Difference between revisions of "Tensorflow JNI development"
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| − | ==About== | + | ==<font color='blue'>Why</font>== |
| + | 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. | ||
| + | |||
| + | ==<font color='blue'>About</font>== | ||
| + | |||
| + | 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 [https://medium.com/@maxime.durand.54/build-tennsorflow-2-0-for-java-on-windows-2ab51b9cac45 Build TensorFlow 2.0 for Java on Windows] article. | Based on [https://medium.com/@maxime.durand.54/build-tennsorflow-2-0-for-java-on-windows-2ab51b9cac45 Build TensorFlow 2.0 for Java on Windows] article. | ||
| Line 12: | Line 18: | ||
* '''Create Elipse project''' | * '''Create Elipse project''' | ||
| − | There's [https://github.com/bytedeco/javacpp-presets JavaCPP Presets] project. Seems useless. | + | There's [https://github.com/bytedeco/javacpp-presets JavaCPP Presets] project. <s>Seems useless</s>. Seems useful. |
| − | ==Install== | + | ==<font color='blue'>Install</font>== |
In Kubuntu: | In Kubuntu: | ||
* Get [https://github.com/tensorflow/tensorflow/archive/v1.15.0.tar.gz TensorFlow-1.15.0] | * Get [https://github.com/tensorflow/tensorflow/archive/v1.15.0.tar.gz TensorFlow-1.15.0] | ||
* Install [https://github.com/bazelbuild/bazel/releases/download/0.25.2/bazel_0.25.2-linux-x86_64.deb bazel 0.25.2] | * Install [https://github.com/bazelbuild/bazel/releases/download/0.25.2/bazel_0.25.2-linux-x86_64.deb bazel 0.25.2] | ||
| − | ==Build== | + | Based on [[Feeding_Tensorflow_from_GPU|Feeding Tensorflow from GPU]]. |
| − | cd ~/git/tensorflow-1.15.0 | + | |
| + | ==<font color='blue'>Build</font>== | ||
| + | ===Note=== | ||
| + | * <font color='red'>While running bazel ate all RAM (have 16GB) a few times and PC "hanged". To limit bazel's appetites try:</font> | ||
| + | <font size=2>~$ bazel build --jobs 4 --local_ram_resources=4096 ... | ||
| + | ~$ bazel test --jobs 4 --local_ram_resources=4096 ... | ||
| + | # I think that '''local_ram_resources''' is MBs per thread (have 8): | ||
| + | ~$ bazel build --local_ram_resources=2048 ... | ||
| + | ~$ bazel test --local_ram_resources=2048 ...</font> | ||
| + | |||
| + | ===Quick=== | ||
| + | ~/git/tensorflow-1.15.0/mvn_build.sh: | ||
| + | <font size=2># Step 1 (Java): | ||
| + | |||
| + | bazel build -c opt //tensorflow/java:tensorflow //tensorflow/java:libtensorflow_jni //tensorflow/java:pom | ||
| + | mvn install:install-file -Dfile=bazel-bin/tensorflow/java/libtensorflow.jar -DpomFile=bazel-bin/tensorflow/java/pom.xml | ||
| + | |||
| + | # Step 2 (JNI): | ||
| + | |||
| + | bazel build -c opt //tensorflow/tools/lib_package:libtensorflow_jni.tar.gz | ||
| + | |||
| + | rm -rf bazel-bin/tensorflow/tools/lib_package/maven | ||
| + | mkdir -p bazel-bin/tensorflow/tools/lib_package/maven/org/tensorflow/native/linux-x86_64 | ||
| + | |||
| + | POM=" | ||
| + | <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> | ||
| + | " | ||
| + | |||
| + | echo $POM > bazel-bin/tensorflow/tools/lib_package/maven/pom.xml | ||
| + | |||
| + | tar -zxvf bazel-bin/tensorflow/tools/lib_package/libtensorflow_jni.tar.gz -C bazel-bin/tensorflow/tools/lib_package/maven/org/tensorflow/native/linux-x86_64 | ||
| + | cd bazel-bin/tensorflow/tools/lib_package/maven | ||
| + | mvn package | ||
| + | mvn install | ||
| + | cd ../../../../.. | ||
| + | |||
| + | ===Detailed=== | ||
| + | |||
| + | <font size=2>cd ~/git/tensorflow-1.15.0 | ||
./configure # do not forget CUDA | ./configure # do not forget CUDA | ||
| − | bazel build -c opt //tensorflow/java:tensorflow //tensorflow/java:libtensorflow_jni //tensorflow/java:pom | + | bazel build -c opt //tensorflow/java:tensorflow //tensorflow/java:libtensorflow_jni //tensorflow/java:pom</font> |
| + | |||
