Add the presets for Tritonserver

.github/workflows/tritonserver.yml

@@ -0,0 +1,22 @@
+name: tritonserver
+on:
+  push:
+    paths:
+      - tritonserver/**
+  pull_request:
+    paths:
+      - tritonserver/**
+  workflow_dispatch:
+env:
+  CI_DEPLOY_MODULE: ${{ github.workflow }}
+  CI_DEPLOY_PLATFORM: ${{ github.job }}
+  CI_DEPLOY_SETTINGS: ${{ secrets.CI_DEPLOY_SETTINGS }}
+  CI_DEPLOY_USERNAME: ${{ secrets.CI_DEPLOY_USERNAME }}
+  CI_DEPLOY_PASSWORD: ${{ secrets.CI_DEPLOY_PASSWORD }}
+  STAGING_REPOSITORY: ${{ secrets.STAGING_REPOSITORY }}
+jobs:
+  linux-x86_64:
+    runs-on: ubuntu-18.04
+    container: nvcr.io/nvidia/tritonserver:21.09-py3
+    steps:
+      - uses: bytedeco/javacpp-presets/.github/actions/deploy-ubuntu@actions

CHANGELOG.md

@@ -1,4 +1,5 @@
 
+ * Add presets for Triton Inference Server 2.14 ([pull #1085](https://github.com/bytedeco/javacpp-presets/pull/1085))
  * Add presets for the NvToolsExt (NVTX) module of CUDA ([issue #1068](https://github.com/bytedeco/javacpp-presets/issues/1068))
  * Increase the amount of function pointers available for callbacks in presets for Qt ([pull #1080](https://github.com/bytedeco/javacpp-presets/pull/1080))
  * Map C++ JIT classes and functions of TorchScript in presets for PyTorch ([issue #1068](https://github.com/bytedeco/javacpp-presets/issues/1068))

README.md

@@ -46,6 +46,7 @@ JavaCPP Presets
 [![tensorflow](https://github.com/bytedeco/javacpp-presets/workflows/tensorflow/badge.svg)](https://github.com/bytedeco/javacpp-presets/actions?query=workflow%3Atensorflow)
 [![tensorflow-lite](https://github.com/bytedeco/javacpp-presets/workflows/tensorflow-lite/badge.svg)](https://github.com/bytedeco/javacpp-presets/actions?query=workflow%3Atensorflow-lite)
 [![tensorrt](https://github.com/bytedeco/javacpp-presets/workflows/tensorrt/badge.svg)](https://github.com/bytedeco/javacpp-presets/actions?query=workflow%3Atensorrt)
+[![tritonserver](https://github.com/bytedeco/javacpp-presets/workflows/tritonserver/badge.svg)](https://github.com/bytedeco/javacpp-presets/actions?query=workflow%3Atritonserver)
 [![ale](https://github.com/bytedeco/javacpp-presets/workflows/ale/badge.svg)](https://github.com/bytedeco/javacpp-presets/actions?query=workflow%3Aale)
 [![depthai](https://github.com/bytedeco/javacpp-presets/workflows/depthai/badge.svg)](https://github.com/bytedeco/javacpp-presets/actions?query=workflow%3Adepthai)
 [![onnx](https://github.com/bytedeco/javacpp-presets/workflows/onnx/badge.svg)](https://github.com/bytedeco/javacpp-presets/actions?query=workflow%3Aonnx)
@@ -214,6 +215,7 @@ Each child module in turn relies by default on the included [`cppbuild.sh` scrip
  * TensorFlow 1.15.x  https://github.com/tensorflow/tensorflow
  * TensorFlow Lite 2.6.x  https://github.com/tensorflow/tensorflow
  * TensorRT 8.x  https://developer.nvidia.com/tensorrt
+ * Triton Inference Server 2.14  https://developer.nvidia.com/nvidia-triton-inference-server
  * The Arcade Learning Environment 0.7.x  https://github.com/mgbellemare/Arcade-Learning-Environment
  * DepthAI 2.11.x  https://github.com/luxonis/depthai-core
  * ONNX 1.10.x  https://github.com/onnx/onnx

