I have been trying to install Install-Package Google.Apis.Drive.v3 using this source with the difference that I have Ubuntu-18.04 instead of Windows.
I know it may be a simple question but I have been trying research how to do that from this morning. I installed sudo apt install nuget on my machine and have been trying to add packages or as in this case the Google.Apis.Drive.v3 package but no luck.
I went through this source which was useful, but does not carry information I was able to replicate on my Linux machine.
Also this source, this one and this one too. But also this last one is for Windows and was not very useful.
How do I install Google Apis Drive V3 via command line easily as it is documented for windows but on Ubunbtu-18.04?
Thanks for pointing to the right direction for solving this problem.
Solution
The way you install your Drive API's library is depending on the programming language you are aiming to use. These are the following commands to run depending on the different languages to interact with the API (with their respective links to the source of the setup):
Python:
pip install --upgrade google-api-python-client google-auth-httplib2 google-auth-oauthlib
C#/.NET:
Create a new Visual C# Console Application project in Visual Studio.
Open the NuGet Package Manager Console, select the package source nuget.org, and run the following command:
">Install-Package Google.Apis.Drive.v3
Java:
gradle init --type basic
mkdir -p src/main/java src/main/resources
Node.js:
npm install googleapis#39 --save
For the Browser check out the steps to follow here
I hope this has helped you. Let me know if you need anything else or if you did not understood something.
NOTE: For all Ubuntu-18.04 users that wish to install via command line the correct way is: sudo dotnet add package Google.Apis.Drive.v3
I need to install Mysql-server in an Ubuntu 18 machine which do not have any internet access. There are plethora of instruction material exist on this this subject but all they require Ubuntu machine to be online.
One such documentation can be available here (quite comprehensive though)
https://www.digitalocean.com/community/tutorials/how-to-install-mysql-on-ubuntu-18-04
Any help on offline installation of Mysql-server will be highly helpful.
I suggest you follow this guide on how to use apt-offline. https://linoxide.com/debian/install-debian-packages-offline/
As a general guide:
You start by having apt-offline installed on both PCs, this is done by default on the desktop releases, but can easily be installed by just downloading the .deb package for your release from the packages.ubuntu.com website: https://packages.ubuntu.com/bionic/all/apt-offline/download
Then create a signature that can be put onto another PC that'll do the downloading/fetching updates and make a note that we also need mysql-server
apt-offline set offline-servers-state.sig --install-packages mysql-server
You can then use this signature on a PC connected to the internet using the same tool to check for updates and/or download the required files into a zip file
apt-offline get --bundle zip/file/location/bundle.zip offline-servers-state.sig
Once downloaded you can put this .zip back on the offline server to install the packages
apt-offline install zip/file/location/bundle.zip
You can visit https://dev.mysql.com/downloads/mysql/ from a computer that can go online.
Then, select your OS and version
Download DEB Bundle on a computer that can go online. Move the downloaded file internally to your system that cannot hit the Internet.
Your downloaded file will be a .tar. Use command tar -xvf filename.tar (See https://www.cyberciti.biz/faq/tar-extract-linux/ for command).
You will get a new directory. cd that-directory will get you in that directory. You will see a bunch of .deb files.
Install the deb files one by one using sudo apt-get install filename.deb depending on what you want to install. Other commands to install deb files can be found in this discussion https://unix.stackexchange.com/questions/159094/how-to-install-a-deb-file-by-dpkg-i-or-by-apt.
I am attempting to install closed source software from Silego, GreenPAK Designer, on a machine running Fedora 19. The supported installation packages on Silego's Website only target Ubuntu and Debian. I downloaded the .deb package and used Alien to convert to an RPM. So far so good, but a dry run of yum install showed dependency errors, which I solved by installing the necessary packages with yum:
qt5-qbase
qt5-qbase-gui
qt5-qtdeclarative
qt5-qtlocation
qwt
Now, yum installed the above libraries in /usr/lib/ but the GreenPAK RPM defaults to /usr/local/bin as the output dir. I figured I could run
sudo yum localinstall --nodeps --noscripts greenpak-designer-x.x.x.rpm
and get a successful install but I received conflict errors relating to dirs such as '/', '/usr', '/usr/bin' etc. I worked around this issue with:
rpmrebuild -pe --notest-install --replacefiles --noscripts greenpak-designer.x.x.x.rpm
and removing the offending lines in the script. It allowed me to install rpm but the software is broken because of dependency issues (not surprisingly). From the system log:
Jan 4 16:06:49 pelican gnome-session[1729]: /usr/local/greenpak-designer/bin/GP5: error while loading shared libraries: libicui18n.so.52: cannot open shared object file: No such file or directory
The machine has a /usr/lib/libicui18n.so.50
One thing I did not try is rebuilding my shared object cache with ldconfig, which sometimes solves problems with missing .so links when building from source but I don't see how that would apply in this instance (I'm not trying to link object files to libraries, rather simply trying to drop binaries in default install locations, no?)
Of course, I contacted the vendor and begged for an RPM. The contact was helpful but informed me the software folks are on a well deserved break. I thought I'd continue puttering with this in the meantime while I have time.
Any ideas? It seems the solution to this problem would be helpful when trying to install almost any closed source software targeting Debian on a Fedora box.
