87 lines
3.0 KiB
Java
87 lines
3.0 KiB
Java
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/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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package org.deeplearning4j.base;
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import org.apache.commons.io.IOUtils;
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import org.deeplearning4j.common.resources.DL4JResources;
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import org.deeplearning4j.common.resources.ResourceType;
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import org.nd4j.linalg.api.ndarray.INDArray;
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import org.nd4j.linalg.dataset.DataSet;
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import org.nd4j.linalg.factory.Nd4j;
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import org.nd4j.resources.Downloader;
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import java.io.File;
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import java.io.FileInputStream;
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import java.io.IOException;
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import java.io.InputStream;
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import java.net.URL;
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import java.util.ArrayList;
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import java.util.List;
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public class IrisUtils {
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private static final String IRIS_RELATIVE_URL = "datasets/iris.dat";
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private static final String MD5 = "1c21400a78061197eac64c6748844216";
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private IrisUtils() {}
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public static List<DataSet> loadIris(int from, int to) throws IOException {
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File rootDir = DL4JResources.getDirectory(ResourceType.DATASET, "iris");
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File irisData = new File(rootDir, "iris.dat");
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if(!irisData.exists()){
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URL url = DL4JResources.getURL(IRIS_RELATIVE_URL);
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Downloader.download("Iris", url, irisData, MD5, 3);
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}
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@SuppressWarnings("unchecked")
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List<String> lines;
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try(InputStream is = new FileInputStream(irisData)){
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lines = IOUtils.readLines(is);
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}
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List<DataSet> list = new ArrayList<>();
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INDArray ret = Nd4j.ones(Math.abs(to - from), 4);
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double[][] outcomes = new double[lines.size()][3];
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int putCount = 0;
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for (int i = from; i < to; i++) {
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String line = lines.get(i);
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String[] split = line.split(",");
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addRow(ret, putCount++, split);
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String outcome = split[split.length - 1];
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double[] rowOutcome = new double[3];
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rowOutcome[Integer.parseInt(outcome)] = 1;
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outcomes[i] = rowOutcome;
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}
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for (int i = 0; i < ret.rows(); i++) {
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DataSet add = new DataSet(ret.getRow(i, true), Nd4j.create(outcomes[from + i], new long[]{1,3}));
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list.add(add);
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}
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return list;
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}
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private static void addRow(INDArray ret, int row, String[] line) {
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double[] vector = new double[4];
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for (int i = 0; i < 4; i++)
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vector[i] = Double.parseDouble(line[i]);
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ret.putRow(row, Nd4j.create(vector));
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}
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}
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