

可以参考如下代码：

$ sudo snap remove flutter

$ sudo apt-get install curl

$ sudo apt-get install clang

$ sudo apt-get install git

$ sudo apt-get install ninja-build

$ sudo apt-get install pkg-config

$ sudo apt install gettext

$ sudo apt-get install libgtk-3-dev

$ sudo apt install libstdc++-12-dev

$ git clone https://github.com/flutter/flutter.git -b stable

$ export PATH="$PATH:`pwd`/flutter/bin"

$ cd `pwd`/flutter/bin 

$ ./flutter doctor

$ sudo snap remove flutter

$ sudo apt-get install curl

$ sudo apt-get install clang

$ sudo apt-get install git

$ sudo apt-get install ninja-build

$ sudo apt-get install pkg-config

$ sudo apt install gettext

$ sudo apt-get install libgtk-3-dev

$ sudo apt install libstdc++-12-dev

$ git clone https://github.com/flutter/flutter.git -b stable

$ export PATH="$PATH:`pwd`/flutter/bin"

$ cd `pwd`/flutter/bin

$ ./flutter doctor

参考链接

ubuntu 20.04升级到ubuntu 22.04报错“update-alternatives: 错误: /var/lib/dpkg/alternatives/mpi 损坏：次要链接与主链接 /usr/bin/mpicc 相同”

ubuntu 20.04 升级到 ubuntu 22.04 报错,报错内容如下：

正在设置 openmpi-bin (4.1.2-2ubuntu1) ...
update-alternatives: 错误: /var/lib/dpkg/alternatives/mpi 损坏：次要链接与主链接 /usr/bin/mpicc 相同
dpkg: 处理软件包 openmpi-bin (--configure)时出错：
 已安装 openmpi-bin 软件包 post-installation 脚本 子进程返回错误状态 2
dpkg: 依赖关系问题使得 mpi-default-bin 的配置工作不能继续：
 mpi-default-bin 依赖于 openmpi-bin；然而：
  软件包 openmpi-bin 尚未配置。

dpkg: 处理软件包 mpi-default-bin (--configure)时出错：
 依赖关系问题 - 仍未被配置
dpkg: 依赖关系问题使得 libcoarrays-openmpi-dev:amd64 的配置工作不能继续：
 libcoarrays-openmpi-dev:amd64 依赖于 openmpi-bin；然而：
  软件包 openmpi-bin 尚未配置。

dpkg: 处理软件包 libcoarrays-openmpi-dev:amd64 (--configure)时出错：
 依赖关系问题 - 仍未被配置
dpkg: 依赖关系问题使得 libopenmpi-dev:amd64 的配置工作不能继续：
 libopenmpi-dev:amd64 依赖于 openmpi-bin (>= 3.0.0-1)；然而：
  软件包 openmpi-bin 尚未配置。

dpkg: 处理软件包 libopenmpi-dev:amd64 (--configure)时出错：
 依赖关系问题 - 仍未被配置
dpkg: 依赖关系问题使得 libboost-mpi-python1.74.0 的配置工作不能继续：
 libboost-mpi-python1.74.0 依赖因为错误消息指示这是由于上一个问题导致的错误，没有写入 apport 报告。
                  因为错误消息指示这是由于上一个问题导致的错误，没有写入 apport 报告。
      由于已经达到 MaxReports 限制，没有写入 apport 报告。
                                                          由于已经达到 MaxReports 限制，没有写入 apport 报告。
                              由于已经达到 MaxReports 限制，没有写入 apport 报告。
  由于已经达到 MaxReports 限制，没有写入 apport 报告。
                                                      由于已经达到 MaxReports 限制，没有写入 apport 报告。
                          由于已经达到 MaxReports 限制，没有写入 apport 报告。
                                                                              由于已经达到 MaxReports 限制，没有写入 apport 报告。
                                                  由于已经达到 MaxReports 限制，没有写入 apport 报告。
                      由于 mpi-default-bin；然而：
  软件包 mpi-default-bin 尚未配置。

dpkg: 处理软件包 libboost-mpi-python1.74.0 (--configure)时出错：
 依赖关系问题 - 仍未被配置
dpkg: 依赖关系问题使得 libboost-mpi-python1.74-dev 的配置工作不能继续：
 libboost-mpi-python1.74-dev 依赖于 libboost-mpi-python1.74.0 (= 1.74.0-14ubuntu3)；然而：
  软件包 libboost-mpi-python1.74.0 尚未配置。

dpkg: 处理软件包 libboost-mpi-python1.74-dev (--configure)时出错：
 依赖关系问题 - 仍未被配置
dpkg: 依赖关系问题使得 libboost-mpi-python-dev 的配置工作不能继续：
 libboost-mpi-python-dev 依赖于 libboost-mpi-python1.74-dev；然而：
  软件包 libboost-mpi-python1.74-dev 尚未配置。

dpkg: 处理软件包 libboost-mpi-python-dev (--configure)时出错：
 依赖关系问题 - 仍未被配置
dpkg: 依赖关系问题使得 libboost-all-dev 的配置工作不能继续：
 libboost-all-dev 依赖于 libboost-mpi-python-dev；然而：
  软件包 libboost-mpi-python-dev 尚未配置。

