Due to unfortunate reason of cpu, CPU dont support avx instruction and so Openvino toolkit not working in my machine.
I have model in my drive ,
How can i use the openvino run convert the model in IR using google colab.
I will just put commands here, might explain lines later. I have set up openvino 2019 R3 version with google colab, steps are as follows:
!sudo apt-get install pciutils
!sudo apt-get update -y && sudo apt-get install -y cpio
!lscpu
!cat /etc/os-release
!wget http://registrationcenter-download.intel.com/akdlm/irc_nas/16057/l_openvino_toolkit_p_2019.3.376.tgz
!tar -xvzf l_openvino_toolkit_p_2019.3.376.tgz
!cd l_openvino_toolkit_p_2019.3.376/ && bash install.sh
!source /opt/intel/openvino/bin/setupvars.sh
!/opt/intel/openvino/deployment_tools/model_optimizer/install_prerequisites /install_prerequisites.sh
!source /opt/intel/openvino/bin/setupvars.sh && \ /opt/intel/openvino/deployment_tools/demo/demo_squeezenet_download_convert_run.sh
You can try some example Google Colab notebook like this one: link. Better to post more specific questions on Stack Overflow regarding how to install as opposed to say asking like an open question.
But if I were you, I would use the official information as a reference since Google Colab runs on a Linux-based hosted machine: Official documentation.
This package seems to be a good way to use openvino in google colab:
https://github.com/alihussainia/openvino-colab
!pip install openvino-colab
import openvino_colab
And you are ready to use openvino at /opt/intel/openvino ...
I managed to run the inference engine on colab. Also, it is possible to create xml and bin files from pretrained models.
Explained here: https://medium.com/analytics-vidhya/intel-openvino-on-google-colab-20ac8d2eede6
Related
I am attempting to utilize the rocker/r-apt image which enables R binary installs.
My 72 Minute Docker Build using the r-base image could use some help...
My file looks like this.
FROM container.registry/rocker/r-apt:bionic
RUN apt-get update
Couple of notes. My company uses an internal registry, so i've downloaded the image from
https://hub.docker.com/r/rocker/r-apt
and pushed it to my local container registry.
When I try and build the Docker container it gives me this error.
UPDATE - Full Error message
/deb.debian.org/debian testing InRelease
The following signatures couldn't be verified because the public key is not available: NO_PUBKEY 04EE7237B7D453EC NO_PUBKEY 648ACFD622F3D138
I can post a more detailed error message when the internet on my other computer returns.
I realize now that bionic is the Ubuntu distro. r-base uses a debian base from what I can tell.
My big question..what am I doing wrong to get this rocker/r-apt image to run correctly and still allow me to use apt-get to install a number of things, include the cran-r packages that its supposed to enable.
I am following this post by datawookie.
https://datawookie.netlify.app/blog/2019/01/docker-images-for-r-r-base-versus-r-apt/
UPDATE
My new big question... should i be pointing at deb.debian.org/debian for apt-get?
I would suggest to use rocker/r-ubuntu instead of rocker/r-apt (which predates it). I am the man behind the curtain for both.
Within Rocker we have containers based on Debian, and containers based on Ubuntu, and containers based on Debian now that will likely be based on Ubuntu in the future. In short, "it's complicated" but that is in part ... because we have so darn many containers already.
The source for background information is still our R Journal paper (shortcut to pdf).
Success!!! So the R-Ubuntu 20.04 appears to be working like a charm.
My outcome of decreasing the build time of my R application has worked.
72 Minutes is now 4 Minutes
This is important because our applications run in CI/CD pipelines and so a 72 minute build is extremely annoying. Not to mention consumes lots of resources to compile code.
It looks like all my issues were related to my organizations Nexus Repository.
Once we downloaded the R-Ubuntu, we had to rebuild it from the GIT Repo to utilize our internal Ubuntu Image. That fixed 1 problem.
Then I had to import the Michael Rutter Repo as a source and update that to utilize the internal repository.
The one issue that might not be apparent is that the DockerFile has to have the apt-get update and installs in the correct order. I do not recall if the source image had all this, but I'll post the order here.
