I am currently building a console package with Dart, and Rust using FFI(foreign function interface). Since I can't/shouldn't publish dll/so/dylib files, how can I add a build functionality to it. With that functionality, the required files should be built after the package is downloaded, so that the interop-ed code can work properly. How can it be done? Will the user that downloaded the package need to have Rust in his machine to build the files?
You need to either distribute binaries or require the user to have a Rust compiler.
I'm interested in incorporating TensorFlow into a C++ server application built in Visual Studio on Windows 10 and I need to know if that's possible.
Google recently announced Windows support for TensorFlow: https://developers.googleblog.com/2016/11/tensorflow-0-12-adds-support-for-windows.html
but from what I can tell this is just a pip install for the more commonly used Python package, and to use the C++ API you need to build the repo from source yourself: How to build and use Google TensorFlow C++ api
I tried building the project myself using bazel, but ran into issues trying to configure the build.
Is there a way to get TensorFlow C++ to work in native Windows (not using Docker or the new Windows 10 Linux subsystem, as I've seen others post about)?
Thanks,
Ian
It is certainly possible to use TensorFlow's C++ API on Windows, but it is not currently very easy. Right now, the easiest way to build against the C++ API on Windows would be to build with CMake, and adapt the CMake rules for the tf_tutorials_example_trainer project (see the source code here). Building with CMake will give you a Visual Studio project in which you can implement your C++ TensorFlow program.
Note that the tf_tutorials_example_trainer project builds a Console Application that statically links all of the TensorFlow runtime into your program. At present we have not written the necessary rules to create a reusable TensorFlow DLL, although this would be technially possible: for example, the Python extension is a DLL that includes the runtime, but does not export the necessary symbols to use TensorFlow's C or C++ APIs directly.
There is a detailed guide by Joe Antognini and a similar TensorFlow ReadMe at GitHub explaining the building of TensorFlow source via CMake. You also need to have SWIG installed on your machine which allows connecting C/C++ source with the Python scripting language. I did use Visual CMAKE (cmake-gui) with the screen capture shown below.
In the CMake configuration, I used Visual Studio 15 2017 compiler. Once this stage successfully completes, you can click on the Generate button to go ahead with the actual build process.
However, on Visual Studio 2015, when I attempted building via the "ALL_BUILD" project, the setup gave me "build tools for v141 cannot be found" error. This did not go away even when I attempted to retarget my solution. Finally, the solution got built successfully with Visual Studio 2017. You also need to manually set the SWIG_EXECUTABLE path in CMake before it successfully configures.
As indicated in the Antognini link, for me the build took about half an hour on a 16GB RAM, Core i7 machine. Once done, you might want to validate your build by attempting to run the tf_tutorials_example_trainer.exe file.
Hope this helps!
For our latest work on building TensorFlow C++ API on Windows, please look at this github page. This works on Windows 10, currently without CUDA support (only CPU).
PS:
Only the bazel build method works, because CMake is not supported and not maintained anymore, resulting in CMake configuration errors.
I had to use a downgraded version of my Visual Studio 2017 (from 15.7.5 to 15.4) by adding "VC++ 2017 version 15.4 v14.11 toolset" through the installer (Individual Components tab).
The cmake command which worked for me was:
cmake .. -A x64 -DCMAKE_BUILD_TYPE=Release ^
-T "v141,version=14.11" ^
-DSWIG_EXECUTABLE="C:/Program Files/swigwin-3.0.12/swig.exe" ^
-DPYTHON_EXECUTABLE="C:/Program Files/Python/python.exe" ^
-DPYTHON_LIBRARIES="C:/Program Files/Python/libs/python27.lib" ^
-Dtensorflow_ENABLE_GPU=ON ^
-DCUDNN_HOME="C:/Program Files/cudnn-9.2-windows10-x64-v7.1/cuda" ^
-DCUDA_TOOLKIT_ROOT_DIR="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v9.0"
After the build, open tensorflow.sln in Visual Studio and build ALL_BUILD.