| + | 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 | ||
| + | <font size=2>At launch bazel starts its server which, to prevent it, add to ~/.bazelrc: | ||
| + | startup --max_idle_secs=0</font> | ||
| + | |||
| + | Artifacts of interest are in '''bazel-bin/tensorflow/java/''': | ||
| + | <font size=2>'''libtensorflow_jni.so''' | ||
| + | '''libtensorflow.jar''' | ||
| + | '''pom.xml'''</font> | ||
| + | |||
| + | * '''xml''' and '''jar''' will be taken care of by '''mvn''' command. | ||
| + | * '''so''' will have to be in the library path (alternatively see [[Tensorflow_JNI_development#Build_so_package|'''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=== | |
| − | + | <font size=2># /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/</font> | ||
| − | + | === preferred [option 2] Build so package=== | |
| − | + | <font size=2>bazel build -c opt //tensorflow/tools/lib_package:libtensorflow_jni.tar.gz</font> | |
| − | + | It puts all libs into a single archive. | |
| − | pom.xml | + | Now to create a JAR to replace [https://mvnrepository.com/artifact/org.tensorflow/libtensorflow_jni_gpu libtensorflow_jni_gpu], do this: |
| + | <font size=2>mkdir -p bazel-bin/tensorflow/tools/lib_package/maven/org/tensorflow/native/linux-x86_64 | ||
| + | tar -zxvf bazel-bin/tensorflow/tools/lib_package/libtensorflow_jni.tar.gz -C bazel-bin/tensorflow/tools/lib_package/maven/org/tensorflow/native/linux-x86_64</font> | ||
| + | Next create a pom.xml in ''bazel-bin/tensorflow/tools/lib_package/maven'': | ||
| + | <font size=2><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></font> | ||
| + | Note: '''libtensorflow_jni_gpu''' - name can be any - just make sure you use it in your project's pom.xml. | ||
| + | Next: | ||
| + | <font size=2>cd bazel-bin/tensorflow/tools/lib_package/maven | ||
| + | mvn package | ||
| + | mvn install | ||
| + | cd ../../../../.. | ||
| + | </font> | ||
| − | + | ==<font color='blue'>Install JAR to local Maven Repository</font>== | |
| − | + | <font size=2>~/GIT/tensorflow-1.15.0$ <b>mvn install:install-file -Dfile=bazel-bin/tensorflow/java/libtensorflow.jar -DpomFile=bazel-bin/tensorflow/java/pom.xml</b></font> | |
| − | + | How to uninstall maven local repo - and switch back to official versions from Maven Central - [https://stackoverflow.com/questions/15358851/how-to-remove-jar-file-from-local-maven-repository-which-was-added-with-install this link]. Or remove unneeded stuff from '''~/.m2/repository/org/tensorflow''' | |
| − | |||
| − | + | <font color=green size='4'>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</font> | |
| − | |||
| − | ==Modify TF JNI== | + | ==<font color='blue'>Modify TF JNI functions</font>== |
For example, one wants to create a new function in org.tensorflow.TensorFlow package. | For example, one wants to create a new function in org.tensorflow.TensorFlow package. | ||
| − | Then | + | Then see inside: |
| − | '''tensorflow/java/src/main/java/org/tensorflow/''' | + | <font size=2>'''tensorflow/java/src/main/java/org/tensorflow/''' |
| − | '''tensorflow/java/src/main/native/''' | + | '''tensorflow/java/src/main/native/'''</font> |
| − | + | Three places: | |
* add native method to tensorflow/java/src/main/java/org/tensorflow/TensorFlow.java | * 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 header file tensorflow/java/src/main/native/tensorflow_jni.h | ||
* add to c file tensorflow/java/src/main/native/tensorflow_jni.cc | * add to c file tensorflow/java/src/main/native/tensorflow_jni.cc | ||
| − | + | Rebuild and Reinstall. | |
| − | ==Java | + | 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.: | ||
| + | <font size=2>Java_org_tensorflow_TensorFlow_<Name></font> | ||
| + | |||
| + | ==<font color='blue'>Java Maven project in Eclipse</font>== | ||
| + | Nothing special. | ||
