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pom.xml
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<?xml version="1.0" encoding="UTF-8"?>
<!--~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~ Copyright (c) 2015-2019 Skymind, Inc.
~
~ This program and the accompanying materials are made available under the
~ terms of the Apache License, Version 2.0 which is available at
~ https://www.apache.org/licenses/LICENSE-2.0.
~
~ Unless required by applicable law or agreed to in writing, software
~ distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
~ WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
~ License for the specific language governing permissions and limitations
~ under the License.
~
~ SPDX-License-Identifier: Apache-2.0
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~-->
<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/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<!-- Group-ID, artifact ID and version of the project. You can modify these as you want -->
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-examples</artifactId>
<version>1.0.0-beta5</version>
<!-- Properties Section. Change DL4J and ND4J versions here, if required -->
<properties>
<dl4j.version>1.0.0-beta4</dl4j.version>
<nd4j.version>1.0.0-beta4</nd4j.version>
<spark.version>2.4.4</spark.version>
<logback.version>1.2.3</logback.version>
<java.version>1.8</java.version>
<maven-shade-plugin.version>2.4.3</maven-shade-plugin.version>
</properties>
<dependencies>
<!-- deeplearning4j-core: contains main functionality and neural networks -->
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-core</artifactId>
<version>${dl4j.version}</version>
</dependency>
<!--
ND4J backend: every project needs one of these. The backend defines the hardware on which network training
will occur. "nd4j-native-platform" is for CPUs only (for running on all operating systems).
-->
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>nd4j-native</artifactId>
<version>${nd4j.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>${spark.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>dl4j-spark_2.11</artifactId>
<version>1.0.0-beta4_spark_2</version>
</dependency>
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>dl4j-spark-parameterserver_2.11</artifactId>
<version>1.0.0-beta4_spark_2</version>
</dependency>
<dependency>
<groupId>com.beust</groupId>
<artifactId>jcommander</artifactId>
<version>1.78</version>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>1.18.10</version>
</dependency>
<!-- CUDA: to use GPU for training (CUDA) instead of CPU, uncomment this, and remove nd4j-native-platform -->
<!-- Requires CUDA to be installed to use. Change the version (8.0, 9.0, 9.1) to change the CUDA version -->
<!--
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>nd4j-cuda-9.2-platform</artifactId>
<version>${nd4j.version}</version>
</dependency>
-->
<!-- Optional, but recommended: if you use CUDA, also use CuDNN. To use this, CuDNN must also be installed -->
<!-- See: https://deeplearning4j.org/cudnn -->
<!--
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-cuda-9.2</artifactId>
<version>${dl4j.version}</version>
</dependency>
-->
<dependency>
<groupId>ch.qos.logback</groupId>
<artifactId>logback-classic</artifactId>
<version>${logback.version}</version>
</dependency>
</dependencies>
<build>
<plugins>
<!-- Maven compiler plugin: compile for Java 8 -->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.5.1</version>
<configuration>
<source>${java.version}</source>
<target>${java.version}</target>
</configuration>
</plugin>
<!--
Maven shade plugin configuration: this is required so that if you build a single JAR file (an "uber-jar")
it will contain all the required native libraries, and the backends will work correctly.
Used for example when running the following commants
mvn package
cd target
java -cp deeplearning4j-examples-1.0.0-beta-bin.jar org.deeplearning4j.LenetMnistExample
-->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>${maven-shade-plugin.version}</version>
<configuration>
<shadedArtifactAttached>true</shadedArtifactAttached>
<shadedClassifierName>bin</shadedClassifierName>
<createDependencyReducedPom>true</createDependencyReducedPom>
<filters>
<filter>
<artifact>*:*</artifact>
<excludes>
<exclude>org/datanucleus/**</exclude>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.RSA</exclude>
</excludes>
</filter>
</filters>
</configuration>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<transformers>
<transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
<resource>reference.conf</resource>
</transformer>
<transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/>
<transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
</transformer>
</transformers>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>