dpkg: 处理软件包 libboost-all-dev (--configure)时出错：
 依赖关系问题 - 仍未被配置
dpkg: 依赖关系问题使得 mpi-default-dev 的配置工作不能继续：
 mpi-default-dev 依赖于 libopenmpi-dev；然而：
  软件包 libopenmpi-dev:amd64 尚未配置。

dpkg: 处理软件包 mpi-default-dev (--configure)时出错：
 依赖关系问题 - 仍未被配置
dpkg: 依赖关系问题使得 libboost-mpi1.74-dev 的配置工作不能继续：
 libboost-mpi1.74-dev 依赖于 mpi-default-dev；然而：
  软件包 mpi-default-dev 尚未配置。

dpkg: 处理软件包 libboost-mpi1.74-dev (--configure)时出错：
 依赖关系问题 - 仍未被配置
dpkg: 依赖关系问题使得 libboost-mpi-dev 的配置工作不能继续：
 libboost-mpi-dev 依赖于 libboost-mpi1.74-dev；然而：
  软件包 libboost-mpi1.74-dev 尚未配置。

dpkg: 处理软件包 libboost-mpi-dev (--configure)时出错：
 依赖关系问题 - 仍未被配置
在处理时有错误发生：
 openmpi-bin
 mpi-default-bin
 libcoarrays-openmpi-dev:amd64
 libopenmpi-dev:amd64
 libboost-mpi-python1.74.0
 libboost-mpi-python1.74-dev
 libboost-mpi-python-dev
 libboost-all-dev
 mpi-default-dev
 libboost-mpi1.74-dev
 libboost-mpi-dev
E: Sub-process /usr/bin/dpkg returned an error code (1)

正在设置 openmpi-bin (4.1.2-2ubuntu1) ...

update-alternatives: 错误: /var/lib/dpkg/alternatives/mpi 损坏：次要链接与主链接 /usr/bin/mpicc 相同

dpkg: 处理软件包 openmpi-bin (--configure)时出错：

已安装 openmpi-bin 软件包 post-installation 脚本子进程返回错误状态 2

dpkg: 依赖关系问题使得 mpi-default-bin 的配置工作不能继续：

mpi-default-bin 依赖于 openmpi-bin；然而：

软件包 openmpi-bin 尚未配置。

dpkg: 处理软件包 mpi-default-bin (--configure)时出错：

依赖关系问题 - 仍未被配置

dpkg: 依赖关系问题使得 libcoarrays-openmpi-dev:amd64 的配置工作不能继续：

libcoarrays-openmpi-dev:amd64 依赖于 openmpi-bin；然而：

软件包 openmpi-bin 尚未配置。

dpkg: 处理软件包 libcoarrays-openmpi-dev:amd64 (--configure)时出错：

依赖关系问题 - 仍未被配置

dpkg: 依赖关系问题使得 libopenmpi-dev:amd64 的配置工作不能继续：

libopenmpi-dev:amd64 依赖于 openmpi-bin (>= 3.0.0-1)；然而：

软件包 openmpi-bin 尚未配置。

dpkg: 处理软件包 libopenmpi-dev:amd64 (--configure)时出错：

依赖关系问题 - 仍未被配置

dpkg: 依赖关系问题使得 libboost-mpi-python1.74.0 的配置工作不能继续：

libboost-mpi-python1.74.0 依赖因为错误消息指示这是由于上一个问题导致的错误，没有写入 apport 报告。

因为错误消息指示这是由于上一个问题导致的错误，没有写入 apport 报告。

由于已经达到 MaxReports 限制，没有写入 apport 报告。

由于 mpi-default-bin；然而：

软件包 mpi-default-bin 尚未配置。

dpkg: 处理软件包 libboost-mpi-python1.74.0 (--configure)时出错：

依赖关系问题 - 仍未被配置

dpkg: 依赖关系问题使得 libboost-mpi-python1.74-dev 的配置工作不能继续：

libboost-mpi-python1.74-dev 依赖于 libboost-mpi-python1.74.0 (= 1.74.0-14ubuntu3)；然而：

