org.nd4j.linalg.api.ops.impl.transforms.BinCount Maven / Gradle / Ivy
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package org.nd4j.linalg.api.ops.impl.transforms;
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.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 BinCount extends DynamicCustomOp {
private Integer minLength;
private Integer maxLength;
private DataType outputType;
public BinCount(){ }
public BinCount(SameDiff sd, SDVariable in, SDVariable weights, Integer minLength, Integer maxLength, DataType outputType) {
super(sd, weights == null ? new SDVariable[]{in} : new SDVariable[]{in, weights}, false);
Preconditions.checkState((minLength == null) != (maxLength == null), "Cannot have only one of minLength and maxLength" +
"non-null: both must be simultaneously null or non-null. minLength=%s, maxLength=%s", minLength, maxLength);
this.minLength = minLength;
this.maxLength = maxLength;
this.outputType = outputType;
addArgs();
}
private void addArgs(){
if(minLength != null)
addIArgument(minLength);
if(maxLength != null)
addIArgument(maxLength);
}
@Override
public String opName(){
return "bincount";
}
@Override
public String tensorflowName() {
return "Bincount";
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
if(attributesForNode.containsKey("T")) {
outputType = TFGraphMapper.convertType(attributesForNode.get("T").getType());
}
}
@Override
public List doDiff(List i_v) {
throw new UnsupportedOperationException("Not supported");
}
@Override
public List calculateOutputDataTypes(List inputTypes){
Preconditions.checkState(inputTypes != null && (inputTypes.size() >= 1 && inputTypes.size() <= 4), "Expected 1 to 4 input types, got %s for op %s",
inputTypes, getClass());
//If weights present, same type as weights. Otherwise specified dtype
if(inputTypes.size() >= 2) {
//weights available case or TF import case (args 2/3 are min/max)
return Collections.singletonList(inputTypes.get(1));
} else {
Preconditions.checkNotNull(outputType, "No output type available - output type must be set unless weights input is available");
return Collections.singletonList(outputType);
}
}
}