Java example source code file (SubsetVertex.java)

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Java - Java tags/keywords

cannot, cnn, data, graphvertex, indarray, invalidinputtypeexception, jsonproperty, override, received, rnn, runtimeexception, string, subsetvertex, util

The SubsetVertex.java Java example source code

/*
 *
 *  * Copyright 2016 Skymind,Inc.
 *  *
 *  *    Licensed under the Apache License, Version 2.0 (the "License");
 *  *    you may not use this file except in compliance with the License.
 *  *    You may obtain a copy of the License at
 *  *
 *  *        http://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.
 *
 */

package org.deeplearning4j.nn.conf.graph;

import com.fasterxml.jackson.annotation.JsonProperty;
import lombok.Data;
import lombok.EqualsAndHashCode;
import org.deeplearning4j.nn.conf.inputs.InputType;
import org.deeplearning4j.nn.conf.inputs.InvalidInputTypeException;
import org.deeplearning4j.nn.graph.ComputationGraph;
import org.nd4j.linalg.api.ndarray.INDArray;

import java.util.Arrays;

/** SubsetVertex is used to select a subset of the activations out of another GraphVertex.<br>
 * For example, a subset of the activations out of a layer.<br>
 * Note that this subset is specifying by means of an interval of the original activations.
 * For example, to get the first 10 activations of a layer (or, first 10 features out of a CNN layer) use
 * new SubsetVertex(0,9).<br>
 * In the case of convolutional (4d) activations, this is done along depth.
 * @author Alex Black
 */
@Data @EqualsAndHashCode(callSuper=false)
public class SubsetVertex extends GraphVertex {

    private int from;
    private int to;

    /**
     * @param from The first column index, inclusive
     * @param to The last column index, inclusive
     */
    public SubsetVertex(@JsonProperty("from") int from, @JsonProperty("to") int to) {
        this.from = from;
        this.to = to;
    }

    @Override
    public SubsetVertex clone() {
        return new SubsetVertex(from,to);
    }

    @Override
    public boolean equals(Object o){
        if(!(o instanceof SubsetVertex)) return false;
        SubsetVertex s = (SubsetVertex)o;
        return s.from == from && s.to == to;
    }

    @Override
    public int hashCode(){
        return new Integer(from).hashCode() ^ new Integer(to).hashCode();
    }

    @Override
    public int numParams(boolean backprop){
        return 0;
    }

    @Override
    public org.deeplearning4j.nn.graph.vertex.GraphVertex instantiate(ComputationGraph graph, String name, int idx,
                                                                      INDArray paramsView, boolean initializeParams) {
        return new org.deeplearning4j.nn.graph.vertex.impl.SubsetVertex(graph,name,idx,from,to);
    }

    @Override
    public InputType getOutputType(InputType... vertexInputs) throws InvalidInputTypeException {
        if(vertexInputs.length != 1){
            throw new InvalidInputTypeException("SubsetVertex expects single input type. Received: " + Arrays.toString(vertexInputs));
        }

        switch(vertexInputs[0].getType()){
            case FF:
                return InputType.feedForward(to-from+1);
            case RNN:
                return InputType.recurrent(to-from+1);
            case CNN:
                InputType.InputTypeConvolutional conv = (InputType.InputTypeConvolutional)vertexInputs[0];
                int depth = conv.getDepth();
                if(to >= depth){
                    throw new InvalidInputTypeException("Invalid range: Cannot select depth subset [" + from + "," + to + "] inclusive from CNN activations with "
                            + " [depth,width,height] = [" + depth + "," + conv.getWidth() + "," + conv.getHeight() + "]" );
                }
                return InputType.convolutional(from-to+1,conv.getWidth(),conv.getHeight());
            default:
                throw new RuntimeException("Unknown input type: " + vertexInputs[0]);
        }
    }
}