RUN apt-get update \
&& apt-get install -y --no-install-recommends \
&& apt-get install -y gnupg2 \
&& apt-get install -y --no-install-recommends \
dialog \
software-properties-common \
ed \
less \
locales \
vim-tiny \
wget \
ca-certificates
So once all that was setup it worked like magic.
The setup I have is like this: I have two sets of libraries that are compiled for amd64 (pc) and armelx (ARM). They are both used to cross-compile some software on a build machine.
The first ones (amd64) can be updated without hassle by updating the apt-repository and using apt-get install on the build machine. The packages for ARM however, I don't want to install with apt, because it does not support installing to different directory. If I installed to default directories, the versions could not coexist. Right?
So far, the build machine was updated manually each time there was a new version of the packages, simply by extracting with dpkg -x to a dedicated "fake" footfs directory. This is where the compiler would also look when cross compiling other SW. The problem is, there is no information about these extracted packages or their versions anywhere on the system, right? It should have been in the status file.
My thought was to have these packages installed on this footfs dir with dpkg -i <package.deb> --root=<rootfs>. Would this work? I have a feeling it will not, because the deb packages have no post/pre-remove/install scripts, so it may work for a virgin install somehow, but not for upgrading? Also, what must the rootfs directory structure look like and what must it contain in order for this to work even the first time? Is there a tool to help with this?
Thanks.
Once you have a base armel Debian system, you can actually enter it and run the armel code inside it using something like QEMU. The qemu-arm-static tool (in the qemu-user-static package) can make use of the binfmt_misc capability in Linux to make it so ARM executables are directly run under the QEMU ARM system emulator. So you can run dpkg, apt-get, and so on inside the armel "rootfs" while running on amd64 hardware.
Example:
my_arm_system=/mnt/arm_system
sudo cp /usr/bin/qemu-arm-static "$my_arm_system/usr/bin/"
sudo chroot "$my_arm_system" apt-get update
sudo chroot "$my_arm_system" apt-get install $somepkg
sudo chroot "$my_arm_system" /bin/bash
As for setting up the base armel system in the first place: Debootstrap is the typical method for setting up a Debian base system, whether in a chroot or otherwise. You can use it for installing a base system of a different architecture, but it takes a few extra steps:
distro=jessie # or whatever
echo "Debootstrap phase 1"
sudo mkdir "$my_arm_system"
sudo debootstrap --arch=armel --verbose --foreign "$distro" "$my_arm_system"
sudo cp /usr/bin/qemu-arm-static "$my_arm_system"/usr/bin/
echo "Debootstrap phase 2"
sudo chroot "$my_arm_system" /debootstrap/debootstrap --second-stage
Multistrap is another tool that might be useful; it is intended for setting up Debian environments of one architecture on a host of a different architecture, or for using more complicated APT source combinations. It's not perfect, as it doesn't follow all the deb installation "rules" exactly. It takes some shortcuts/deviations in order to make its job reasonably possible.
I'd like to discover the guile ecosystem. I looked at how to install a library and I didn't find a package manager, like python's pip. Does such a thing exist for guile ?
Looks like guildhall is the closest thing to pip out there. There has been some discussion on the Guile mailing lists recently around it. The posts by Wingo, Boubekki, Zaretskii, and a few others who are heavily involved with Guile development indicate a push towards making guildhall an upstream source for something called Guix that is a more general package manager intended to be independent of platform.
If you consult the Guix list of packages you will see guile there and a number of other guile related items (e.g. guile-json, guile-ncurses, etc..). I'd give that a shot. Otherwise you're on your own and you'll have to either fall back to the OS package manager or pull down the source yourself, build, and install.
Full disclosure: I haven't tried Guix myself but I've been meaning to. I'd be very interested to see how it turns out for you so if you do go this route it'd be awesome if you could provide an update with your Guix experience.
There's also been a recent call to update the libraries page and from a quick inspection there's been some small number of updates that you may find useful.
#unclejamil This is an update of my attempt to install the guix package manager.