软件包 libboost-mpi-python1.74.0 尚未配置。

dpkg: 处理软件包 libboost-mpi-python1.74-dev (--configure)时出错：

依赖关系问题 - 仍未被配置

dpkg: 依赖关系问题使得 libboost-mpi-python-dev 的配置工作不能继续：

libboost-mpi-python-dev 依赖于 libboost-mpi-python1.74-dev；然而：

软件包 libboost-mpi-python1.74-dev 尚未配置。

dpkg: 处理软件包 libboost-mpi-python-dev (--configure)时出错：

依赖关系问题 - 仍未被配置

dpkg: 依赖关系问题使得 libboost-all-dev 的配置工作不能继续：

libboost-all-dev 依赖于 libboost-mpi-python-dev；然而：

软件包 libboost-mpi-python-dev 尚未配置。

dpkg: 处理软件包 libboost-all-dev (--configure)时出错：

依赖关系问题 - 仍未被配置

dpkg: 依赖关系问题使得 mpi-default-dev 的配置工作不能继续：

mpi-default-dev 依赖于 libopenmpi-dev；然而：

软件包 libopenmpi-dev:amd64 尚未配置。

dpkg: 处理软件包 mpi-default-dev (--configure)时出错：

依赖关系问题 - 仍未被配置

dpkg: 依赖关系问题使得 libboost-mpi1.74-dev 的配置工作不能继续：

libboost-mpi1.74-dev 依赖于 mpi-default-dev；然而：

软件包 mpi-default-dev 尚未配置。

dpkg: 处理软件包 libboost-mpi1.74-dev (--configure)时出错：

依赖关系问题 - 仍未被配置

dpkg: 依赖关系问题使得 libboost-mpi-dev 的配置工作不能继续：

libboost-mpi-dev 依赖于 libboost-mpi1.74-dev；然而：

软件包 libboost-mpi1.74-dev 尚未配置。

dpkg: 处理软件包 libboost-mpi-dev (--configure)时出错：

依赖关系问题 - 仍未被配置

在处理时有错误发生：

openmpi-bin

mpi-default-bin

libcoarrays-openmpi-dev:amd64

libopenmpi-dev:amd64

libboost-mpi-python1.74.0

libboost-mpi-python1.74-dev

libboost-mpi-python-dev

libboost-all-dev

mpi-default-dev

libboost-mpi1.74-dev

libboost-mpi-dev

E: Sub-process /usr/bin/dpkg returned an error code (1)

解决方法：

$ sudo mv /var/lib/dpkg/alternatives/mpi /var/lib/dpkg/alternatives/mpi.bak

$ sudo apt-get dist-upgrade

$ sudo mv /var/lib/dpkg/alternatives/mpi /var/lib/dpkg/alternatives/mpi.bak

$ sudo apt-get dist-upgrade

ubuntu 20.04.4系统升级后全部应用图标都无法显示

ubuntu 20.04.4系统执行升级命令后全部应用图标都无法显示，系统变成如下图：

很多应用也无法打开了，点击之后无任何反应。

查看系统日志可以看到如下错误信息：

(gnome-calculator:4038): Gtk-WARNING **: 06:23:42.942: Could not load a pixbuf from icon theme.
This may indicate that pixbuf loaders or the mime database could not be found.
**
Gtk:ERROR:../../../../gtk/gtkiconhelper.c:494:ensure_surface_for_gicon: assertion failed (error == NULL): Failed to load /usr/share/icons/Yaru/16x16/status/image-missing.png: Unrecognized image file format (gdk-pixbuf-error-quark, 3)
Bail out! Gtk:ERROR:../../../../gtk/gtkiconhelper.c:494:ensure_surface_for_gicon: assertion failed (error == NULL): Failed to load /usr/share/icons/Yaru/16x16/status/image-missing.png: Unrecognized image file format (gdk-pixbuf-error-quark, 3)
[1]    4038 abort (core dumped)  gnome-calculator

(gnome-calculator:4038): Gtk-WARNING **: 06:23:42.942: Could not load a pixbuf from icon theme.

This may indicate that pixbuf loaders or the mime database could not be found.

Gtk:ERROR:../../../../gtk/gtkiconhelper.c:494:ensure_surface_for_gicon: assertion failed (error == NULL): Failed to load /usr/share/icons/Yaru/16x16/status/image-missing.png: Unrecognized image file format (gdk-pixbuf-error-quark, 3)

Bail out! Gtk:ERROR:../../../../gtk/gtkiconhelper.c:494:ensure_surface_for_gicon: assertion failed (error == NULL): Failed to load /usr/share/icons/Yaru/16x16/status/image-missing.png: Unrecognized image file format (gdk-pixbuf-error-quark, 3)

[1] 4038 abort (core dumped) gnome-calculator

这个原因是由于 gdk-pixbuf 的改动导致的系统 BUG，只需要重新生成一下应用图标缓存即可。

执行如下命令：

$ sudo apt-get install shared-mime-info

$ sudo update-mime-database /usr/share/mime

$ sudo chmod 644 /usr/share/applications/mimeinfo.cache

$ sudo /usr/lib/x86_64-linux-gnu/gdk-pixbuf-2.0/gdk-pixbuf-query-loaders --update-cache

$ sudo apt-get install shared-mime-info

$ sudo update-mime-database /usr/share/mime

$ sudo chmod 644 /usr/share/applications/mimeinfo.cache

$ sudo /usr/lib/x86_64-linux-gnu/gdk-pixbuf-2.0/gdk-pixbuf-query-loaders --update-cache

参考链接

Flutter构建Linux应用

从3.0之后的版本，flutter已经正式支持构建Linux应用

条件

ubuntu 22.04
Android Studio Chipmunk | 2021.2.1
flutter sdk 3.x

方法

1. 打开Linux的平台支持

输入如下指令（如下命令可以使用flutter config查看，2.10以上的版本默认开启）

flutter config --enable-linux-desktop

# 其他平台
flutter config --[no-]enable-macos-desktop

flutter config --[no-]enable-windows-desktop

flutter config --enable-linux-desktop

# 其他平台

flutter config --[no-]enable-macos-desktop

flutter config --[no-]enable-windows-desktop

可以使用flutter doctor查看情况。

安装编译依赖

# 安装Android Studio
$ sudo snap install android-studio --classic

# 安装 Flutter SDK
$ sudo snap install flutter

# 更新 Flutter SDK
$ flutter

$ sudo apt-get install cmake

$ sudo apt-get install ninja-build

$ sudo apt-get install clang

$ sudo apt-get install gtk+-3.0

$ sudo apt-get install libssl-dev

$ sudo apt-get install git

$ sudo apt-get install vim

# 安装Android Studio

$ sudo snap install android-studio --classic

# 安装 Flutter SDK

$ sudo snap install flutter

# 更新 Flutter SDK

$ flutter

$ sudo apt-get install cmake

$ sudo apt-get install ninja-build

$ sudo apt-get install clang

$ sudo apt-get install gtk+-3.0

$ sudo apt-get install libssl-dev

$ sudo apt-get install git

$ sudo apt-get install vim

2. 在旧项目中添加Linux平台支持

在项目地址输入如下指令

flutter create --platforms=linux[,macos,windows] .

