deeplearning4j 和 Maven 的错误
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【中文标题】deeplearning4j 和 Maven 的错误【英文标题】：Errors with deeplearning4j and Maven 【发布时间】：2020-10-08 16:24:21 【问题描述】：这里是the tutorial I'm following。
pom.xml 文件是 dl4j 示例文件夹附带的默认文件，因此那里应该没有问题，但仍然有错误。
代码如下：
package org.deeplearning4j.self;
import org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator;
import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
import org.deeplearning4j.nn.conf.layers.DenseLayer;
import org.deeplearning4j.nn.conf.layers.OutputLayer;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
import org.deeplearning4j.nn.weights.WeightInit;
import org.nd4j.linalg.activations.Activation;
import org.nd4j.linalg.learning.config.Adam;
import org.nd4j.linalg.lossfunctions.LossFunctions;
import java.io.IOException;
public class first
int batchSize = 128; // how many examples to simultaneously train in the network
EmnistDataSetIterator.Set emnistSet = EmnistDataSetIterator.Set.BALANCED;
EmnistDataSetIterator emnistTrain;
try emnistTrain = new EmnistDataSetIterator(emnistSet, batchSize, true); catch (IOException e) e.printStackTrace();
EmnistDataSetIterator emnistTest;
try emnistTest = new EmnistDataSetIterator(emnistSet, batchSize, false); catch (IOException e) e.printStackTrace();
int outputNum = EmnistDataSetIterator.numLabels(emnistSet);// total output classes
int rngSeed = 123; // integer for reproducability of a random number generator
int numRows = 28; // number of "pixel rows" in an mnist digit
int numColumns = 28;
MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
.seed(rngSeed)
.updater(new Adam())
.l2(1e-4)
.list()
.layer(new DenseLayer.Builder()
.nIn(numRows * numColumns) // Number of input datapoints.
.nOut(1000) // Number of output datapoints.
.activation(Activation.RELU) // Activation function.
.weightInit(WeightInit.XAVIER) // Weight initialization.
.build())
.layer(new OutputLayer.Builder(LossFunctions.LossFunction.NEGATIVELOGLIKELIHOOD)
.nIn(1000)
.nOut(outputNum)
.activation(Activation.SOFTMAX)
.weightInit(WeightInit.XAVIER)
.build())
.build();
MultiLayerNetwork network = new MultiLayerNetwork(conf);
network.init();
// pass a training listener that reports score every 10 iterations
int eachIterations = 10;
network.addListeners(new ScoreIterationListener(eachIterations));
我正在使用 IntelliJ。
我在课堂上遇到的错误是：
无法识别在“network”上调用的两种方法，“init()”和“addListeners()”都有“无法解析符号”。它还在“网络”上说“从不使用现场网络”。
此外，int“eachIterations”在 addListeners() 方法中存在“未知类”错误。
这是 pom.xml 文件：
<?xml version="1.0" encoding="UTF-8"?> <!--~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~ Copyright (c) 2020 Konduit K.K. ~ 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>
<groupId>org.deeplearning4j</groupId>
<artifactId>dl4j-examples</artifactId>
<version>1.0.0-beta7</version>
<name>Introduction to DL4J</name>
<description>A set of examples introducing the DL4J framework</description>
<properties>
<dl4j-master.version>1.0.0-beta7</dl4j-master.version>
<!-- Change the nd4j.backend property to nd4j-cuda-X-platform to use CUDA GPUs -->
<!-- <nd4j.backend>nd4j-cuda-10.2-platform</nd4j.backend> -->
<nd4j.backend>nd4j-native</nd4j.backend>
<java.version>1.8</java.version>
<maven-compiler-plugin.version>3.6.1</maven-compiler-plugin.version>
<maven.minimum.version>3.3.1</maven.minimum.version>
<exec-maven-plugin.version>1.4.0</exec-maven-plugin.version>
<maven-shade-plugin.version>2.4.3</maven-shade-plugin.version>
<jcommon.version>1.0.23</jcommon.version>
<jfreechart.version>1.0.13</jfreechart.version>
<logback.version>1.1.7</logback.version>
</properties>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.freemarker</groupId>
<artifactId>freemarker</artifactId>
<version>2.3.29</version>
</dependency>
<dependency>
<groupId>io.netty</groupId>
<artifactId>netty-common</artifactId>
<version>4.1.48.Final</version>
</dependency>
</dependencies>
</dependencyManagement>
<dependencies>
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>$nd4j.backend</artifactId>
<version>$dl4j-master.version</version>
</dependency>
<dependency>
<groupId>org.datavec</groupId>
<artifactId>datavec-api</artifactId>
<version>$dl4j-master.version</version>
</dependency>
<dependency>
<groupId>org.datavec</groupId>
<artifactId>datavec-data-image</artifactId>
<version>$dl4j-master.version</version>
</dependency>
<dependency>
<groupId>org.datavec</groupId>
<artifactId>datavec-local</artifactId>
<version>$dl4j-master.version</version>
</dependency>
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-datasets</artifactId>
<version>$dl4j-master.version</version>
</dependency>
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-core</artifactId>
<version>$dl4j-master.version</version>
</dependency>
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-ui</artifactId>
<version>$dl4j-master.version</version>
</dependency>
