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org.nd4j.linalg.api.ops.impl.accum.distances.CosineDistance 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.distances;
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.api.ops.executioner.OpExecutioner;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.util.ArrayUtil;
/**
* Cosine distance
* Note that you need to initialize
* a scaling constant equal to the norm2 of the
* vector
*
* @author [email protected]
*/
public class CosineDistance extends BaseAccumulation {
private Number constantNormalizedByNorm2X, constantNormalizedByNorm2Y;
public CosineDistance() {
passThrough = true;
}
public CosineDistance(INDArray x, INDArray y, INDArray z, long n) {
super(x, y, z, n);
passThrough = Nd4j.getExecutioner().executionMode() == OpExecutioner.ExecutionMode.JAVA;
extraArgs = new Object[2];
extraArgs[0] = 0.0f;
extraArgs[1] = 0.0f;
}
public CosineDistance(INDArray x, INDArray y, long n) {
super(x, y, n);
passThrough = Nd4j.getExecutioner().executionMode() == OpExecutioner.ExecutionMode.JAVA;
extraArgs = new Object[2];
extraArgs[0] = 0.0f;
extraArgs[1] = 0.0f;
}
public CosineDistance(INDArray x) {
super(x);
passThrough = Nd4j.getExecutioner().executionMode() == OpExecutioner.ExecutionMode.JAVA;
extraArgs = new Object[2];
extraArgs[0] = 0.0f;
extraArgs[1] = 0.0f;
}
public CosineDistance(INDArray x, INDArray y) {
super(x, y);
passThrough = Nd4j.getExecutioner().executionMode() == OpExecutioner.ExecutionMode.JAVA;
extraArgs = new Object[2];
extraArgs[0] = 0.0f;
extraArgs[1] = 0.0f;
}
public CosineDistance(INDArray x, INDArray y, INDArray z, boolean allDistances) {
this(x,y,z, x.lengthLong());
isComplex = allDistances;
}
public CosineDistance(INDArray x, INDArray y, boolean allDistances) {
this(x,y);
isComplex = allDistances;
}
@Override
public double update(double accum, double x) {
return accum + x;
}
@Override
public double update(double accum, double x, double y) {
return accum + x * y;
}
@Override
public float update(float accum, float x) {
return accum + x;
}
@Override
public float update(float accum, float x, float y) {
return accum + x * y;
}
@Override
public IComplexNumber update(IComplexNumber accum, double x) {
return accum.add(x);
}
@Override
public IComplexNumber update(IComplexNumber accum, double x, double y) {
return accum.add(x * y);
}
@Override
public IComplexNumber update(IComplexNumber accum, IComplexNumber x) {
return accum.add(x);
}
@Override
public IComplexNumber update(IComplexNumber accum, IComplexNumber x, IComplexNumber y) {
return accum.add(x.mul(y));
}
@Override
public IComplexNumber update(IComplexNumber accum, IComplexNumber x, double y) {
return accum.add(x.mul(y));
}
@Override
public int opNum() {
return 5;
}
@Override
public String name() {
return "cosinedistance";
}
@Override
public IComplexNumber op(IComplexNumber origin, double other) {
numProcessed++;
return origin.mul(other);
}
@Override
public IComplexNumber op(IComplexNumber origin, float other) {
numProcessed++;
return origin.mul(other);
}
@Override
public IComplexNumber op(IComplexNumber origin, IComplexNumber other) {
numProcessed++;
return origin.mul(other);
}
@Override
public float op(float origin, float other) {
numProcessed++;
return (origin * other);
}
@Override
public double op(double origin, double other) {
numProcessed++;
return origin * other;
}
@Override
public Op opForDimension(int index, int dimension) {
INDArray xAlongDimension = x.vectorAlongDimension(index, dimension);
CosineDistance ret;
if (y() != null)
ret = new CosineDistance(xAlongDimension, y.vectorAlongDimension(index, dimension),
xAlongDimension.length());
else
ret = new CosineDistance(x.vectorAlongDimension(index, dimension));
ret.setApplyFinalTransform(applyFinalTransform());
return ret;
}
@Override
public Op opForDimension(int index, int... dimension) {
INDArray xForDimesnion = x.tensorAlongDimension(index, dimension);
CosineDistance ret;
if (y() != null)
ret = new CosineDistance(xForDimesnion, y.tensorAlongDimension(index, dimension), xForDimesnion.length());
else
ret = new CosineDistance(x.tensorAlongDimension(index, dimension));
ret.setApplyFinalTransform(applyFinalTransform());
return ret;
}
@Override
public void exec() {
this.constantNormalizedByNorm2X = x.norm2Number();
this.constantNormalizedByNorm2Y = y.norm2Number();
this.extraArgs = new Object[] {0.0, constantNormalizedByNorm2X, constantNormalizedByNorm2Y};
double dot = Nd4j.getBlasWrapper().dot(x, y);
this.finalResult = dot / (constantNormalizedByNorm2X.doubleValue() * constantNormalizedByNorm2Y.doubleValue());
}
@Override
public void exec(int... dimension) {
int[] retShape = ArrayUtil.removeIndex(x.shape(), dimension);
int nOps = x.tensorssAlongDimension(dimension);
z = Nd4j.create(retShape);
for (int i = 0; i < nOps; i++) {
double d = Nd4j.getExecutioner().execAndReturn((CosineDistance) opForDimension(i, dimension))
.getFinalResult().doubleValue();
z.putScalar(i, d);
}
}
@Override
public double getAndSetFinalResult(double accum) {
if (applyFinalTransform()) {
double d = accum / (constantNormalizedByNorm2X.doubleValue() * constantNormalizedByNorm2Y.doubleValue());
this.finalResult = d;
return d;
} else {
return accum;
}
}
@Override
public float getAndSetFinalResult(float accum) {
return (float) getAndSetFinalResult((double) accum);
}
@Override
public IComplexNumber getAndSetFinalResult(IComplexNumber accum) {
finalResultComplex = Nd4j.createComplexNumber(accum.realComponent().doubleValue()
/ (constantNormalizedByNorm2X.doubleValue() * constantNormalizedByNorm2Y.doubleValue()), 0);
return finalResultComplex;
}
@Override
public double calculateFinalResult(double accum, long n) {
throw new UnsupportedOperationException("Not supported for passthrough op");
}
@Override
public float calculateFinalResult(float accum, long n) {
throw new UnsupportedOperationException("Not supported for passthrough op");
}
}
