TensorFlow provides a Java API— useful for loading models created with Python and running them within a Java application.
Nightly Libtensorflow Java packages
Libtensorflow JNI 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.
Supported Platforms
TensorFlow for Java is supported on the following systems:
- Ubuntu 16.04 or higher; 64-bit, x86
- macOS 10.12.6 (Sierra) or higher
- Windows 7 or higher; 64-bit, x86
To use TensorFlow on Android see TensorFlow Lite
TensorFlow with Apache Maven
To use TensorFlow with Apache Maven,
add the dependency to the project's pom.xml
file:
<dependency>
<groupId>org.tensorflow</groupId>
<artifactId>tensorflow</artifactId>
<version>2.4.0</version>
</dependency>
GPU support
If your system has GPU support, add the following TensorFlow
dependencies to the project's pom.xml
file:
<dependency>
<groupId>org.tensorflow</groupId>
<artifactId>libtensorflow</artifactId>
<version>2.4.0</version>
</dependency>
<dependency>
<groupId>org.tensorflow</groupId>
<artifactId>libtensorflow_jni_gpu</artifactId>
<version>2.4.0</version>
</dependency>
Example program
This example shows how to build an Apache Maven project with TensorFlow. First,
add the TensorFlow dependency to the project's pom.xml
file:
<project>
<modelVersion>4.0.0</modelVersion>
<groupId>org.myorg</groupId>
<artifactId>hellotensorflow</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<exec.mainClass>HelloTensorFlow</exec.mainClass>
<!-- The sample code requires at least JDK 1.7. -->
<!-- The maven compiler plugin defaults to a lower version -->
<maven.compiler.source>1.7</maven.compiler.source>
<maven.compiler.target>1.7</maven.compiler.target>
</properties>
<dependencies>
<dependency>
<groupId>org.tensorflow</groupId>
<artifactId>tensorflow</artifactId>
<version>1.14.0</version>
</dependency>
</dependencies>
</project>
Create the source file (src/main/java/HelloTensorFlow.java
):
import org.tensorflow.Graph;
import org.tensorflow.Session;
import org.tensorflow.Tensor;
import org.tensorflow.TensorFlow;
public class HelloTensorFlow {
public static void main(String[] args) throws Exception {
try (Graph g = new Graph()) {
final String value = "Hello from " + TensorFlow.version();
// Construct the computation graph with a single operation, a constant
// named "MyConst" with a value "value".
try (Tensor t = Tensor.create(value.getBytes("UTF-8"))) {
// The Java API doesn't yet include convenience functions for adding operations.
g.opBuilder("Const", "MyConst").setAttr("dtype", t.dataType()).setAttr("value", t).build();
}
// Execute the "MyConst" operation in a Session.
try (Session s = new Session(g);
// Generally, there may be multiple output tensors,
// all of them must be closed to prevent resource leaks.
Tensor output = s.runner().fetch("MyConst").run().get(0)) {
System.out.println(new String(output.bytesValue(), "UTF-8"));
}
}
}
}
Compile and execute:
mvn -q compile exec:java # Use -q to hide logging
The command outputs: Hello from version
TensorFlow with the JDK
TensorFlow can be used with the JDK through the Java Native Interface (JNI).
Download
- Download the TensorFlow Jar Archive (JAR): libtensorflow.jar
- Download and extract the Java Native Interface (JNI) file for your operating system and processor support:
Compile
Using the HelloTensorFlow.java
file from the previous example,
compile a program that uses TensorFlow. Make sure the libtensorflow.jar
is
accessible to your classpath
:
javac -cp libtensorflow-2.4.0.jar HelloTensorFlow.java
Run
To execute a TensorFlow Java program, the JVM must access libtensorflow.jar
and
the extracted JNI library.
Linux / macOS
java -cp libtensorflow-2.4.0.jar:. -Djava.library.path=./jni HelloTensorFlow
Windows
java -cp libtensorflow-2.4.0.jar;. -Djava.library.path=jni HelloTensorFlow
The command outputs: Hello from version
Build from source
TensorFlow is open source. Read the instructions to build TensorFlow's Java and native libraries from source code.