parent
ba269a26ab
commit
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@ -1562,8 +1562,8 @@ public class DifferentialFunctionFactory {
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}
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public SDVariable eluBp(SDVariable in, SDVariable epsilon) {
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return new EluBp(sameDiff(), in, epsilon).outputVariable();
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public SDVariable eluBp(SDVariable in, SDVariable epsilon, double alpha) {
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return new EluBp(sameDiff(), in, epsilon, alpha).outputVariable();
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}
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@ -18,14 +18,12 @@ package org.nd4j.linalg.activations.impl;
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import lombok.EqualsAndHashCode;
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import lombok.Getter;
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import org.nd4j.linalg.api.ops.impl.transforms.gradient.EluBp;
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import org.nd4j.linalg.primitives.Pair;
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import org.nd4j.linalg.activations.BaseActivationFunction;
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import org.nd4j.linalg.api.ndarray.INDArray;
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import org.nd4j.linalg.api.ops.impl.transforms.gradient.EluBp;
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import org.nd4j.linalg.api.ops.impl.transforms.strict.ELU;
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import org.nd4j.linalg.factory.Nd4j;
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import org.nd4j.linalg.indexing.BooleanIndexing;
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import org.nd4j.linalg.indexing.conditions.Conditions;
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import org.nd4j.linalg.primitives.Pair;
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/**
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* f(x) = alpha * (exp(x) - 1.0); x < 0
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@ -55,15 +53,7 @@ public class ActivationELU extends BaseActivationFunction {
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*/
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@Override
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public INDArray getActivation(INDArray in, boolean training) {
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// no support in ELU native to override alpha
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if (this.alpha != 1.00) {
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INDArray alphaMultiple = Nd4j.getExecutioner().exec(new ELU(in.dup()))[0];
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alphaMultiple.muli(alpha);
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BooleanIndexing.replaceWhere(in, alphaMultiple, Conditions.lessThan(0));
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} else {
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Nd4j.getExecutioner().execAndReturn(new ELU(in));
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}
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return in;
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return Nd4j.exec(new ELU(in, in, alpha))[0];
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}
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/*
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@ -33,8 +33,9 @@ public class EluBp extends DynamicCustomOp {
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public EluBp(){ }
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public EluBp(SameDiff sd, SDVariable input, SDVariable gradient){
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public EluBp(SameDiff sd, SDVariable input, SDVariable gradient, double alpha){
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super(sd, new SDVariable[]{input, gradient});
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addTArgument(alpha);
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}
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public EluBp(@NonNull INDArray input, @NonNull INDArray gradient, INDArray output) {
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@ -23,13 +23,9 @@ import org.nd4j.imports.NoOpNameFoundException;
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import org.nd4j.linalg.api.buffer.DataType;
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import org.nd4j.linalg.api.ndarray.INDArray;
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import org.nd4j.linalg.api.ops.DynamicCustomOp;
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import org.tensorflow.framework.AttrValue;
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import org.tensorflow.framework.GraphDef;
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import org.tensorflow.framework.NodeDef;
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import java.util.Collections;
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import java.util.List;
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import java.util.Map;
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/**
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* ELU: Exponential Linear Unit (alpha=1.0)<br>
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@ -41,19 +37,31 @@ import java.util.Map;
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* @author Alex Black
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*/
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public class ELU extends DynamicCustomOp {
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public static final double DEFAULT_ALPHA = 1.0;
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protected double alpha;
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public ELU(SameDiff sameDiff, SDVariable i_v) {
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super(sameDiff, new SDVariable[]{i_v});
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this.alpha = DEFAULT_ALPHA;
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addTArgument(alpha);
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}
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public ELU() {
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}
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public ELU(INDArray x, INDArray z) {
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this(x, z, DEFAULT_ALPHA);
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}
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public ELU(INDArray x, INDArray z, double alpha) {
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super(null, wrapOrNull(x), wrapOrNull(z));
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this.alpha = alpha;
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addTArgument(alpha);
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}
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public ELU(INDArray x) {
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this(x, null);
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this(x, null, DEFAULT_ALPHA);
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}
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@Override
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@ -75,7 +83,7 @@ public class ELU extends DynamicCustomOp {
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public List<SDVariable> doDiff(List<SDVariable> i_v) {
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//ELU: e^x-1 if x<0, x otherwise
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//dL/dIn = dL/Out * dOut/dIn
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return Collections.singletonList(f().eluBp(arg(), i_v.get(0)));
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return Collections.singletonList(f().eluBp(arg(), i_v.get(0), alpha));
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}
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@Override
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