I'm currently trying to install tensorflow from source. And when I typed bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package -cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0 into the terminal, it simply gave me an angular bracket indicator >. What am I supposed to do next?
Here was the ./configure step output.
Please specify the location of python. [Default is /home/jingw222/anaconda3/bin/python]:
Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]:
Do you wish to use jemalloc as the malloc implementation? [Y/n]
jemalloc enabled
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N]
No Google Cloud Platform support will be enabled for TensorFlow
Do you wish to build TensorFlow with Hadoop File System support? [y/N]
No Hadoop File System support will be enabled for TensorFlow
Do you wish to build TensorFlow with the XLA just-in-time compiler (experimental)? [y/N]
No XLA support will be enabled for TensorFlow
Found possible Python library paths:
/home/jingw222/anaconda3/lib/python3.6/site-packages
Please input the desired Python library path to use. Default is [/home/jingw222/anaconda3/lib/python3.6/site-packages]
Using python library path: /home/jingw222/anaconda3/lib/python3.6/site-packages
Do you wish to build TensorFlow with OpenCL support? [y/N]
No OpenCL support will be enabled for TensorFlow
Do you wish to build TensorFlow with CUDA support? [y/N]
No CUDA support will be enabled for TensorFlow
Configuration finished
...........
INFO: Starting clean (this may take a while). Consider using --expunge_async if the clean takes more than several minutes.
..........
INFO: All external dependencies fetched successfully.
Can it be that you're missing a closing "?
bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package -cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0"
Related
I am going to deploy a Qt Application on github and I want to link with some KF5 modules
I call the cmake command
find_package(KF5Crash)
and on linux the things are quite simple the user can
apt-get install libkf5crash-dev
I can mention on documentation the instruction on how to install kcrash or other kf5 modules, the problem is on windows, how can I instruct the windows developers/contributors to install any of the kf5 module?
KDE developers use the Craft utility to deploy source and binaries of KF5 (and many other dependencies) to Windows.
See https://community.kde.org/Craft
I am currently trying to build a project with source in a git repository and some dependencies in an artifactory. I need to first download all the sources and binaries from the repo and artifactory to my local workspace.
I could not find any information regarding artifactory integration with bazel. I can see that this feature has been requested https://www.jfrog.com/jira/browse/RTFACT-15428?jql=labels%20%3D%20bazel.
Is anyone aware of any build tools that can first download resources and then build them?
I need both git and artifactory support.
According to the Bazel documentation for Java, you can define external dependencies resolved to Maven with rule maven_jar.
As Artifactory supports Maven, you can set up your dependencies in a Maven repository, and retrieve artifacts from there with your Bazel build script.
On the other side of the build, publication seems to be a work-in-progress and on the roadmap for Bazel builds.
You can also attempt to write the artifactory rules in Skylark: https://docs.bazel.build/versions/master/skylark/repository_rules.html
Remote build cache
Bazel supports any HTTP 1.1 server with PUT and GET methods as http cache. Simple HTTP Auth is also supported. This means using Artifactory as a remote build cache is straightforward.
Create a new Generic repository in Artifactory.
Now run bazel as
bazel test \
--remote_http_cache=https://user:password#[...].com:8081/artifactory/bazel/ \
test //...
See https://docs.bazel.build/versions/master/remote-caching.html for the relevant Bazel doc.
If I need to use a nightly TensorFlow build in a Cloud ML Engine training job, how do I do it?
Download a nightly build from https://github.com/tensorflow/tensorflow#installation.
How to pick the right build:
use "Linux CPU-only" or "Linux GPU" depending on whether you need to use GPUs for training,
use the Python 2 build.
Rename the .whl file, for example
mv tensorflow-1.0.1-cp27-cp27mu-linux_x86_64.whl \
tensorflow-1.0.1-cp27-none-linux_x86_64.whl
(here we renamed the cpu27mu to none. Pip parses that part to detect whether a .whl package is suitable for a platform, but that particular name doesn't work on some older versions of pip)
Upload the .whl file to GCS and specify it as one of the package_uris
when submitting a Cloud ML Engine training job.
Note that instead of using a nightly build you can also build TensorFlow from source as described in https://www.tensorflow.org/install/install_sources.
I want to build an application that will be compatible with, say, Debian Lenny (libc, postgres, oracle and other libs) on a different Debian/Ubuntu release.
Is this possible? If so, where can I read how to do it?
You can use the open build service for this. Create the Debian package description files for it (you can add also rpm spec files), select the target distributions and you will get it built on each platform and also get a specific download repository for each platform. Your package will be rebuilt automatically when needed as well. You can install your own instance of the service if you need to host proprietary code.
If you want a multiplatform binary, you may want to build it against a LSB chroot:
http://ftp.linux-foundation.org/pub/lsb/impl
And bundle any library that is not part of it. The LSB has tools to then check your app for compliance. Their website is down right now, but it should be here: http://ldn.linuxfoundation.org/lsb/check-your-app
I have downloaded and installed the pion network library.
I am trying to build the sample web services (HelloService etc). However, I cannot find instructions on how to build the examples.
I am developing on windows7
Check This for build instructions on Windows.
You might also want to see here the compatibility of your windows.