1	flutter create --platforms=linux[,macos,windows] .

注意: 项目的名称必须是全小写，如果出现大小写则会报错

"TxxxFxxx" is not a valid Dart package name.

See https://dart.dev/tools/pub/pubspec#name for more information.

"TxxxFxxx" is not a valid Dart package name.

See https://dart.dev/tools/pub/pubspec#name for more information.

3. 构建Linux项目

flutter build linux

1	flutter build linux

4. 报错

Launching lib/main.dart on Linux in debug mode...
Building Linux application...
CMake Error at cmake_install.cmake:66 (file):
  file INSTALL cannot copy file
  "/xxxx/xxxx/build/linux/x64/debug/intermediates_do_not_run/xxx"
  to "/usr/local/xxx": Permission denied.


Exception: Build process failed

Launching lib/main.dart on Linux in debug mode...

Building Linux application...

CMake Error at cmake_install.cmake:66 (file):

file INSTALL cannot copy file

"/xxxx/xxxx/build/linux/x64/debug/intermediates_do_not_run/xxx"

to "/usr/local/xxx": Permission denied.

Exception: Build process failed

出现这个问题

flutter clean //执行这个然后重启 Android Studio

1	flutter clean //执行这个然后重启 Android Studio

参考链接

Visual Studio Code调试Flutter报错“[CHROME]:need to run as root or suid”

在最新的 Ubuntu 22.04 系统上使用Visual Studio Code调试Flutter应用，Chrome使用Snap安装。

通过指定 CHROME_EXECUTABLE=/snap/bin/chromium，在调试的时候，报错如下：

Launching lib/main.dart on Chrome in debug mode...
lib/main.dart:1
[CHROME]:need to run as root or suid
Failed to launch browser after 3 tries. Command used to launch it: /snap/bin/chromium --user-data-dir=/tmp/flutter_tools.SEVTFD/flutter_tools_chrome_device.AMHTFX --remote-debugging-port=38457 --disable-background-timer-throttling --disable-extensions --disable-popup-blocking --bwsi --no-first-run --no-default-browser-check --disable-default-apps --disable-translate http://localhost:42407
Failed to launch browser. Make sure you are using an up-to-date Chrome or Edge. Otherwise, consider using -d web-server instead and filing an issue at https://github.com/flutter/flutter/issues.
Exited (sigterm)

Launching lib/main.dart on Chrome in debug mode...

lib/main.dart:1

[CHROME]:need to run as root or suid

Failed to launch browser after 3 tries. Command used to launch it: /snap/bin/chromium --user-data-dir=/tmp/flutter_tools.SEVTFD/flutter_tools_chrome_device.AMHTFX --remote-debugging-port=38457 --disable-background-timer-throttling --disable-extensions --disable-popup-blocking --bwsi --no-first-run --no-default-browser-check --disable-default-apps --disable-translate http://localhost:42407

Failed to launch browser. Make sure you are using an up-to-date Chrome or Edge. Otherwise, consider using -d web-server instead and filing an issue at https://github.com/flutter/flutter/issues.

Exited (sigterm)

解决方法就是指定真实的Chrome安装路径，直接调用，而不是通过Snap的沙箱，解决沙箱无法调试的问题。

如下：

#export CHROME_EXECUTABLE=/snap/bin/chromium
export CHROME_EXECUTABLE=/snap/chromium/current/usr/lib/chromium-browser/chrome

1 2	#export CHROME_EXECUTABLE=/snap/bin/chromium export CHROME_EXECUTABLE=/snap/chromium/current/usr/lib/chromium-browser/chrome

上述方法同样可以解决 Android Studio 在 Ubuntu 22.04 系统上无法找到 Chrome 的问题。

参考链接

How to get the snap-based chromium to access a separately mounted filesystem?

解决远程桌面执行sudo启动X应用报错“Gtk-WARNING **: 12:39:47.296: cannot open display: :10.0”

通过远程桌面（RDP）连接到远程Ubuntu服务器桌面，执行调用X窗口应用的时候，报错如下：

$ sudo update-manager
No protocol specified
Unable to init server: Could not connect: Connection refused
No protocol specified
Unable to init server: 无法连接： Connection refused
No protocol specified
Unable to init server: 无法连接： Connection refused