cppbuild.sh

@@ -164,7 +164,7 @@ function sedinplace {
 }
 
 if [[ -z ${PROJECTS:-} ]]; then
-    PROJECTS=(opencv ffmpeg flycapture spinnaker libdc1394 libfreenect libfreenect2 librealsense librealsense2 videoinput artoolkitplus chilitags flandmark arrow hdf5 hyperscan mkl mkl-dnn dnnl openblas arpack-ng cminpack fftw gsl cpython numpy scipy gym llvm libpostal leptonica tesseract caffe openpose cuda nvcodec opencl mxnet pytorch tensorflow tensorflow-lite tensorrt depthai ale onnx ngraph onnxruntime tvm liquidfun qt skia cpu_features modsecurity systems)
+    PROJECTS=(opencv ffmpeg flycapture spinnaker libdc1394 libfreenect libfreenect2 librealsense librealsense2 videoinput artoolkitplus chilitags flandmark arrow hdf5 hyperscan mkl mkl-dnn dnnl openblas arpack-ng cminpack fftw gsl cpython numpy scipy gym llvm libpostal leptonica tesseract caffe openpose cuda nvcodec opencl mxnet pytorch tensorflow tensorflow-lite tensorrt tritonserver depthai ale onnx ngraph onnxruntime tvm liquidfun qt skia cpu_features modsecurity systems)
 fi
 
 for PROJECT in ${PROJECTS[@]}; do

platform/pom.xml

@@ -58,6 +58,7 @@
     <module>../tensorflow/platform</module>
     <module>../tensorflow-lite/platform</module>
     <module>../tensorrt/platform</module>
+    <module>../tritonserver/platform</module>
     <module>../ale/platform</module>
     <module>../depthai/platform</module>
     <module>../onnx/platform</module>
@@ -294,6 +295,11 @@
       <artifactId>tensorrt-platform</artifactId>
       <version>8.0-${project.version}</version>
     </dependency>
+    <dependency>
+      <groupId>org.bytedeco</groupId>
+      <artifactId>tritonserver-platform</artifactId>
+      <version>2.14-${project.version}</version>
+    </dependency>
     <dependency>
       <groupId>org.bytedeco</groupId>
       <artifactId>ale-platform</artifactId>

pom.xml

@@ -618,6 +618,7 @@
         <module>tensorflow</module>
         <module>tensorflow-lite</module>
         <module>tensorrt</module>
+        <module>tritonserver</module>
         <module>ale</module>
         <module>depthai</module>
         <module>onnx</module>
@@ -1368,6 +1369,7 @@
         <module>tensorflow</module>
         <module>tensorflow-lite</module>
         <module>tensorrt</module>
+        <module>tritonserver</module>
         <module>ale</module>
         <module>depthai</module>
         <module>onnx</module>