I know that I can install Cuda with the following:
wget http://developer.download.nvidia.com/compute/cuda/7_0/Prod/local_installers/cuda_7.0.28_linux.run
chmod +x cuda_7.0.28_linux.run
./cuda_7.0.28_linux.run -extract=`pwd`/nvidia_installers
cd nvidia_installers
sudo ./NVIDIA-Linux-x86_64-346.46.run
sudo modprobe nvidia
sudo ./cuda-linux64-rel-7.0.28-19326674.run
Just wondering if I can install Cuda without root?
Thanks,
Update The installation UI for 10.1 changed. The following works:
Deselect driver installation (pressing ENTERon it)
Change options -> root install path to a non-sudo directory.
Press A on the line marked with a + to access advanced options. Deselect create symbolic link, and change the toolkit install path.
Now installation should work without root permissions
Thank you very much for the hints in the question! I just want to complete it with an approach that worked for me, also inspired in this gist and that hopefully helps in situations where a valid driver is installed, and installing a more recent CUDA on Linux without root permissions is still needed.
TL;DR: Here are the steps to install CUDA9+CUDNN7 on Debian, and installing a pre-compiled version of TensorFlow1.4 on Python2.7 to test that everything works. Everything without root privileges and via terminal. Should also work for other CUDA, CUDNN, TensorFlow and Python versions on other Linux systems too.
INSTALLATION
Go to NVIDIA's official release web for CUDA (as for Nov. 2017, CUDA9 is out): https://developer.nvidia.com/cuda-downloads.
Under your Linux distro, select the runfile (local)option. Note that the sudo indication present in the installation instructions is deceiving, since it is possible to run this installer without root permissions. On a server, one easy way is to copy the <LINK> of the Download button and, in any location of your home directory, run wget <LINK>. It will download the <INSTALLER> file.
Run chmod +x <INSTALLER> to make it executable, and execute it ./<INSTALLER>.
accept the EULA, say no to driver installation, and enter a <CUDA> location under your home directory to install the toolkit and a <CUDASAMPLES> for the samples.
Not asked here but recommended: Download a compatible CUDNN file from the official web (you need to sign in). In my case, I downloaded the cudnn-9.0-linux-x64-v7.tgz, compatible with CUDA9 into the <CUDNN> folder. Uncompress it: tar -xzvf ....
Optional: compile the samples. cd <CUDASAMPLES> && make. There are some very nice examples there and a very good starting point to write some CUDA scripts of yourself.
(If you did 5.): Copy the required files from <CUDNN> into <CUDA>, and grant reading permission to user (not sure if needed):
cp -P <CUDNN>/cuda/include/cudnn.h <CUDA>/include/
cp -P <CUDNN>/cuda/lib64/libcudnn* <CUDA>/lib64
chmod a+r <CUDA>/include/cudnn.h <CUDA>/lib64/libcudnn*
Add the library to your environment. This is typically done adding this following two lines to your ~/.bashrc file (in this example, the <CUDA> directory was ~/cuda9/:
export PATH=<CUDA>/bin:$PATH
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<CUDA>/lib64/
FOR QUICK TESTING OR TENSORFLOW USERS
The quickest way to get a TensorFlow compatible with CUDA9 and CUDNN7 (and a very quick way to test this) is to download a precompiled wheel file and install it with pip install <WHEEL>. Most of the versions you need, can be found in mind's repo (thanks a lot guys). A minimal test that confirms that CUDNN is also working involves the use of tf.nn.conv2d:
import tensorflow as tf
x = tf.nn.conv2d(tf.ones([1,1,10,1]), tf.ones([1,5,1,1]), strides=[1, 1, 1, 1], padding='SAME')
with tf.Session() as sess:
sess.run(x) # this should output a tensor of shape (1,1,10,1) with [3,4,5,5,5,5,5,5,4,3]
In my case, the wheel I installed required Intel's MKL library, as explained here. Again, from terminal and without root users, this are the steps I followed to install the library and make TensorFlow find it (reference):
git clone https://github.com/01org/mkl-dnn.git
cd mkl-dnn/scripts && ./prepare_mkl.sh && cd ..
mkdir -p build && cd build
cmake -D CMAKE_INSTALL_PREFIX:PATH=<TARGET_DIR_IN_HOME> ..
make # this takes a while
make doc # do this optionally if you have doxygen
make test # also takes a while
make install # installs into <TARGET_DIR_IN_HOME>
add the following to your ~/.bashrc: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<TARGET_DIR_IN_HOME>/lib
Hope this helps!
Andres
You can install using conda with the following command.
conda install -c anaconda cudatoolkit
But you need to have prior accesss to the device(GPU).
EDIT : If you are finding error in anaconda repository then change the repository to conda-forge which is frequently updated.
conda install -c conda-forge cudatoolkit
You can install CUDA and compile programs, but you won't be able to run them for a lack of device access.
This is a pretty dumb question. I am trying to install Fedora on a virtual machine (the open source VirtualBox seems like the best option). I downloaded it from somewhere, and I have the rpm instead of the iso. If it were just the ISO I could simply mount it using virtual clone drive and then I would be able to install it on virtualBox, because it would think that it is a cd. But how do I do that with an RPM? I get the impression that an RPM is simply a packaging format like a .rar or .zip but how do I install this thing on virtualBox? Find some kind of unrapper for an rpm and then install? Or is there a simpler way.
Sorry, but you're not going to be able to install Fedora onto a VirtualBox VM from the RPM file. There's nothing out there that will produce an ISO from the RPM, but that's the only type of file your VM will be able to mount as a install medium. You'll have to download the ISO.