(update-manager:2547): Gtk-WARNING **: 12:39:47.296: cannot open display: :10.0

$ sudo update-manager

No protocol specified

Unable to init server: Could not connect: Connection refused

No protocol specified

Unable to init server: 无法连接： Connection refused

No protocol specified

Unable to init server: 无法连接： Connection refused

(update-manager:2547): Gtk-WARNING **: 12:39:47.296: cannot open display: :10.0

原因为：

XServer默认情况下不允许别的用户的图形程序的图形显示在当前屏幕上。

如果需要别的用户的图形显示在当前屏幕上，则应以当前登陆的用，也就是切换身份前的用户执行如下命令。

当前登陆普通用户执行：xhost +

$ xhost +
access control disabled, clients can connect from any host

$ sudo update-manager

$ xhost +

access control disabled, clients can connect from any host

$ sudo update-manager

参考链接

Ubuntu gedit报错Gtk-WARNING **: cannot open display: 问题解决

禁止ubuntu 20.04/21.10自动休眠

ubuntu 20.04/21.10使用 RDP 远程登陆之后，如果系统较长时间不操作，系统就自动休眠了。

如果重启之后，从来都没有登陆，就不会出现系统自动休眠的情况。

观察系统日志，发现类似如下的内容：

Feb 25 22:15:38 server NetworkManager[737]: <info>  [1582668938.0193] manager: sleep: sleep requested (sleeping: no  enabled: yes)
Feb 25 22:15:38 server NetworkManager[737]: <info>  [1582668938.0239] manager: NetworkManager state is now ASLEEP
Feb 25 22:15:38 server whoopsie[1025]: [22:15:38] offline
Feb 25 22:15:38 server gnome-shell[956]: Screen lock is locked down, not locking
Feb 25 22:15:38 server systemd[1]: Reached target Sleep.
Feb 25 22:15:38 server systemd[1]: Starting Suspend...
Feb 25 22:15:38 server kernel: [ 1235.212537] PM: suspend entry (s2idle)
Feb 25 22:15:38 server systemd-sleep[1705]: Suspending system...

Feb 25 22:15:38 server NetworkManager[737]: <info> [1582668938.0193] manager: sleep: sleep requested (sleeping: no enabled: yes)

Feb 25 22:15:38 server NetworkManager[737]: <info> [1582668938.0239] manager: NetworkManager state is now ASLEEP

Feb 25 22:15:38 server whoopsie[1025]: [22:15:38] offline

Feb 25 22:15:38 server gnome-shell[956]: Screen lock is locked down, not locking

Feb 25 22:15:38 server systemd[1]: Reached target Sleep.

Feb 25 22:15:38 server systemd[1]: Starting Suspend...

Feb 25 22:15:38 server kernel: [ 1235.212537] PM: suspend entry (s2idle)

Feb 25 22:15:38 server systemd-sleep[1705]: Suspending system...

发现是触发了systemd的自动休眠功能，检查休眠功能的状态以及历史记录，如下：

$ systemctl status sleep.target

 ● sleep.target - Sleep
    Loaded: loaded (/lib/systemd/system/sleep.target; static; vendor preset: enabled)
    Active: inactive (dead)
      Docs: man:systemd.special(7)
 Feb 24 13:18:08 xps systemd[1]: Reached target Sleep.
 Feb 26 13:29:31 xps systemd[1]: Stopped target Sleep.
 Feb 26 13:29:57 xps systemd[1]: Reached target Sleep.
 Feb 26 13:30:19 xps systemd[1]: Stopped target Sleep.

$ systemctl status sleep.target

● sleep.target - Sleep

Loaded: loaded (/lib/systemd/system/sleep.target; static; vendor preset: enabled)

Active: inactive (dead)

Docs: man:systemd.special(7)

Feb 24 13:18:08 xps systemd[1]: Reached target Sleep.

Feb 26 13:29:31 xps systemd[1]: Stopped target Sleep.

Feb 26 13:29:57 xps systemd[1]: Reached target Sleep.

Feb 26 13:30:19 xps systemd[1]: Stopped target Sleep.

普通桌面应用这个情况问题不大，但是如果是作为服务器使用的时候，我们一般远程访问系统，这个功能就会导致我们无法远程控制服务器，因此我们需要关闭这个功能。

执行关闭休眠功能的命令，如下：

$ sudo systemctl mask sleep.target suspend.target hibernate.target hybrid-sleep.target

 Created symlink /etc/systemd/system/sleep.target → /dev/null.
 Created symlink /etc/systemd/system/suspend.target → /dev/null.
 Created symlink /etc/systemd/system/hibernate.target → /dev/null.
 Created symlink /etc/systemd/system/hybrid-sleep.target → /dev/null.

$ sudo systemctl mask sleep.target suspend.target hibernate.target hybrid-sleep.target

Created symlink /etc/systemd/system/sleep.target → /dev/null.

Created symlink /etc/systemd/system/suspend.target → /dev/null.

Created symlink /etc/systemd/system/hibernate.target → /dev/null.

Created symlink /etc/systemd/system/hybrid-sleep.target → /dev/null.

再次观察系统休眠状态，如下：

$ systemctl status sleep.target

● sleep.target
   Loaded: masked (Reason: Unit sleep.target is masked.)
   Active: inactive (dead)

$ systemctl status sleep.target

● sleep.target

Loaded: masked (Reason: Unit sleep.target is masked.)

