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 7: | Line 13: | ||
How to: | How to: | ||
− | * '''Build TF JNI - libtensorflow.jar, libtensorflow_jni.so | + | * '''Build TF JNI''' - libtensorflow.jar, libtensorflow_jni.so and pom.xml |
* '''Add TF JAR to local Maven''' which will override the [https://mvnrepository.com/artifact/org.tensorflow/tensorflow Central Maven Repository] | * '''Add TF JAR to local Maven''' which will override the [https://mvnrepository.com/artifact/org.tensorflow/tensorflow Central Maven Repository] | ||
* '''Modify TF JNI functions''' | * '''Modify TF JNI functions''' | ||
* '''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. |
+ | |||
+ | ==<font color='blue'>Install</font>== | ||
+ | In Kubuntu: | ||
+ | * 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] | ||
+ | |||
+ | Based on [[Feeding_Tensorflow_from_GPU|Feeding Tensorflow from GPU]]. | ||
+ | |||
+ | ==<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=== |
− | cd ~/git/tensorflow-1.15.0 | + | |
+ | <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