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org.nd4j.linalg.api.ops.impl.accum.NormMax Maven / Gradle / Ivy
/*-
*
* * Copyright 2015 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.nd4j.linalg.api.ops.impl.accum;
import org.apache.commons.math3.util.FastMath;
import org.nd4j.linalg.api.complex.IComplexNumber;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.BaseAccumulation;
import org.nd4j.linalg.api.ops.Op;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.ops.transforms.Transforms;
/**
* The max absolute value
*
* @author Adam Gibson
*/
public class NormMax extends BaseAccumulation {
public NormMax() {}
public NormMax(INDArray x, INDArray y, INDArray z, long n) {
super(x, y, z, n);
}
public NormMax(INDArray x, INDArray y, long n) {
super(x, y, n);
}
public NormMax(INDArray x) {
super(x);
}
public NormMax(INDArray x, INDArray y) {
super(x, y);
}
@Override
public INDArray noOp() {
return Transforms.abs(x());
}
@Override
public double update(double accum, double x) {
numProcessed++;
return FastMath.max(FastMath.abs(x), accum);
}
@Override
public double update(double accum, double x, double y) {
return update(accum, x);
}
@Override
public float update(float accum, float x) {
return (x >= 0 ? (x > accum ? x : accum) : (-x > accum ? -x : accum));
}
@Override
public float update(float accum, float x, float y) {
return (x >= 0 ? (x > accum ? x : accum) : (-x > accum ? -x : accum));
}
@Override
public IComplexNumber update(IComplexNumber accum, double x) {
return (accum.absoluteValue().doubleValue() >= FastMath.abs(x) ? accum
: Nd4j.createComplexNumber(FastMath.abs(x), 0));
}
@Override
public IComplexNumber update(IComplexNumber accum, double x, double y) {
return (accum.absoluteValue().doubleValue() >= FastMath.abs(x) ? accum
: Nd4j.createComplexNumber(FastMath.abs(x), 0));
}
@Override
public IComplexNumber update(IComplexNumber accum, IComplexNumber x) {
return (accum.absoluteValue().doubleValue() >= x.absoluteValue().doubleValue() ? accum
: Nd4j.createComplexNumber(x.absoluteValue(), 0));
}
@Override
public IComplexNumber update(IComplexNumber accum, IComplexNumber x, IComplexNumber y) {
return (accum.absoluteValue().doubleValue() >= x.absoluteValue().doubleValue() ? accum
: Nd4j.createComplexNumber(x.absoluteValue(), 0));
}
@Override
public IComplexNumber update(IComplexNumber accum, IComplexNumber x, double y) {
return (accum.absoluteValue().doubleValue() >= x.absoluteValue().doubleValue() ? accum
: Nd4j.createComplexNumber(x.absoluteValue(), 0));
}
@Override
public int opNum() {
return 7;
}
@Override
public String name() {
return "normmax";
}
@Override
public IComplexNumber op(IComplexNumber origin, IComplexNumber other) {
throw new UnsupportedOperationException();
}
@Override
public IComplexNumber op(IComplexNumber origin, float other) {
throw new UnsupportedOperationException();
}
@Override
public IComplexNumber op(IComplexNumber origin, double other) {
throw new UnsupportedOperationException();
}
@Override
public IComplexNumber op(IComplexNumber origin) {
throw new UnsupportedOperationException();
}
@Override
public Op opForDimension(int index, int dimension) {
INDArray xAlongDimension = x.vectorAlongDimension(index, dimension);
if (y() != null)
return new NormMax(xAlongDimension, y.vectorAlongDimension(index, dimension), xAlongDimension.length());
else
return new NormMax(x.vectorAlongDimension(index, dimension));
}
@Override
public Op opForDimension(int index, int... dimension) {
INDArray xAlongDimension = x.tensorAlongDimension(index, dimension);
if (y() != null)
return new NormMax(xAlongDimension, y.tensorAlongDimension(index, dimension), xAlongDimension.length());
else
return new NormMax(x.tensorAlongDimension(index, dimension));
}
}