Active: inactive (dead)

发现自动休眠功能已经被关闭，不会出现自动休眠导致远程控制无法访问的情况了。

参考链接

禁止ubuntu 20.04自动休眠

ubuntu 21.10(GeForce GTX 3060 12GB)编译StyleGAN3

安装驱动：

# 清理全部的其他版本的nvidia驱动
$ sudo apt-get purge nvidia-*

$ sudo reboot

# nvidia-smi
$ sudo apt install nvidia-utils-470

# 驱动
$ sudo apt install nvidia-driver-470

# cuda 11.3 
$ sudo apt install nvidia-cuda-toolkit

$ sudo apt-get update

# 部分驱动可能会更新，需要执行更新，否则可能依旧不正常
$ sudo apt-get dist-upgrade

$ sudo apt-get autoremove

# 重启，否则部分驱动可能工作不正常
$ sudo reboot

# 清理全部的其他版本的nvidia驱动

$ sudo apt-get purge nvidia-*

$ sudo reboot

# nvidia-smi

$ sudo apt install nvidia-utils-470

# 驱动

$ sudo apt install nvidia-driver-470

# cuda 11.3

$ sudo apt install nvidia-cuda-toolkit

$ sudo apt-get update

# 部分驱动可能会更新，需要执行更新，否则可能依旧不正常

$ sudo apt-get dist-upgrade

$ sudo apt-get autoremove

# 重启，否则部分驱动可能工作不正常

$ sudo reboot

在 Anaconda 上建立独立的编译环境，然后执行编译：

# wget https://repo.anaconda.com/archive/Anaconda3-2020.02-Linux-x86_64.sh
# 国内镜像下载
$ wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2021.11-Linux-x86_64.sh

$ bash Anaconda3-*-Linux-x86_64.sh

# 更新到最新版本
$ conda update -n base -c defaults conda

# wget https://repo.anaconda.com/archive/Anaconda3-2020.02-Linux-x86_64.sh

# 国内镜像下载

$ wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2021.11-Linux-x86_64.sh

$ bash Anaconda3-*-Linux-x86_64.sh

# 更新到最新版本

$ conda update -n base -c defaults conda

参考 Anaconda conda切换为国内源加速下载。

编译配置StyleGAN3

$ sudo apt-get install git

$ git clone git@github.com:NVlabs/stylegan3.git

$ cd stylegan3

$ conda env create -f environment.yml

$ conda activate stylegan3

$ pip install psutil

# cudnn加速
$ conda install cudnn

# 目前测试 RTX 3060 12GB的情况下，batch建议是2，更高会报告OOM
# 并且当batch低于4的时候，需要同时指定 --mbstd-group=2
$ python train.py --outdir=~/training-runs --cfg=stylegan3-t --data=~/datasets/metfaces-1024x1024.zip --gpus=1 --batch=2 --mbstd-group=2 --gamma=8.2 --mirror=1 --metrics=none

$ sudo apt-get install git

$ git clone git@github.com:NVlabs/stylegan3.git

$ cd stylegan3

$ conda env create -f environment.yml

$ conda activate stylegan3

$ pip install psutil

# cudnn加速

$ conda install cudnn

# 目前测试 RTX 3060 12GB的情况下，batch建议是2，更高会报告OOM

# 并且当batch低于4的时候，需要同时指定 --mbstd-group=2

$ python train.py --outdir=~/training-runs --cfg=stylegan3-t --data=~/datasets/metfaces-1024x1024.zip --gpus=1 --batch=2 --mbstd-group=2 --gamma=8.2 --mirror=1 --metrics=none

如果报错：

Constructing networks...
Setting up PyTorch plugin "bias_act_plugin"... Failed!
Traceback (most recent call last):
  File "~/source/stylegan3/train.py", line 286, in <module>
    main() # pylint: disable=no-value-for-parameter
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1128, in __call__
    return self.main(*args, **kwargs)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1053, in main
    rv = self.invoke(ctx)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1395, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 754, in invoke
    return __callback(*args, **kwargs)
  File "~/source/stylegan3/train.py", line 281, in main
    launch_training(c=c, desc=desc, outdir=opts.outdir, dry_run=opts.dry_run)
  File "~/source/stylegan3/train.py", line 96, in launch_training
    subprocess_fn(rank=0, c=c, temp_dir=temp_dir)
  File "~/source/stylegan3/train.py", line 47, in subprocess_fn
    training_loop.training_loop(rank=rank, **c)
  File "~/source/stylegan3/training/training_loop.py", line 168, in training_loop
    img = misc.print_module_summary(G, [z, c])
  File "~/source/stylegan3/torch_utils/misc.py", line 216, in print_module_summary
    outputs = module(*inputs)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1071, in _call_impl
    result = forward_call(*input, **kwargs)
  File "~/source/stylegan3/training/networks_stylegan3.py", line 511, in forward
    ws = self.mapping(z, c, truncation_psi=truncation_psi, truncation_cutoff=truncation_cutoff, update_emas=update_emas)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1071, in _call_impl
    result = forward_call(*input, **kwargs)
  File "~/source/stylegan3/training/networks_stylegan3.py", line 151, in forward
    x = getattr(self, f'fc{idx}')(x)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1071, in _call_impl
    result = forward_call(*input, **kwargs)
  File "~/source/stylegan3/training/networks_stylegan3.py", line 100, in forward
    x = bias_act.bias_act(x, b, act=self.activation)
  File "~/source/stylegan3/torch_utils/ops/bias_act.py", line 84, in bias_act
    if impl == 'cuda' and x.device.type == 'cuda' and _init():
  File "~/source/stylegan3/torch_utils/ops/bias_act.py", line 41, in _init
    _plugin = custom_ops.get_plugin(
  File "~/source/stylegan3/torch_utils/custom_ops.py", line 136, in get_plugin
    torch.utils.cpp_extension.load(name=module_name, build_directory=cached_build_dir,
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/utils/cpp_extension.py", line 1080, in load
    return _jit_compile(
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/utils/cpp_extension.py", line 1318, in _jit_compile
    return _import_module_from_library(name, build_directory, is_python_module)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/utils/cpp_extension.py", line 1701, in _import_module_from_library
    module = importlib.util.module_from_spec(spec)
  File "<frozen importlib._bootstrap>", line 565, in module_from_spec
  File "<frozen importlib._bootstrap_external>", line 1173, in create_module
  File "<frozen importlib._bootstrap>", line 228, in _call_with_frames_removed
ImportError: ~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/lib/../../../../libstdc++.so.6: version `GLIBCXX_3.4.29' not found (required by ~/.cache/torch_extensions/bias_act_plugin/3cb576a0039689487cfba59279dd6d46-nvidia-geforce-rtx-3060/bias_act_plugin.so)

