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README.md |
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 TensorFlow Lite.
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.
-
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:
- An archive of Java classes:
libtensorflow.jar
- A native library:
libtensorflow_jni.so
on Linux,libtensorflow_jni.dylib
on OS X, ortensorflow_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