* Create a new maven project | * Create a new maven project | ||
* Edit pom.xml: | * Edit pom.xml: | ||
| − | <project> | + | <font size=2><project> |
... | ... | ||
<dependencies> | <dependencies> | ||
| Line 68: | Line 174: | ||
</dependencies> | </dependencies> | ||
... | ... | ||
| − | </project> | + | </project></font> |
| + | * Write code as usual | ||
===Basic example code=== | ===Basic example code=== | ||
tfhello.java: | tfhello.java: | ||
| − | import org.tensorflow.TensorFlow; | + | <font size=2>import org.tensorflow.TensorFlow; |
public class tfhello{ | public class tfhello{ | ||
| Line 78: | Line 185: | ||
System.out.println(TensorFlow.version()); | System.out.println(TensorFlow.version()); | ||
} | } | ||
| − | } | + | }</font> |
| + | |||
| + | ==<font color='blue'>A few words on TF in Maven Central repository</font>== | ||
| + | |||
| + | ===libtensorflow=== | ||
| + | Record in pom.xml: | ||
| + | <font size=2><dependency> | ||
| + | <groupId>org.tensorflow</groupId> | ||
| + | <artifactId>libtensorflow</artifactId> | ||
| + | <version>1.15.0</version> | ||
| + | </dependency></font> | ||
| + | |||
| + | Archive contains Java classes. | ||
| + | |||
| + | ===libtensorflow_jni_gpu=== | ||
| + | Record in pom.xml: | ||
| + | <font size=2><dependency> | ||
| + | <groupId>org.tensorflow</groupId> | ||
| + | <artifactId>libtensorflow_jni_gpu</artifactId> | ||
| + | <version>1.15.0</version> | ||
| + | </dependency></font> | ||
| + | |||
| + | Archive contains native library: | ||
| + | <font size=2>├── 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</font> | ||
Latest revision as of 09:48, 1 April 2020
Contents
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. Seems useful.
Install
In Kubuntu:
- Get TensorFlow-1.15.0
- Install bazel 0.25.2
Based on Feeding Tensorflow from GPU.
Build
Note
- While running bazel ate all RAM (have 16GB) a few times and PC "hanged". To limit bazel's appetites try:
~$ bazel build --jobs 4 --local_ram_resources=4096 ... ~$ bazel test --jobs 4 --local_ram_resources=4096 ... # I think that local_ram_resources is MBs per thread (have 8): ~$ bazel build --local_ram_resources=2048 ... ~$ bazel test --local_ram_resources=2048 ...
Quick
~/git/tensorflow-1.15.0/mvn_build.sh:
# Step 1 (Java):
bazel build -c opt //tensorflow/java:tensorflow //tensorflow/java:libtensorflow_jni //tensorflow/java:pom
mvn install:install-file -Dfile=bazel-bin/tensorflow/java/libtensorflow.jar -DpomFile=bazel-bin/tensorflow/java/pom.xml
# Step 2 (JNI):
bazel build -c opt //tensorflow/tools/lib_package:libtensorflow_jni.tar.gz
rm -rf bazel-bin/tensorflow/tools/lib_package/maven
mkdir -p bazel-bin/tensorflow/tools/lib_package/maven/org/tensorflow/native/linux-x86_64
POM="
<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>
"
echo $POM > bazel-bin/tensorflow/tools/lib_package/maven/pom.xml
tar -zxvf bazel-bin/tensorflow/tools/lib_package/libtensorflow_jni.tar.gz -C bazel-bin/tensorflow/tools/lib_package/maven/org/tensorflow/native/linux-x86_64
cd bazel-bin/tensorflow/tools/lib_package/maven
mvn package
mvn install
cd ../../../../..
Detailed
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/
preferred [option 2] Build so package
bazel build -c opt //tensorflow/tools/lib_package:libtensorflow_jni.tar.gz
It puts all libs into a single archive. Now to create a JAR to replace libtensorflow_jni_gpu, do this:
mkdir -p bazel-bin/tensorflow/tools/lib_package/maven/org/tensorflow/native/linux-x86_64 tar -zxvf bazel-bin/tensorflow/tools/lib_package/libtensorflow_jni.tar.gz -C bazel-bin/tensorflow/tools/lib_package/maven/org/tensorflow/native/linux-x86_64
Next create a pom.xml in 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:
cd bazel-bin/tensorflow/tools/lib_package/maven mvn package mvn install cd ../../../../..
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