Constructing networks...

Setting up PyTorch plugin "bias_act_plugin"... Failed!

Traceback (most recent call last):

File "~/source/stylegan3/train.py", line 286, in <module>

main() # pylint: disable=no-value-for-parameter

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1128, in __call__

return self.main(*args, **kwargs)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1053, in main

rv = self.invoke(ctx)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1395, in invoke

return ctx.invoke(self.callback, **ctx.params)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 754, in invoke

return __callback(*args, **kwargs)

File "~/source/stylegan3/train.py", line 281, in main

launch_training(c=c, desc=desc, outdir=opts.outdir, dry_run=opts.dry_run)

File "~/source/stylegan3/train.py", line 96, in launch_training

subprocess_fn(rank=0, c=c, temp_dir=temp_dir)

File "~/source/stylegan3/train.py", line 47, in subprocess_fn

training_loop.training_loop(rank=rank, **c)

File "~/source/stylegan3/training/training_loop.py", line 168, in training_loop

img = misc.print_module_summary(G, [z, c])

File "~/source/stylegan3/torch_utils/misc.py", line 216, in print_module_summary

outputs = module(*inputs)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1071, in _call_impl

result = forward_call(*input, **kwargs)

File "~/source/stylegan3/training/networks_stylegan3.py", line 511, in forward

ws = self.mapping(z, c, truncation_psi=truncation_psi, truncation_cutoff=truncation_cutoff, update_emas=update_emas)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1071, in _call_impl

result = forward_call(*input, **kwargs)

File "~/source/stylegan3/training/networks_stylegan3.py", line 151, in forward

x = getattr(self, f'fc{idx}')(x)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1071, in _call_impl

result = forward_call(*input, **kwargs)

File "~/source/stylegan3/training/networks_stylegan3.py", line 100, in forward

x = bias_act.bias_act(x, b, act=self.activation)

File "~/source/stylegan3/torch_utils/ops/bias_act.py", line 84, in bias_act

if impl == 'cuda' and x.device.type == 'cuda' and _init():

File "~/source/stylegan3/torch_utils/ops/bias_act.py", line 41, in _init

_plugin = custom_ops.get_plugin(

File "~/source/stylegan3/torch_utils/custom_ops.py", line 136, in get_plugin

torch.utils.cpp_extension.load(name=module_name, build_directory=cached_build_dir,

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/utils/cpp_extension.py", line 1080, in load

return _jit_compile(

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/utils/cpp_extension.py", line 1318, in _jit_compile

return _import_module_from_library(name, build_directory, is_python_module)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/utils/cpp_extension.py", line 1701, in _import_module_from_library

module = importlib.util.module_from_spec(spec)

File "<frozen importlib._bootstrap>", line 565, in module_from_spec

File "<frozen importlib._bootstrap_external>", line 1173, in create_module

File "<frozen importlib._bootstrap>", line 228, in _call_with_frames_removed

ImportError: ~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/lib/../../../../libstdc++.so.6: version `GLIBCXX_3.4.29' not found (required by ~/.cache/torch_extensions/bias_act_plugin/3cb576a0039689487cfba59279dd6d46-nvidia-geforce-rtx-3060/bias_act_plugin.so)

上述报错产生的原因是在 Anaconda 下载的包，在进行编译的时候，使用了高版本的 libstdc++.so。而运行时却使用了Anaconda 环境里低版本的 libstdc++.so 导致报错。

了解了原因，解决方法就比较简单了，可以手工升级 Anaconda 环境下的 libstdc++.so 动态库。

如下：

$ conda activate stylegan3

$ conda install cmake

$ conda install make

# 关键升级命令,更新当前项目里面的 libstdc++.so
$ conda install -c conda-forge libstdcxx-ng

# 删除上次失败时候的编译缓存
$ rm -rf ~/.cache

# 目前测试 RTX 3060 12GB的情况下，batch建议是2，更高会报告OOM
# 当batch=4的时候会在第11天的时候报告OOM
# 并且当batch低于4的时候，需要同时指定 --mbstd-group=2
$ python train.py --outdir=~/training-runs --cfg=stylegan3-t --data=~/datasets/metfaces-1024x1024.zip --gpus=1 --batch=2 --mbstd-group=2 --gamma=8.2 --mirror=1 --metrics=none

