Tensorflow JNI development

Why

Why modify TF JNI?

• Add TF features that are still missing in TF for Java like feeding directly from GPU memory thus saving time on back and forth CPU-GPU transfers if you, say, run data through a custom CUDA kernel first.

About

Notes on how to build TF JNI, where to modify JNI if needed, install to local maven and setup a project that will use modified native functions.

Based on Build TensorFlow 2.0 for Java on Windows article. Also this one - tensorflow/java/README.md.

These instructions are for Linux and old TensorFlow 1.15.0.

How to:

• Build TF JNI - libtensorflow.jar, libtensorflow_jni.so and pom.xml
• Add TF JAR to local Maven which will override the Central Maven Repository
• Modify TF JNI functions
• Create Elipse project

There's JavaCPP Presets project. Seems useless.

Install

In Kubuntu:

• Get TensorFlow-1.15.0
• Install bazel 0.25.2

Based on Feeding Tensorflow from GPU.

Build

cd ~/git/tensorflow-1.15.0
./configure # do not forget CUDA
bazel build -c opt //tensorflow/java:tensorflow //tensorflow/java:libtensorflow_jni //tensorflow/java:pom

With TF, bazel tends to rebuild everything from scratch - takes a ton of time. Is it because it gets restarted after idle timeout or something else? A somewhat solution might be

At launch bazel starts its server which, to prevent it, add to ~/.bazelrc:
startup --max_idle_secs=0

Artifacts of interest are in bazel-bin/tensorflow/java/:

libtensorflow_jni.so
libtensorflow.jar
pom.xml

• xml and jar will be taken care of by mvn command.
• so will have to be in the library path (alternatively see Build so package a little below and skip this linking). Link or copy to /usr/lib/ or go with "java -Djava.library.path=...".

[option 1] Link so library

# /usr/lib is in the default java.library.path
sudo ln -sf ~/GIT/tensorflow-1.15.0/bazel-bin/tensorflow/java/libtensorflow_jni.so /usr/lib/

[option 2] <preferred> Build so package

bazel build -c opt //tensorflow/tools/lib_package:libtensorflow_jni.tar.gz

Now to create a JAR to replace libtensorflow_jni_gpu, do this:

mkdir -p bazel-bin/tensorflow/tools/lib_package/maven
tar -zxvf bazel-bin/tensorflow/tools/lib_package/libtensorflow_jni.tar.gz -C bazel-bin/tensorflow/tools/lib_package/maven

Next create a pom.xml there (bazel-bin/tensorflow/tools/lib_package/maven):

<project>
  <modelVersion>4.0.0</modelVersion>
  <description>Platform-dependent native code for the TensorFlow Java library. CUDA support depends on the local build.</description>
  <groupId>org.tensorflow</groupId>
  <artifactId>libtensorflow_jni_gpu</artifactId>
  <version>1.15.0</version>
  <packaging>jar</packaging>
  <build>
    <resources>
      <resource>
        <directory>.</directory>
          <excludes>
            <exclude>target/**</exclude>
          </excludes>
      </resource>
    </resources>
  </build>
</project>

Note: libtensorflow_jni_gpu - name can be any - just make sure you use it in your project's pom.xml. Next:

mvn package
mvn install

I'm yet to test this but the libtensorflow_jni_gpu-1.15.0.jar at least has all the files needed.

Install JAR to local Maven Repository

~/GIT/tensorflow-1.15.0$ mvn install:install-file -Dfile=bazel-bin/tensorflow/java/libtensorflow.jar -DpomFile=bazel-bin/tensorflow/java/pom.xml

How to uninstall maven local repo - and switch back to official versions from Maven Central - this link. Or remove unneeded stuff from ~/.m2/repository/org/tensorflow

After *_jni.so is linked (or jar'd) and jar installed one can resume normal development. See below what to add to your project's pom.xml

Modify TF JNI functions

For example, one wants to create a new function in org.tensorflow.TensorFlow package. Then see inside:

tensorflow/java/src/main/java/org/tensorflow/
tensorflow/java/src/main/native/

Three places:

• add native method to tensorflow/java/src/main/java/org/tensorflow/TensorFlow.java
• add to header file tensorflow/java/src/main/native/tensorflow_jni.h
• add to c file tensorflow/java/src/main/native/tensorflow_jni.cc

Rebuild and Reinstall.

The native header files seem to be regenerated but I haven't tested if they are actually used (need to test). In function naming - avoid underscores, e.g.:

Java_org_tensorflow_TensorFlow_<Name>

Java Maven project in Eclipse

Nothing special.

• Create a new maven project
• Edit pom.xml:

<project>
  ...
  <dependencies>
    ...
    <dependency>
      <groupId>org.tensorflow</groupId>
      <artifactId>libtensorflow</artifactId>
      <version>1.15.0</version>
    </dependency>
    ...
  </dependencies>
  ...
</project>

• Write code as usual

Basic example code

tfhello.java:

import org.tensorflow.TensorFlow;

public class tfhello{
	public static void main(String[] args){
		System.out.println(TensorFlow.version());
	}
}

A few words on TF in Maven Central repository

libtensorflow

Record in pom.xml:

<dependency>
  <groupId>org.tensorflow</groupId>
  <artifactId>libtensorflow</artifactId>
  <version>1.15.0</version>
</dependency>

Archive contains Java classes.

libtensorflow_jni_gpu

Record in pom.xml:

<dependency>
  <groupId>org.tensorflow</groupId>
  <artifactId>libtensorflow_jni_gpu</artifactId>
  <version>1.15.0</version>
</dependency>

Archive contains native library:

├── META-INF
│   ├── MANIFEST.MF
│   └── maven
│       └── org.tensorflow
│           └── libtensorflow_jni_gpu
│               ├── pom.properties
│               └── pom.xml
└── org
    └── tensorflow
        └── native
            ├── linux-x86_64
            │   ├── libtensorflow_framework.so.1
            │   ├── libtensorflow_jni.so
            │   ├── LICENSE
            │   └── THIRD_PARTY_TF_JNI_LICENSES
            └── windows-x86_64
                ├── LICENSE
                └── tensorflow_jni.dll