tritonserver/README.md

@@ -0,0 +1,77 @@
+JavaCPP Presets for Triton Inference Server
+===========================================
+
+[![Gitter](https://badges.gitter.im/bytedeco/javacpp.svg)](https://gitter.im/bytedeco/javacpp) [![Maven Central](https://maven-badges.herokuapp.com/maven-central/org.bytedeco/tritonserver/badge.svg)](https://maven-badges.herokuapp.com/maven-central/org.bytedeco/tritonserver) [![Sonatype Nexus (Snapshots)](https://img.shields.io/nexus/s/https/oss.sonatype.org/org.bytedeco/tritonserver.svg)](http://bytedeco.org/builds/)  
+<sup>Build status for all platforms:</sup> [![tritonserver](https://github.com/bytedeco/javacpp-presets/workflows/tritonserver/badge.svg)](https://github.com/bytedeco/javacpp-presets/actions?query=workflow%3Atritonserver)  <sup>Commercial support:</sup> [![xscode](https://img.shields.io/badge/Available%20on-xs%3Acode-blue?style=?style=plastic&logo=appveyor&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAEAAAABACAMAAACdt4HsAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAAAZQTFRF////////VXz1bAAAAAJ0Uk5T/wDltzBKAAAAlUlEQVR42uzXSwqAMAwE0Mn9L+3Ggtgkk35QwcnSJo9S+yGwM9DCooCbgn4YrJ4CIPUcQF7/XSBbx2TEz4sAZ2q1RAECBAiYBlCtvwN+KiYAlG7UDGj59MViT9hOwEqAhYCtAsUZvL6I6W8c2wcbd+LIWSCHSTeSAAECngN4xxIDSK9f4B9t377Wd7H5Nt7/Xz8eAgwAvesLRjYYPuUAAAAASUVORK5CYII=)](https://xscode.com/bytedeco/javacpp-presets)
+
+
+License Agreements
+------------------
+By downloading these archives, you agree to the terms of the license agreements for NVIDIA software included in the archives.
+
+### Triton Inference Server
+To view the license for Triton Inference Server included in these archives, click [here](https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license)
+
+ * Triton Inference Server is widely used software package for inference service
+ * Triton supports almost all kinds of model generated by different DL frameworks or tools, such as TensorFlow, PyTorch, ONNX Runtime, TensorRT, OpenVINO...
+ * Triton supports both CPU and GPU
+ * Triton can be used both as an application and as a shared library. In case you already have your own inference service framework but want to add more features, just try Triton as a shared library.
+ * Triton supports Java as a shared library through JavaCPP Presets
+
+
+Introduction
+------------
+This directory contains the JavaCPP Presets module for:
+
+ * Triton Inference Server 2.14  https://github.com/triton-inference-server/server
+
+Please refer to the parent README.md file for more detailed information about the JavaCPP Presets.
+
+
+Documentation
+-------------
+Java API documentation is available here:
+
+ * http://bytedeco.org/javacpp-presets/tritonserver/apidocs/
+
+
+Sample Usage
+------------
+Here is a simple example of Triton Inference Server ported to Java from the `simple.cc` sample file available at:
+
+ * https://github.com/triton-inference-server/server/tree/main/src/servers
+
+We can use [Maven 3](http://maven.apache.org/) to download and install automatically all the class files as well as the native binaries. To run this sample code, after creating the `pom.xml` and `Simple.java` source files from the [`samples/`](samples/) subdirectory, simply execute on the command line:
+```bash
+ $ mvn compile exec:java -Dexec.args="-r /path/to/models"
+```
+This sample intends to show how to call the Java-mapped C API of Triton to execute inference requests.
+
+### Steps to run this sample inside an NGC container
+
+ 1. Get the source code of Triton Inference Server to prepare the model repository:
+```bash
+ $ wget https://github.com/triton-inference-server/server/archive/refs/tags/v2.14.0.tar.gz
+ $ tar zxvf v2.14.0.tar.gz
+ $ cd server-2.14.0/docs/examples/model_repository
+ $ mkdir models
+ $ cd models; cp -a ../simple .
+```
+Now, this `models` directory will be our model repository.
+
+ 2. Start the Docker container to run the sample (assuming we are under the `models` directory created above):
+```bash
+ $ docker run -it --gpus=all -v $(pwd):/workspace nvcr.io/nvidia/tritonserver:21.09-py3 bash
+ $ apt update
+ $ apt install -y openjdk-11-jdk
+ $ wget https://dlcdn.apache.org/maven/maven-3/3.8.3/binaries/apache-maven-3.8.3-bin.tar.gz
+ $ tar zxvf apache-maven-3.8.3-bin.tar.gz
+ $ export PATH=/opt/tritonserver/apache-maven-3.8.2/bin:$PATH
+ $ git clone https://github.com/bytedeco/javacpp-presets.git
+ $ cd javacpp-presets/tritonserver/samples
+ $ mvn compile exec:java -Djavacpp.platform=linux-x86_64 -Dexec.args="-r /workspace/models"
+```
+
+This sample is the Java implementation of the simple example written for the [C API](https://github.com/triton-inference-server/server/blob/main/docs/inference_protocols.md#c-api).
+
+

tritonserver/cppbuild.sh

@@ -0,0 +1,30 @@
+#!/bin/bash
+# This file is meant to be included by the parent cppbuild.sh script
+if [[ -z "$PLATFORM" ]]; then
+    pushd ..
+    bash cppbuild.sh "$@" tritonserver
+    popd
+    exit
+fi
+
+case $PLATFORM in
+    linux-arm64)
+        if [[ ! -f "/opt/tritonserver/include/triton/core/tritonserver.h" ]] && [[ ! -d "/opt/tritonserver/lib/" ]]; then
+            echo "Please make sure library and include files exist"
+            exit 1
+        fi
+        ;;
+    linux-x86_64)
+        if [[ ! -f "/opt/tritonserver/include/triton/core/tritonserver.h" ]] && [[ ! -d "/opt/tritonserver/lib/" ]]; then
+            echo "Please make sure library and include files exist"
+            exit 1
+        fi
+        ;;
+    windows-x86_64)
+        echo "Windows is not supported yet"
+        exit 1
+        ;;
+    *)
+        echo "Error: Platform \"$PLATFORM\" is not supported"
+        ;;
+esac