$ conda activate stylegan3

$ conda install cmake

$ conda install make

# 关键升级命令,更新当前项目里面的 libstdc++.so

$ conda install -c conda-forge libstdcxx-ng

# 删除上次失败时候的编译缓存

$ rm -rf ~/.cache

# 目前测试 RTX 3060 12GB的情况下，batch建议是2，更高会报告OOM

# 当batch=4的时候会在第11天的时候报告OOM

# 并且当batch低于4的时候，需要同时指定 --mbstd-group=2

$ python train.py --outdir=~/training-runs --cfg=stylegan3-t --data=~/datasets/metfaces-1024x1024.zip --gpus=1 --batch=2 --mbstd-group=2 --gamma=8.2 --mirror=1 --metrics=none

目前测试发现，当batch=4的时候会在第11天的时候报告OOM，如下：

tick 444   kimg 1776.0   time 11d 17h 14m  sec/tick 2292.6  sec/kimg 573.16  maintenance 0.2    cpumem 5.40   gpumem 7.69   reserved 10.03  augment 0.344
Traceback (most recent call last):
  File "~/source/stylegan3/train.py", line 286, in <module>
    main() # pylint: disable=no-value-for-parameter
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1128, in __call__
    return self.main(*args, **kwargs)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1053, in main
    rv = self.invoke(ctx)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1395, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 754, in invoke
    return __callback(*args, **kwargs)
  File "~/source/stylegan3/train.py", line 281, in main
    launch_training(c=c, desc=desc, outdir=opts.outdir, dry_run=opts.dry_run)
  File "~/source/stylegan3/train.py", line 96, in launch_training
    subprocess_fn(rank=0, c=c, temp_dir=temp_dir)
  File "~/source/stylegan3/train.py", line 47, in subprocess_fn
    training_loop.training_loop(rank=rank, **c)
  File "~/source/stylegan3/training/training_loop.py", line 278, in training_loop
    loss.accumulate_gradients(phase=phase.name, real_img=real_img, real_c=real_c, gen_z=gen_z, gen_c=gen_c, gain=phase.interval, cur_nimg=cur_nimg)
  File "~/source/stylegan3/training/loss.py", line 81, in accumulate_gradients
    loss_Gmain.mean().mul(gain).backward()
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/_tensor.py", line 255, in backward
    torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/autograd/__init__.py", line 147, in backward
    Variable._execution_engine.run_backward(
  File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/autograd/function.py", line 87, in apply
    return self._forward_cls.backward(self, *args)  # type: ignore[attr-defined]
  File "~/source/stylegan3/torch_utils/ops/grid_sample_gradfix.py", line 50, in backward
    grad_input, grad_grid = _GridSample2dBackward.apply(grad_output, input, grid)
  File "~/source/stylegan3/torch_utils/ops/grid_sample_gradfix.py", line 59, in forward
    grad_input, grad_grid = op(grad_output, input, grid, 0, 0, False)
RuntimeError: CUDA out of memory. Tried to allocate 1.39 GiB (GPU 0; 11.76 GiB total capacity; 7.06 GiB already allocated; 443.88 MiB free; 10.02 GiB reserved in total by PyTorch)

tick 444 kimg 1776.0 time 11d 17h 14m sec/tick 2292.6 sec/kimg 573.16 maintenance 0.2 cpumem 5.40 gpumem 7.69 reserved 10.03 augment 0.344

Traceback (most recent call last):

File "~/source/stylegan3/train.py", line 286, in <module>

main() # pylint: disable=no-value-for-parameter

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1128, in __call__

return self.main(*args, **kwargs)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1053, in main

rv = self.invoke(ctx)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 1395, in invoke

return ctx.invoke(self.callback, **ctx.params)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/click/core.py", line 754, in invoke

return __callback(*args, **kwargs)

File "~/source/stylegan3/train.py", line 281, in main

launch_training(c=c, desc=desc, outdir=opts.outdir, dry_run=opts.dry_run)

File "~/source/stylegan3/train.py", line 96, in launch_training

subprocess_fn(rank=0, c=c, temp_dir=temp_dir)

File "~/source/stylegan3/train.py", line 47, in subprocess_fn

training_loop.training_loop(rank=rank, **c)

File "~/source/stylegan3/training/training_loop.py", line 278, in training_loop

loss.accumulate_gradients(phase=phase.name, real_img=real_img, real_c=real_c, gen_z=gen_z, gen_c=gen_c, gain=phase.interval, cur_nimg=cur_nimg)

File "~/source/stylegan3/training/loss.py", line 81, in accumulate_gradients

loss_Gmain.mean().mul(gain).backward()

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/_tensor.py", line 255, in backward

torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/autograd/__init__.py", line 147, in backward

Variable._execution_engine.run_backward(

File "~/anaconda3/envs/stylegan3/lib/python3.9/site-packages/torch/autograd/function.py", line 87, in apply

return self._forward_cls.backward(self, *args) # type: ignore[attr-defined]

File "~/source/stylegan3/torch_utils/ops/grid_sample_gradfix.py", line 50, in backward

grad_input, grad_grid = _GridSample2dBackward.apply(grad_output, input, grid)

File "~/source/stylegan3/torch_utils/ops/grid_sample_gradfix.py", line 59, in forward

grad_input, grad_grid = op(grad_output, input, grid, 0, 0, False)

RuntimeError: CUDA out of memory. Tried to allocate 1.39 GiB (GPU 0; 11.76 GiB total capacity; 7.06 GiB already allocated; 443.88 MiB free; 10.02 GiB reserved in total by PyTorch)

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