org.deeplearning4j.nn.conf.layers.CapsuleStrengthLayer Maven / Gradle / Ivy

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package org.deeplearning4j.nn.conf.layers;

import lombok.Data;
import lombok.EqualsAndHashCode;
import lombok.NoArgsConstructor;
import org.deeplearning4j.nn.conf.inputs.InputType;
import org.deeplearning4j.nn.conf.inputs.InputType.InputTypeRecurrent;
import org.deeplearning4j.nn.conf.inputs.InputType.Type;
import org.deeplearning4j.nn.conf.layers.samediff.SameDiffLambdaLayer;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;

@Data
@NoArgsConstructor
@EqualsAndHashCode(callSuper = true)
public class CapsuleStrengthLayer extends SameDiffLambdaLayer {

    public CapsuleStrengthLayer(Builder builder){
        super();
    }

    @Override
    public SDVariable defineLayer(SameDiff SD, SDVariable layerInput) {
        return SD.norm2("caps_strength", layerInput, 2);
    }

    @Override
    public InputType getOutputType(int layerIndex, InputType inputType) {

        if(inputType == null || inputType.getType() != Type.RNN) {
            throw new IllegalStateException("Invalid input for Capsule Strength layer (layer name = \""
                    + layerName + "\"): expect RNN input.  Got: " + inputType);
        }

        InputTypeRecurrent ri = (InputTypeRecurrent) inputType;
        return InputType.feedForward(ri.getSize());
    }

    public static class Builder extends SameDiffLambdaLayer.Builder{

        @Override
        public  E build() {
            return (E) new CapsuleStrengthLayer(this);
        }
    }
}