Java &引用；无法解析符号“；在所有的多层网络上'；s方法
下面是我将要学习的教程的一部分 我使用的是IntelliJ，Maven安装正确，最初我使用的是JDK13.0.2，但切换到JDK1.8.0ą来尝试修复此错误。以下是迄今为止的代码：Java &引用；无法解析符号“；在所有的多层网络上'；s方法,java,machine-learning,intellij-idea,neural-network,deeplearning4j,Java,Machine Learning,Intellij Idea,Neural Network,Deeplearning4j,下面是我将要学习的教程的一部分 我使用的是IntelliJ，Maven安装正确，最初我使用的是JDK13.0.2，但切换到JDK1.8.0ą来尝试修复此错误。以下是迄今为止的代码： package org.deeplearning4j.examples; import org.deeplearning4j.datasets.iterator.BaseDatasetIterator; import org.deeplearning4j.datasets.iterator.impl.EmnistD
package org.deeplearning4j.examples;
import org.deeplearning4j.datasets.iterator.BaseDatasetIterator;
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 learnNum {
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));
int numEpochs = 2;
network.fit(emnistTrain, numEpochs);
}
<?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>
<goal>check</goal>
</goals>
</pluginExecutionFilter>
<action>
<ignore/>
</action>
</pluginExecution>
</pluginExecutions>
</lifecycleMappingMetadata>
</configuration>
</plugin>
</plugins>
</pluginManagement>
</build>
</project>
4.0.0
org.deeplearning4j
dl4j示例
1.0.0-beta7
DL4J简介
介绍DL4J框架的一组示例
1.0.0-beta7
nd4j本机
1.8
3.6.1
3.3.1
1.4.0
2.4.3
1.0.23
1.0.13
1.1.7
org.freemarker
自由标记
2.3.29
伊奥·内蒂
荨麻
4.1.48.最终版本
org.nd4j
${nd4j.backend}
${dl4j master.version}
org.datavec
datavec api
${dl4j master.version}
org.datavec
数据向量数据图像
${dl4j master.version}
org.datavec
datavec本地
${dl4j master.version}
org.deeplearning4j
深入学习4J数据集
${dl4j master.version}
org.deeplearning4j
深度学习4J型芯
${dl4j master.version}
org.deeplearning4j
深度学习4J用户界面
${dl4j master.version}
org.deeplearning4j
深度学习4J动物园
${dl4j master.version}
org.deeplearning4j
深度学习4J并行包装器
${dl4j master.version}
jfree
柱状图
${jfreechart.version}
org.jfree
共同
${jcommon.version}
org.apache.httpcomponents
httpclient
4.3.5
回写
回归经典
${logback.version}
org.datavec
数据编解码器
${dl4j master.version}
org.bytedeco
javacv平台
1.5.2
maven enforcer插件
1.0.1
强制违约
执行
[${maven.minimum.version}，）
**********最小Maven版本为${Maven.Minimum.Version}。请在继续之前升级Maven（运行“mvn--Version”进行检查）**********
org.apache.maven.plugins
maven编译器插件
${maven编译器plugin.version}
1.7
1.7
com.lewisd
lint-maven插件
0.0.11
真的
重复的
冗余反转
绒布