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/*
 * Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
 * with the License. A copy of the License is located at
 *
 * http://aws.amazon.com/apache2.0/
 *
 * or in the "license" file accompanying this file. This file 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.
 */
package ai.djl.training.dataset;

import ai.djl.ndarray.NDArray;
import ai.djl.ndarray.NDList;
import ai.djl.ndarray.NDManager;
import java.util.stream.Stream;

/**
 * {@code ArrayDataset} is an implementation of {@link RandomAccessDataset} that consist entirely of
 * large {@link NDArray}s. There can be multiple data and label {@link NDArray}s within the dataset.
 * Each sample will be retrieved by indexing each {@link NDArray} along the first dimension.
 *
 * 

The following is an example of how to use ArrayDataset: * *

 *     ArrayDataset dataset = new ArrayDataset.Builder()
 *                              .setData(data)
 *                              .optLabels(label)
 *                              .setSampling(20, false)
 *                              .build();
 * 
* * @see Dataset */ public class ArrayDataset extends RandomAccessDataset { protected NDArray[] data; protected NDArray[] labels; /** * Creates a new instance of {@code ArrayDataset} with the arguments in {@link Builder}. * * @param builder a builder with the required arguments */ public ArrayDataset(BaseBuilder builder) { super(builder); if (builder instanceof Builder) { Builder builder2 = (Builder) builder; data = builder2.data; labels = builder2.labels; // check data and labels have the same size long size = data[0].size(0); if (Stream.of(data).anyMatch(array -> array.size(0) != size)) { throw new IllegalArgumentException("All the NDArray must have the same length!"); } if (labels != null && Stream.of(labels).anyMatch(array -> array.size(0) != size)) { throw new IllegalArgumentException("All the NDArray must have the same length!"); } } } /** {@inheritDoc} */ @Override protected long availableSize() { return data[0].size(0); } /** {@inheritDoc} */ @Override public Record get(NDManager manager, long index) { NDList datum = new NDList(); NDList label = new NDList(); for (NDArray array : data) { datum.add(array.get(index)); } if (labels != null) { for (NDArray array : labels) { label.add(array.get(index)); } } datum.attach(manager); label.attach(manager); return new Record(datum, label); } /** The Builder to construct an {@link ArrayDataset}. */ public static final class Builder extends BaseBuilder { private NDArray[] data; private NDArray[] labels; /** {@inheritDoc} */ @Override protected Builder self() { return this; } /** * Sets the data as an {@link NDArray} for the {@code ArrayDataset}. * * @param data an array of {@link NDArray} that contains the data * @return this Builder */ public Builder setData(NDArray... data) { this.data = data; return self(); } /** * Sets the labels for the data in the {@code ArrayDataset}. * * @param labels an array of {@link NDArray} that contains the labels * @return this Builder */ public Builder optLabels(NDArray... labels) { this.labels = labels; return self(); } /** * Builds a new instance of {@code ArrayDataset} with the specified data and labels. * * @return a new instance of {@code ArrayDataset} */ public ArrayDataset build() { if (data == null || data.length == 0) { throw new IllegalArgumentException("Please pass in at least one data"); } return new ArrayDataset(this); } } }




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