If you want to enable GPU computation, do check your Graphics Card here (Compute Capability > 3.5). Do remember to install all the packages (Cuda Toolkit 9.0, cuDNN, Python 3.7, SWIG, Git, CMake...) and add the paths to the environment variable in the beginning.
I made a README detailing how to I built the Tensorflow dll and .lib file for the C++ API on Windows with GPU support building from source with Bazel. Tensorflow version 1.14
The tutorial is step by step and starts at the very beginning, so you may have to scroll down past steps you have already done, like checking your hardware, installing Bazel etc.
Here is the url: https://github.com/sitting-duck/stuff/tree/master/ai/tensorflow/build_tensorflow_1.14_source_for_Windows
Probably you will want to scroll all the way down to this part:
https://github.com/sitting-duck/stuff/tree/master/ai/tensorflow/build_tensorflow_1.14_source_for_Windows#step-7-build-the-dll
It shows how to pass command to create .lib and .dll.
Then to test your .lib you should link it into your c++ project,
Then it will show you how to identify and fix the missing symbols using the TF_EXPORT macro
I am actively working on making this tutorial better so feel free to leave comments on this answer if you are having problems.
I have written c++ Code that requires Opencv libraries to compile in Ubuntu 12.04. When I try to run the binary generated on a different system, it asks for the library. Does this happens, or there is error in code. If no error how can I run the code than.
You should build it on the new system , if it asks for the library, you are not linking correctly.
I am an experienced (but retired) Windows software developer, with more years experience than I care to admit, developing in C++, C#, VB and Java. I therefore decided to have a crack at Android development. My development machine is a Windows 7 box. My IDE of choice would be Microsoft Visual Studio but, for now, I am happy doing hand editing and launching tools from the command line.
I started by downloading the Android SDK and various additional items it suggested. I then started working my way through the tutorial at developer.android.com/training/basics/firstapp. Android list targets gave me a couple of choices (Android 4.2.2 and Google APIs:17). I then did Android create project from the command line and that appeared to do its stuff, creating MyFirstApp in my development folder. I then ran Android avd and created an emulator. I also added the android SDK's tools and platform-tools to my path. So far so good.
I fell at the next hurdle. The tutorial told me to change to the root folder of my project and run ant debug. At this point, Windows reports:
'ant' is not recognized as an internal or external command,
operable program or batch file.
I've searched around for ant.exe without success. Did I miss installing something or did I miss a vital step in the set-up? Any advice for this very green newbie would be greatly appreciated.
There is no ant.exe. Only ant.bat. Ant is a Java build tool.
If it comes with the Android SDK, make sure its bin directory is in your PATH environment variable. Otherwise, download it (from [http://ant.apache.org][1]), and follow the installation instructions on the web site.
Normally, simply unzipping it, putting its bin directory in the PATH envieonment variable, and setting a JAVA_HOME environment variable that points to your preferred JDK directory is sufficient.
I am currently learning F# and preparing to write my first program. I will be using Visual Studio 10 in Windows 7 to write the code, because the F# support for MonoDevelop is a few versions behind.
My normal day-to-day development environment is Mac Os X 10.7. I have Mono and MonoDevelop installed. After I finish writing my masterpiece, how do I package it for running on Os X? What DLLs do I need to send to other Windows users so that they can run my .exe file? How do they install those DLLs?
In the Java world (where I usually live), I just package my Java code with any dependencies into a monolithic UberJAR that I can send to anyone who has the appropriate version of Java (usually 6) and they can run my code by typing
java -jar MyUberJar.jar
I routinely write code in Scala and include the Scala library, along with any other dependencies.
Is there any easy way to do something similar for .NET, and specifically for F#?
One alternative is to use the --standalone flag to fsc which will statically compile all the DLL's you need into a single large EXE. The people you send it to will still need to install Mono, but there are no other dependencies.
I think this is what most people use:
http://wix.sourceforge.net/
I say "I think" because at work we've got a release team that builds the installer package for us.