Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
/*-
*
* * 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.nd4j.linalg.api.complex.IComplexNumber;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.Op;
/**
* Calculate the absolute mean of the given vector
*
* @author [email protected]
*/
public class AMean extends ASum {
public AMean() {}
public AMean(INDArray x, INDArray y, INDArray z, long n) {
super(x, y, z, n);
}
public AMean(INDArray x, INDArray y, long n) {
super(x, y, n);
}
public AMean(INDArray x) {
super(x);
}
public AMean(INDArray x, INDArray y) {
super(x, y);
}
public AMean(INDArray x, INDArray y, INDArray z) {
super(x, y, z, x.lengthLong());
}
@Override
public int opNum() {
return 15;
}
@Override
public String name() {
return "amean";
}
@Override
public Op opForDimension(int index, int dimension) {
INDArray xAlongDimension = x.vectorAlongDimension(index, dimension);
AMean ret;
if (y() != null)
ret = new AMean(xAlongDimension, y.vectorAlongDimension(index, dimension), xAlongDimension.length());
else
ret = new AMean(x.vectorAlongDimension(index, dimension));
ret.setApplyFinalTransform(applyFinalTransform());
return ret;
}
@Override
public Op opForDimension(int index, int... dimension) {
INDArray xAlongDimension = x.tensorAlongDimension(index, dimension);
AMean ret;
if (y() != null)
ret = new AMean(xAlongDimension, y.tensorAlongDimension(index, dimension), xAlongDimension.length());
else
ret = new AMean(x.tensorAlongDimension(index, dimension));
ret.setApplyFinalTransform(applyFinalTransform());
return ret;
}
@Override
public double getAndSetFinalResult(double accum) {
double result;
if (applyFinalTransform()) {
result = accum / n();
this.finalResult = result;
} else {
result = accum;
this.finalResult = result;
}
return result;
}
@Override
public float getAndSetFinalResult(float accum) {
if (applyFinalTransform()) {
float f = accum / n();
this.finalResult = f;
return f;
} else {
this.finalResult = accum;
return accum;
}
}
@Override
public double calculateFinalResult(double accum, long n) {
if (applyFinalTransform())
return accum / n;
return accum;
}
@Override
public float calculateFinalResult(float accum, long n) {
if (applyFinalTransform())
return accum / n;
return accum;
}
@Override
public IComplexNumber getAndSetFinalResult(IComplexNumber accum) {
finalResultComplex = accum.div(n());
return finalResultComplex;
}
}