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TensorFlow provides a C API that can be used to build
bindings for other languages.
The API is defined in
c_api.h
and designed for simplicity and uniformity rather than convenience.
Nightly libtensorflow C packages
libtensorflow packages are built nightly and uploaded to GCS for all supported
platforms. They are uploaded to the
libtensorflow-nightly GCS bucket
and are indexed by operating system and date built. For MacOS and Linux shared
objects, there is a
script
that renames the .so files versioned to the current date copied into the
directory with the artifacts.
Supported Platforms
TensorFlow for C is supported on the following systems:
- Linux, 64-bit, x86
- macOS, Version 10.12.6 (Sierra) or higher
- Windows, 64-bit x86
Setup
Download and extract
| TensorFlow C library | URL |
|---|---|
| Linux | |
| Linux CPU only | https://storage.googleapis.com/tensorflow/versions/2.18.0/libtensorflow-cpu-linux-x86_64.tar.gz |
| Linux GPU support | https://storage.googleapis.com/tensorflow/versions/2.18.0/libtensorflow-gpu-linux-x86_64.tar.gz |
| macOS | |
| macOS CPU only | https://storage.googleapis.com/tensorflow/versions/2.16.2/libtensorflow-cpu-darwin-x86_64.tar.gz |
| macOS ARM64 CPU only | https://storage.googleapis.com/tensorflow/versions/2.18.0/libtensorflow-cpu-darwin-arm64.tar.gz |
| Windows | |
| Windows CPU only | https://storage.googleapis.com/tensorflow/versions/2.18.1/libtensorflow-cpu-windows-x86_64.zip |
| Windows GPU only | https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-2.10.0.zip |
Extract the downloaded archive, which contains the header files to include in your C program and the shared libraries to link against.
On Linux and macOS, you may want to extract to /usr/local/lib:
FILENAME=libtensorflow-cpu-linux-x86_64.tar.gzwget -q --no-check-certificate https://storage.googleapis.com/tensorflow/versions/2.18.1/${FILENAME}sudo tar -C /usr/local -xzf ${FILENAME}
Linker
On Linux/macOS, if you extract the TensorFlow C library to a system directory,
such as /usr/local, configure the linker with ldconfig:
sudo ldconfig /usr/local/libIf you extract the TensorFlow C library to a non-system directory, such as
~/mydir, then configure the linker environmental variables:
Linux
export LIBRARY_PATH=$LIBRARY_PATH:~/mydir/lib export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/mydir/lib
macOS
export LIBRARY_PATH=$LIBRARY_PATH:~/mydir/lib export DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:~/mydir/lib
Build
Example program
With the TensorFlow C library installed, create an example program with the
following source code (hello_tf.c):
%%writefile hello_tf.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;
}
Writing hello_tf.c
Compile
Compile the example program to create an executable, then run:
gcc hello_tf.c -ltensorflow -o hello_tf./hello_tf
Hello from TensorFlow C library version 2.18.1
If the program doesn't build, make sure that gcc can access the TensorFlow C
library. If extracted to /usr/local, explicitly pass the library location to
the compiler:
gcc -I/usr/local/include -L/usr/local/lib hello_tf.c -ltensorflow -o hello_tf./hello_tf
Hello from TensorFlow C library version 2.18.1
Build from source
TensorFlow is open source. Read the instructions to build TensorFlow's C library from source code.
View on TensorFlow.org
Run in Google Colab
View source on GitHub
Download notebook