tritonserver/platform/pom.xml

@@ -0,0 +1,127 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+    xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+
+  <parent>
+    <groupId>org.bytedeco</groupId>
+    <artifactId>javacpp-presets</artifactId>
+    <version>1.5.7-SNAPSHOT</version>
+    <relativePath>../../</relativePath>
+  </parent>
+
+  <groupId>org.bytedeco</groupId>
+  <artifactId>tritonserver-platform</artifactId>
+  <version>2.14-${project.parent.version}</version>
+  <name>JavaCPP Presets Platform for Tritonserver</name>
+
+  <properties>
+    <javacpp.moduleId>tritonserver</javacpp.moduleId>
+  </properties>
+
+  <dependencies>
+    <dependency>
+      <groupId>org.bytedeco</groupId>
+      <artifactId>cuda-platform</artifactId>
+      <version>11.4-8.2-${project.parent.version}</version>
+    </dependency>
+    <dependency>
+      <groupId>org.bytedeco</groupId>
+      <artifactId>tensorrt-platform</artifactId>
+      <version>8.0-${project.parent.version}</version>
+    </dependency>
+    <dependency>
+      <groupId>${project.groupId}</groupId>
+      <artifactId>${javacpp.moduleId}</artifactId>
+      <version>${project.version}</version>
+    </dependency>
+    <dependency>
+      <groupId>${project.groupId}</groupId>
+      <artifactId>${javacpp.moduleId}</artifactId>
+      <version>${project.version}</version>
+      <classifier>${javacpp.platform.linux-arm64}</classifier>
+    </dependency>
+    <dependency>
+      <groupId>${project.groupId}</groupId>
+      <artifactId>${javacpp.moduleId}</artifactId>
+      <version>${project.version}</version>
+      <classifier>${javacpp.platform.linux-x86_64}</classifier>
+    </dependency>
+    <dependency>
+      <groupId>${project.groupId}</groupId>
+      <artifactId>${javacpp.moduleId}</artifactId>
+      <version>${project.version}</version>
+      <classifier>${javacpp.platform.windows-x86_64}</classifier>
+    </dependency>
+  </dependencies>
+
+  <build>
+    <plugins>
+      <plugin>
+        <artifactId>maven-jar-plugin</artifactId>
+        <executions>
+          <execution>
+            <id>default-jar</id>
+            <configuration>
+              <archive>
+                <manifestEntries>
+                  <Class-Path>${javacpp.moduleId}.jar ${javacpp.moduleId}-linux-arm64.jar ${javacpp.moduleId}-linux-x86_64.jar ${javacpp.moduleId}-windows-x86_64.jar</Class-Path>
+                </manifestEntries>
+              </archive>
+            </configuration>
+          </execution>
+          <execution>
+            <id>empty-javadoc-jar</id>
+            <goals>
+              <goal>jar</goal>
+            </goals>
+            <configuration>
+              <classifier>javadoc</classifier>
+            </configuration>
+          </execution>
+          <execution>
+            <id>empty-sources-jar</id>
+            <goals>
+              <goal>jar</goal>
+            </goals>
+            <configuration>
+              <classifier>sources</classifier>
+            </configuration>
+          </execution>
+        </executions>
+      </plugin>
+      <plugin>
+        <groupId>org.moditect</groupId>
+        <artifactId>moditect-maven-plugin</artifactId>
+        <executions>
+          <execution>
+            <id>add-module-infos</id>
+            <phase>none</phase>
+          </execution>
+          <execution>
+            <id>add-platform-module-info</id>
+            <phase>package</phase>
+            <goals>
+              <goal>add-module-info</goal>
+            </goals>
+            <configuration>
+              <modules>
+                <module>
+                  <file>${project.build.directory}/${project.artifactId}.jar</file>
+                  <moduleInfoSource>
+                    module org.bytedeco.${javacpp.moduleId}.platform {
+                      requires static org.bytedeco.${javacpp.moduleId}.linux.arm64;
+                      requires static org.bytedeco.${javacpp.moduleId}.linux.x86_64;
+                      requires static org.bytedeco.${javacpp.moduleId}.windows.x86_64;
+                    }
+                  </moduleInfoSource>
+                </module>
+              </modules>
+            </configuration>
+          </execution>
+        </executions>
+      </plugin>
+    </plugins>
+  </build>
+
+</project>