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# Installing TensorFlow for C
TensorFlow provides a C API defined in
[`c_api.h`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/c/c_api.h),
which is suitable for
[building bindings for other languages](https://www.tensorflow.org/extend/language_bindings).
The API leans towards simplicity and uniformity rather than convenience.
## Supported Platforms
You may install TensorFlow for C on the following operating systems:
* Linux
* Mac OS X
## Installation
Take the following steps to install the TensorFlow for C library and
enable TensorFlow for C:
1. Decide whether you will run TensorFlow for C on CPU(s) only or
with the help of GPU(s). To help you decide, read the section
entitled "Determine which TensorFlow to install" in one of the
following guides:
* @{$install_linux#determine_which_tensorflow_to_install$Installing TensorFlow on Linux}
* @{$install_mac#determine_which_tensorflow_to_install$Installing TensorFlow on Mac OS}
2. Download and extract the TensorFlow C library into `/usr/local/lib` by
invoking the following shell commands:
TF_TYPE="cpu" # Change to "gpu" for GPU support
OS="linux" # Change to "darwin" for Mac OS
TARGET_DIRECTORY="/usr/local"
curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.2.1.tar.gz" |
sudo tar -C $TARGET_DIRECTORY -xz
The `tar` command extracts the TensorFlow C library into the `lib`
subdirectory of `TARGET_DIRECTORY`. For example, specifying `/usr/local`
as `TARGET_DIRECTORY` causes `tar` to extract the TensorFlow C library
into `/usr/local/lib`.
If you'd prefer to extract the library into a different directory,
adjust `TARGET_DIRECTORY` accordingly.
3. In Step 2, if you specified a system directory (for example, `/usr/local`)
as the `TARGET_DIRECTORY`, then run `ldconfig` to configure the linker.
For example:
<pre><b>sudo ldconfig</b></pre>
If you assigned a `TARGET_DIRECTORY` other than a system
directory (for example, `~/mydir`), then you must append the extraction
directory (for example, `~/mydir/lib`) to two environment variables.
For example:
<pre> <b>export LIBRARY_PATH=$LIBRARY_PATH:~/mydir/lib</b> # For both Linux and Mac OS X
<b>export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/mydir/lib</b> # For Linux only
<b>export DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:~/mydir/lib</b> # For Mac OS X only</pre>
## Validate your installation
After installing TensorFlow for C, enter the following code into a file named
`hello_tf.c`:
```c
#include <stdio.h>
#include <tensorflow/c/c_api.h>
int main() {
printf("Hello from TensorFlow C library version %s\n", TF_Version());
return 0;
}
```
### Build and Run
Build `hello_tf.c` by invoking the following command:
<pre><b>gcc hello_tf.c</b></pre>
Running the resulting executable should output the following message:
<pre><b>a.out</b>
Hello from TensorFlow C library version <i>number</i></pre>
### Troubleshooting
If building the program fails, the most likely culprit is that `gcc` cannot
find the TensorFlow C library. One way to fix this problem is to specify
the `-I` and `-L` options to `gcc`. For example, if the `TARGET_LIBRARY`
was `/usr/local`, you would invoke `gcc` as follows:
<pre><b>gcc -I/usr/local/include -L/usr/local/lib hello_tf.c -ltensorflow</b></pre>
If executing `a.out` fails, ask yourself the following questions:
* Did the program build without error?
* Have you assigned the correct directory to the environment variables
noted in Step 3 of [Installation](#installation)?
* Did you export those environment variables?
If you are still seeing build or execution error messages, search (or post to)
[StackOverflow](www.stackoverflow.com/questions/tagged/tensorflow) for
possible solutions.
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