Documentation
First of all, the links:
the official page: https://www.gnu.org/software/guix/
the download page: http://alpha.gnu.org/gnu/guix/ (guix-the-system and guix the package manager are listed together)
Installation (Debian)
Guix needs Guile-2.0-dev and more dependencies, which are present in Debian's repositories:
apt-get install guile-2.0-dev guile-2.0 libgcrypt20-dev libbz2-dev libsqlite3-dev autopoint
Download guix. See the above links to download a binary. Or get the sources:
git clone git://git.savannah.gnu.org/guix.git
The installation goes with a classical ./configure && make && make install.
make will take several minutes and make install needs root access. If you install from source, make will build guile objects of the 346 base packages (python, zsh, abiword,…) so it'll take a long time (the database is included into guix-the-program, so we must do that. You can still tweak this list in the Makefile, at MODULES) .
Note: Your current directory must not contain non ascii characters.
Note: see also this complete tutorial, with the focus on how to install guix locally, i.e. not to run make install: http://dustycloud.org/blog/guix-package-manager-without-make-install/
Usage
To install packages with guix, we need a running server.
The first method, for testing purposes, is simply to run the server in a terminal:
sudo guix-daemon
and the client in another one:
guix package -s "guile.*curses" # search with regexps
sudo guix package -i guile-ncurses # install. All start with the "package" command.
For the proper method, see https://www.gnu.org/software/guix/manual/html_node/Build-Environment-Setup.html#Build-Environment-Setup
To be continued.
This answer is a community wiki, feel free to complete it, thanks !
I am building Guix right now and encountered the same error about not finding guile-2.0. I managed to fix it by installing the development files for guile-2.0
sudo apt-get install guile-2.0-dev
I encountered some more errors later on and it just meant I needed to install the development files for it.
I'm new to R and I decided to put R on a machine I have and see if I can remotely run code that is on my desktop computer.
While searching for "how to do" that, I came across the names "Rserve" and "RStudio". As far as I could tell, RServe is a package (actually, it seems to be the package) which I can use to configure the server, while RStudio is an IDE.
My question is: does RStudio use RServe "under the hood"? And, if it doesn't, then how does RStudio compare to RServe? (I.e., which one is better and why?)
[I figured out that this question could possibly be a duplicate, but I couldn't find any similar question]
Rserve is a client server implemenation written in pure c that starts a server and spawns multiple processes each with it's own R workspace. This is not threads but processes due to R's limitation on multithreading. It uses a QAP packing protocol as it's primary form of transport between the client and the server. You execute commands via the client (PHP, Java, C++) to the server and it returns you REXP objects that are essentially mappings to R's underlying SEXP data objects. Rserve also offers a websockets version that does will can transmit data through websockets but the api is not well documented. It also supports basic authentication through a configuration file.
Rstudio is a C++ and gwt application that provides a web based front end to R. AFAIK it uses json as it's primary transport and supports authentication through pam. Each user has a workspace configured in their home directory. It runs a server very similar but not the same as Rserve to communicate with R using RCPP. It also has it's own plotting driver used to wrap the plot device so that it can pickup the plots to be served to the ui. It has much more functionality such as stepping through your code from the ui and viewing workspace variables.
Functionally they are similar in that they provide a client/server connection to R but IMHO the comparison stops there.
I believe they are separate projects (though I could be wrong). I've never heard of RServe and there does not appear to be any mention of it in the documentation for RStudio. I have used and would recommend RStudio Server. It is relatively easy to set up and super easy to use once it is set up. This is a helpful guide to setting up a server on Amazon EC2:
#Create a user, home directory and set password
sudo useradd rstudio
sudo mkdir /home/rstudio
sudo passwd rstudio
#Enter Password
sudo chmod -R 0777 /home/rstudio
#Update all files from the default state
sudo apt-get update
sudo apt-get upgrade
#Be Able to get R 3.0
sudo add-apt-repository 'deb http://cran.rstudio.com/bin/linux/ubuntu precise/'
#Update files to use CRAN mirror
#Don't worry about error message
sudo apt-get update
#Install latest version of R
#Install without verification
sudo apt-get install r-base
#Install a few background files
sudo apt-get install gdebi-core
sudo apt-get install libapparmor1
#Change to a writeable directory
#Download & Install RStudio Server
cd /tmp
wget http://download2.rstudio.org/rstudio-server-0.97.551-amd64.deb
sudo gdebi rstudio-server-0.97.551-amd64.deb
#Once you’ve installed the above commands, you can now access RStudio through your local browser. Navigate to the Public DNS of your image on port 8787, similar to:
#http://ec2-50-19-18-120.compute-1.amazonaws.com:8787
The earlier answer about 3 years old provide old information, such as here.
Updated correction
RStudio is a firm that provides the open source RStudio IDE for R. They also sell commercial services such as RStudio Server Pro that markets itself with load balancing and related things. Apparently, the successuful open source project has lead the way to markets.
You may also mean Microsoft R Server, which is now called Microsoft Machine Learning Server?
There is also RServer by RStudio.
Anyway how to install both can be found here.
preface: i'm an os x user coming to linux, so excuse my ignorance in advance
I've installed R using synaptic and now i'm trying to install packages.
I open R then try
install.packages("some_package")
system tries to default to /site-library, then tells me it's not writable, then asks about making a personal library?
Should I just make site-library writable? Or is there something more to this?
The directory /usr/share/local/lib/R is the default location; the directory is has ownership root:staff by default. If you add yourself to group staff (easiest: by editing /etc/group and /etc/gshadow) you can write there and you do not need sudo powers for the installation of packages. That is what I do.
Alternatively, do apt-get install littler and copy the example file /usr/share/doc/littler/examples/install.r to /usr/local/bin and chmod 755 it. The you can just do sudo install.r lattice ggplot2 to take two popular examples.
BTW Ubuntu 8.1 does not exist as a version. Maybe you meant 8.10? Consider upgrading to 9.10 ...
Edit: Also have a look at this recent SO question.
I faced the same issue. The most convenient way is to start R as super user.
sudo R
After that, install.packages("some package") should work.
If you are the only user who needs those packages, then the easiest and neatest way is to let R create a personal library for you. That way you don't need to mess with the system directories managed by the package management system.
Another way to install some packages in Ubuntu is to look for Ubuntu packages with names like r-cran-*. This way you do not have to worry about dependencies, the packages become available to all users, and updates are taken care of by the Ubuntu package management system. But only a small proportion of CRAN packages are available this way and you may not get the latest version.
Well, I prefer to install packages into local R folder ~/R/, but it's just a matter of an individual preference... you can also grant yourself a write permission to default library, it doesn't make any difference.
Be sure to add up-to-date packages. Those packages available in default repos are quite old. R v.2.9.0 is available by default in 9.10, while v.2.10.1 is now available.
So stay up-to-date, add this line to file /etc/apt/sources.list (replace <text> with CRAN server address, you can find server addresses on www.r-project.org > CRAN > Linux > Ubuntu):
deb http://<my.favorite.cran.mirror>/bin/linux/ubuntu karmic/
then run this line in terminal:
gpg --keyserver subkeys.pgp.net --recv-key E2A11821 && gpg -a --export E2A11821 | sudo apt-key add -
and if keys are imported properly, run:
sudo apt-get install r-base-core
or if you already installed R, run:
sudo apt-get update && sudo apt-get upgrade
you should also check for alias functions (try man alias in terminal) to automatize repetitive tasks... feel comfortable in terminal, Synaptic is indeed a good tool, but most Linux users prefer command-line approach for a good reason - it's highly customizable =)
I recommend that you stick with one server (be advised when choosing the default server - I prefer UCLA's server, Berkeley works just fine, Main server is usually busy as hell... so there...)
Alternatively, you can add default CRAN server to .First() function:
# replace '<server address>'
.First() <- function() {
options("repos" = c(CRAN = "<my.favorite.cran.mirror>"))
}
now you can just type:
> install.packages('<somepackage>')
and you'll lose the boring Tcl/Tk serverlist window! Oh, what a relief!
Welcome to Ubuntu!
Cheers, mate!