TensorFlow for Java

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.

Quickstart

• Refer to Installing TensorFlow for Java
• Javadoc
• 

Nightly builds

Releases built from release branches are available on Maven Central.
Additionally, every day binaries are built from the master branch on GitHub:

• JAR
• Source JAR
• JNI:
  • Linux CPU-only
  • Linux GPU
  • MacOS
  • Windows: (No nightly builds available yet)

Building from source

If the quickstart instructions above do not work out, the TensorFlow Java and
native libraries will need to be built from source.

1. Install bazel

2. 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:

   ```sh

   On Linux

   sudo apt-get install python swig python-numpy

   On Mac OS X with homebrew

   brew install swig
   ```

3. 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:

• An archive of Java classes: libtensorflow.jar
• A native library: 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.

Maven

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>

Bazel

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