WARNING: The TensorFlow Java API is not currently covered by the TensorFlow API stability guarantees.
For using TensorFlow on Android refer instead to contrib/android, makefile and/or the Android demo.
Releases built from release branches are available on Maven Central. Additionally, every day binaries are built from the master
branch on GitHub:
If the quickstart instructions above do not work out, the TensorFlow Java and native libraries will need to be built from source.
Install bazel
Setup the environment to build TensorFlow from source code (Linux or macOS). If you'd like to skip reading those details and do not care about GPU support, try the following:
# On Linux sudo apt-get install python swig python-numpy # On Mac OS X with homebrew brew install swig
Configure (e.g., enable GPU support) and build:
./configure bazel build --config opt \ //tensorflow/java:tensorflow \ //tensorflow/java:libtensorflow_jni
The command above will produce two files in the bazel-bin/tensorflow/java
directory:
libtensorflow.jar
libtensorflow_jni.so
on Linux, libtensorflow_jni.dylib
on OS X, or tensorflow_jni.dll
on Windows.To compile Java code that uses the TensorFlow Java API, include libtensorflow.jar
in the classpath. For example:
javac -cp bazel-bin/tensorflow/java/libtensorflow.jar ...
To execute the compiled program, include libtensorflow.jar
in the classpath and the native library in the library path. For example:
java -cp bazel-bin/tensorflow/java/libtensorflow.jar \ -Djava.library.path=bazel-bin/tensorflow/java \ ...
Installation on Windows requires the more experimental bazel on Windows. Details are omitted here, but find inspiration in the script used for building the release archive: tensorflow/tools/ci_build/windows/libtensorflow_cpu.sh
.
Details of the release process for Maven Central are in maven/README.md
. However, for development, you can push the library built from source to a local Maven repository with:
bazel build -c opt //tensorflow/java:pom mvn install:install-file \ -Dfile=../../bazel-bin/tensorflow/java/libtensorflow.jar \ -DpomFile=../../bazel-bin/tensorflow/java/pom.xml
And then refer to this library in a project's pom.xml
with: (replacing VERSION with the appropriate version of TensorFlow):
<dependency> <groupId>org.tensorflow</groupId> <artifactId>libtensorflow</artifactId> <version>VERSION</version> </dependency>
If your project uses bazel for builds, add a dependency on //tensorflow/java:tensorflow
to the java_binary
or java_library
rule. For example:
bazel run -c opt //tensorflow/java/src/main/java/org/tensorflow/examples:label_image