Configuring the source tree

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The next step is to configure the Apache source tree for your particular platform and personal requirements. This is done using the script configure included in the root directory of the distribution. (Developers downloading an unreleased version of the Apache source tree will need to have autoconf and libtool installed and will need to run buildconf before proceeding with the next steps. This is not necessary for official releases.)

MacPorts is an easy to use system for compiling, installing, and managing open source software. MacPorts may be conceptually divided into two main parts: the infrastructure, known as MacPorts base, and the set of available ports. Step 1: Remove game-specific files created by the launcher. For each game that uses the launcher, you will need to delete the following files or folders, if they exist, from the game’s data directory (e.g., Documents/Paradox Interactive/Age of Wonders Planetfall).launcher-cache; contentload.json or dlcload.json (depending on game) game. Missing compiler run-time libraries. If your system does not have the same compiler that built the MEX file, see the Microsoft ® MSDN ® website for information about Visual C ® Redistributable Packages. Missing or incorrectly installed specialized run-time libraries. Contact your MEX file or library vendor.

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To configure the source tree using all the default options, simply type ./configure. To change the default options, configure accepts a variety of variables and command line options.

The most important option is the location --prefix where Apache is to be installed later, because Apache has to be configured for this location to work correctly. More fine-tuned control of the location of files is possible with additional configure options.

Also at this point, you can specify which features you want included in Apache by enabling and disabling modules. Apache comes with a wide range of modules included by default. They will be compiled as shared objects (DSOs) which can be loaded or unloaded at runtime. You can also choose to compile modules statically by using the option --enable-module=static.

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Additional modules are enabled using the --enable-module option, where module is the name of the module with the mod_ string removed and with any underscore converted to a dash. Similarly, you can disable modules with the --disable-module option. Be careful when using these options, since configure cannot warn you if the module you specify does not exist; it will simply ignore the option.

In addition, it is sometimes necessary to provide the configure script with extra information about the location of your compiler, libraries, or header files. This is done by passing either environment variables or command line options to configure. For more information, see the configure manual page. Or invoke configure using the --help option.

For a short impression of what possibilities you have, here is a typical example which compiles Apache for the installation tree /sw/pkg/apache with a particular compiler and flags plus the two additional modules mod_ldap and mod_lua:

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$ CC='pgcc' CFLAGS='-O2'
./configure --prefix=/sw/pkg/apache
--enable-ldap=shared
--enable-lua=shared

When configure is run it will take several minutes to test for the availability of features on your system and build Makefiles which will later be used to compile the server.

Details on all the different configure options are available on the configure manual page.

TensorFlow has APIs available in several languages both for constructing andexecuting a TensorFlow graph. The Python API is at present the most completeand the easiest to use, but other language APIs may be easier to integrateinto projects and may offer some performance advantages in graph execution.

A word of caution: the APIs in languages other than Python are not yetcovered by the API stability promises.

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We encourage the community to develop and maintain support for other languageswith theapproach recommended by the TensorFlow maintainers.For example, see the bindings for:

• C#: TensorFlowSharp and TensorFlow.NET,
• Haskell,
• Julia,
• MATLAB,
• R,
• Ruby,
• Rust, and
• Scala.

We also provide the C++ API reference for TensorFlow Serving:

There are also some archived or unsupported language bindings: