org.nd4j.linalg.api.ops.impl.transforms.custom.InTopK Maven / Gradle / Ivy
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package org.nd4j.linalg.api.ops.impl.transforms.custom;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.imports.graphmapper.tf.TFGraphMapper;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.Collections;
import java.util.List;
import java.util.Map;
public class InTopK extends DynamicCustomOp {
private boolean sorted;
private int k;
public InTopK(){ }
public InTopK(SameDiff sd, SDVariable predictions, SDVariable targets, int k){
super(sd, new SDVariable[]{predictions, targets}, false);
this.k = k;
addIArgument(k);
}
@Override
public String opName(){
return "in_top_k";
}
@Override
public String tensorflowName() {
return "InTopKV2";
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
String thisName = nodeDef.getName();
String inputName = thisName + "/k";
NodeDef kNode = null;
for(int i = 0; i < graph.getNodeCount(); i++) {
if(graph.getNode(i).getName().equals(inputName)){
kNode = graph.getNode(i);
break;
}
}
Preconditions.checkState(kNode != null, "Could not find 'k' parameter node for op: %s", thisName);
INDArray arr = TFGraphMapper.getNDArrayFromTensor(kNode);
this.k = arr.getInt(0);
addIArgument(k);
}
@Override
public List doDiff(List i_v) {
throw new UnsupportedOperationException("Not implemented yet");
}
@Override
public List calculateOutputDataTypes(List dataTypes){
//3rd input: dynamic K value
Preconditions.checkState(dataTypes != null && !dataTypes.isEmpty(), "Expected at least 1 input data types. for %s, got %s", getClass(), dataTypes);
return Collections.singletonList(DataType.BOOL);
}
}