Latest commit 8c69e00 Feb 24, 2017 @asimshankar asimshankar committed with tensorflower-gardener Docs: Typos and link fixes.
- Point C++ API links to the "Guide" page instead of the page that lists out
  every API function/type
- Point Java API links to the Javadoc instead of github code
- Fix a typo
Change: 148430624

TensorFlow for Java

Java bindings for TensorFlow. (Javadoc)

WARNING: The TensorFlow Java API is not currently covered by the TensorFlow API stability guarantees.

For using TensorFlow on Android refer to contrib/android, makefile and/or the Android demo.


  1. Download the Java archive (JAR): libtensorflow.jar (optionally, the Java sources: libtensorflow-src.jar).

  2. Download the native library. GPU-enabled versions required CUDA 8 and cuDNN 5.1. For other versions, the native library will need to be built from source (see below).

    The following shell snippet downloads and extracts the native library:

    TF_TYPE="cpu" # Set to "gpu" to enable GPU support
    OS=$(uname -s | tr '[:upper:]' '[:lower:]')
    mkdir -p ./jni
    curl -L \
      "${TF_TYPE}-${OS}-x86_64-1.0.0-PREVIEW1.tar.gz" |
    tar -xz -C ./jni
  3. Include the downloaded .jar in the classpath during compilation. For example, if your program looks like the following:

    import org.tensorflow.TensorFlow;
    public class MyClass {
      public static void main(String[] args) {
        System.out.println("I'm using TensorFlow version: " +  TensorFlow.version());

    then it should be compiled with:

    javac -cp libtensorflow-1.0.0-PREVIEW1.jar

    For a more sophisticated example, see, which can be compiled with:

    javac \
      -cp libtensorflow-1.0.0-PREVIEW1.jar \
  4. Include the downloaded .jar in the classpath and the native library in the library path during execution. For example:

    java -cp libtensorflow-1.0.0-PREVIEW1.jar:. -Djava.library.path=./jni MyClass

    or for the LabelImage example:

    java \
      -Djava.library.path=./jni \
      -cp libtensorflow-1.0.0-PREVIEW1.jar:./src/main/java \

That's all. These artifacts are not yet available on Maven central, see #6926.

Building from source

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

  1. Install bazel

  2. Setup the environment to buile TensorFlow from source code (Linux or Mac OS X). 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
  3. Configure (e.g., enable GPU support) and build:

    bazel build --config opt \
      //tensorflow/java:tensorflow \

The JAR (libtensorflow.jar) and native library ( will be in bazel-genfiles/tensorflow/tensorflow/java.


To use the library in an external Java project, publish the library to a Maven repository. For example, publish the library to the local Maven repository using the mvn tool (installed separately):

bazel build -c opt //tensorflow/java:pom
mvn install:install-file \
  -Dfile=../../bazel-bin/tensorflow/java/libtensorflow.jar \

Refer to the library using Maven coordinates. For example, if you're using Maven then place this dependency into your pom.xml file (replacing 1.0.head with the version of the TensorFlow runtime you wish to use).



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