Difference between revisions of "Tensorflow JNI development"

Revision as of 09:26, 5 March 2020

Why

Why modify TF JNI?

• Add TF features that are still missing in TF for Java like feeding directly from GPU memory.

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. Link or copy to /usr/lib/ or go with "java -Djava.library.path=...". Example:

# /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/

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

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>1.14.0</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