nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/transforms/custom/Min.java
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* * terms of the Apache License, Version 2.0 which is available at
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package org.nd4j.linalg.api.ops.impl.transforms.custom;
import lombok.NonNull;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.impl.transforms.BaseDynamicTransformOp;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
public class Min extends BaseDynamicTransformOp {
public Min() {}
public Min(SameDiff sameDiff, @NonNull SDVariable first, @NonNull SDVariable second){
this(sameDiff, new SDVariable[]{first, second}, false);
}
public Min( SameDiff sameDiff, SDVariable[] args, boolean inPlace) {
super(sameDiff, args, inPlace);
}
public Min( INDArray first, INDArray second, INDArray out){
super(new INDArray[]{first, second}, out == null ? null : new INDArray[]{out});
}
public Min( INDArray first, INDArray second){
this(first, second, null);
}
public Min( INDArray[] inputs, INDArray[] outputs) {
super(inputs, outputs);
}
@Override
public String opName() {
return "minimum";
}
@Override
public String onnxName() {
return "Min";
}
@Override
public String tensorflowName() {
return "Minimum";
}
@Override
public List<SDVariable> doDiff(List<SDVariable> f1) {
//TODO Switch to minimum_bp op - https://github.com/eclipse/deeplearning4j/blob/master/libnd4j/include/ops/declarable/generic/broadcastable/minimum.cpp
SDVariable min = outputVariables()[0];
SDVariable eq1 = sameDiff.eq(larg(), min).castTo(arg(0).dataType());
SDVariable eq2 = sameDiff.eq(rarg(), min).castTo(arg(1).dataType());
return Arrays.asList(eq1.mul(f1.get(0)), eq2.mul(f1.get(0)));
}
@Override
public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 2, "Expected exactly 2 input datatypes for %s, got %s", getClass(), dataTypes);
Preconditions.checkState(dataTypes.get(0) == dataTypes.get(1), "Input datatypes must be the same, got %s", dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
}