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/*******************************************************************************
 * Copyright (c) 2015-2018 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
 ******************************************************************************/

package org.datavec.api.io.labels;

import org.datavec.api.writable.Writable;

import java.io.Serializable;
import java.net.URI;
import java.util.List;

/**
 * PathMultiLabelGenerator: interface to infer the label(s) of a file directly from the URI/path

 * Similar to {@link PathLabelGenerator}, with 2 main differences:

 * (a) Can be used for multi-label, multi-class classification (i.e., return *multiple* NDArray writables, for use in
 * networks with multiple output layers)

 * (b) Does not support inferring label classes

 * 

 * Regarding (b) above, this means that the implementations of PathMultiLabelGenerator typically need to (for classification
 * use cases) do one of two things (either will work, though down-stream usage of these arrays can vary slightly):
 * (a) Perform label to integer index assignment (i.e., return an IntWritable(0) for A, if you have 3 classes {A,B,C})
 * (b) Create a one-hot NDArrayWritable. For 3 classes {A,B,C} you should return a [1,0,0], [0,1,0] or [0,0,1] NDArrayWritable

 * Comparatively, PathLabelGenerator can return a Text writable with the label (i.e., "class_3" or "cat") for classification.

 * 

 * More generally, PathMultiLabelGenerator must return Writables of one of the following types:
 * {@link org.datavec.api.writable.DoubleWritable}, {@link org.datavec.api.writable.FloatWritable},
 * {@link org.datavec.api.writable.IntWritable}, {@link org.datavec.api.writable.LongWritable} or
 * {@link org.datavec.api.writable.NDArrayWritable}.

 * NDArrayWritable is used for classification (via one-hot NDArrayWritable) or multi-output regression (where all values
 * are grouped together into a single array/writable) - whereas the others (double/float/int/long writables) are
 * typically used for single output regression cases, or (IntWritable) for classification where downstream classes (notably
 * DL4J's RecordReader(Multi)DataSetIterator) will convert the integer index (IntWritable) to a one-hot array ready for
 * training.

 * 

 * In principle, you can also return time series (3d - shape [1,size,seqLength]) or images (4d - shape
 * [1,channels,height,width]) as a "label" for a given input image.
 *
 * @author Alex Black
 * @see PathLabelGenerator
 */
public interface PathMultiLabelGenerator extends Serializable {

    /**
     * @param uriPath The file or URI path to get the label for
     * @return A list of labels for the specified URI/path
     */
    List getLabels(String uriPath);

}