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-zoo</artifactId>
<version>$dl4j-master.version</version>
</dependency>
<!-- ParallelWrapper & ParallelInference live here -->
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-parallel-wrapper</artifactId>
<version>$dl4j-master.version</version>
</dependency>
<!-- Used in the feedforward/classification/MLP* and feedforward/regression/RegressionMathFunctions example -->
<dependency>
<groupId>jfree</groupId>
<artifactId>jfreechart</artifactId>
<version>$jfreechart.version</version>
</dependency>
<dependency>
<groupId>org.jfree</groupId>
<artifactId>jcommon</artifactId>
<version>$jcommon.version</version>
</dependency>
<!-- Used for downloading data in some of the examples -->
<dependency>
<groupId>org.apache.httpcomponents</groupId>
<artifactId>httpclient</artifactId>
<version>4.3.5</version>
</dependency>
<dependency>
<groupId>ch.qos.logback</groupId>
<artifactId>logback-classic</artifactId>
<version>$logback.version</version>
</dependency>
<dependency>
<groupId>org.datavec</groupId>
<artifactId>datavec-data-codec</artifactId>
<version>$dl4j-master.version</version>
</dependency>
<dependency>
<groupId>org.bytedeco</groupId>
<artifactId>javacv-platform</artifactId>
<version>1.5.2</version>
</dependency>
</dependencies>
<!-- Maven Enforcer: Ensures user has an up to date version of Maven before building -->
<build>
<plugins>
<plugin>
<artifactId>maven-enforcer-plugin</artifactId>
<version>1.0.1</version>
<executions>
<execution>
<id>enforce-default</id>
<goals>
<goal>enforce</goal>
</goals>
<configuration>
<rules>
<requireMavenVersion>
<version>[$maven.minimum.version,)</version>
<message>********** Minimum Maven Version is $maven.minimum.version. Please upgrade Maven before continuing (run "mvn --version" to check). **********</message>
</requireMavenVersion>
</rules>
</configuration>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>$maven-compiler-plugin.version</version>
<configuration>
<source>1.7</source>
<target>1.7</target>
</configuration>
</plugin>
<plugin>
<groupId>com.lewisd</groupId>
<artifactId>lint-maven-plugin</artifactId>
<version>0.0.11</version>
<configuration>
<failOnViolation>true</failOnViolation>
<onlyRunRules>
<rule>DuplicateDep</rule>
<rule>RedundantPluginVersion</rule>
<!-- Rules incompatible with Java 9
<rule>VersionProp</rule>
<rule>DotVersionProperty</rule> -->
</onlyRunRules>
</configuration>
<executions>
<execution>
<id>pom-lint</id>
<phase>validate</phase>
<goals>
<goal>check</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.codehaus.mojo</groupId>
<artifactId>exec-maven-plugin</artifactId>
<version>$exec-maven-plugin.version</version>
<executions>
<execution>
<goals>
<goal>exec</goal>
</goals>
</execution>
</executions>
<configuration>
<executable>java</executable>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>$maven-shade-plugin.version</version>
<configuration>
<shadedArtifactAttached>true</shadedArtifactAttached>
<shadedClassifierName>$shadedClassifier</shadedClassifierName>
<createDependencyReducedPom>true</createDependencyReducedPom>
<filters>
<filter>
<artifact>*:*</artifact>
<excludes>
<exclude>org/datanucleus/**</exclude>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.RSA</exclude>
</excludes>
</filter>
</filters>
</configuration>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<transformers>
<transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
<resource>reference.conf</resource>
</transformer>
<transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/>
<transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
</transformer>
</transformers>
</configuration>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.5.1</version>
<configuration>
<source>$java.version</source>
<target>$java.version</target>
</configuration>
</plugin>
</plugins>
<pluginManagement>
<plugins>
<plugin>
<groupId>org.eclipse.m2e</groupId>
<artifactId>lifecycle-mapping</artifactId>
<version>1.0.0</version>
<configuration>
<lifecycleMappingMetadata>
<pluginExecutions>
<pluginExecution>
<pluginExecutionFilter>
<groupId>com.lewisd</groupId>
<artifactId>lint-maven-plugin</artifactId>
<versionRange>[0.0.11,)</versionRange>
<goals>
<goals><goal>check</goal></goals>
</goals>
</pluginExecutionFilter>
<action>
<ignore/>
</action>
</pluginExecution>
</pluginExecutions>
</lifecycleMappingMetadata>
</configuration>
</plugin>
</plugins>
</pluginManagement>
</build> </project>
这里的错误是“$shadedClassifier” shadedClassifier 是红色的，错误是：“Cannot resolve symbol 'shadedClassifier'”
所以我用“mvn clean install”重新安装了maven，但还是不行。
Maven 已通过全新安装正确安装，但仍然出现这些错误。
请提供任何帮助。我已经坚持了一周，我真的很想学习机器学习。
【问题讨论】：
代码是否在 IDE 中编译，或者您还会从编译器以及编辑器突出显示中得到错误？ 【参考方案1】：我猜 maven 设置不正确。我会确保 IDE 是最新的。右键单击 intellij 中的项目并点击重新加载是我会考虑做的事情。与此处相同的答案：Force Intellij IDEA to reread all maven dependencies
【讨论】：
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