org.nd4j.linalg.api.ops.impl.shape.Rank Maven / Gradle / Ivy
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package org.nd4j.linalg.api.ops.impl.shape;
import lombok.extern.slf4j.Slf4j;
import onnx.Onnx;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import java.util.*;
@Slf4j
public class Rank extends DynamicCustomOp {
public Rank() {
}
public Rank(SameDiff sameDiff, SDVariable input) {
this(sameDiff, input, false);
}
public Rank(SameDiff sameDiff, SDVariable input, boolean inPlace) {
super(null, sameDiff, new SDVariable[] {input}, inPlace);
}
public Rank(INDArray indArray) {
addInputArgument(indArray);
}
@Override
public void initFromOnnx(Onnx.NodeProto node, SameDiff initWith, Map attributesForNode, Onnx.GraphProto graph) {
}
@Override
public String opName() {
return "rank";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx found for op " + opName());
}
@Override
public String tensorflowName() {
return "Rank";
}
@Override
public List doDiff(List i_v) {
return Collections.singletonList(sameDiff.zerosLike(arg()));
}
@Override
public List calculateOutputDataTypes(List dataTypes) {
Preconditions.checkState(dataTypes.size() == 1, "Expected list with exactly 1 datatype for %s, got %s", getClass(), dataTypes);
if(!dArguments.isEmpty())
return Collections.singletonList(dArguments.get(0));
//Output type is always int
return Collections.singletonList(DataType.INT);
}
}