org.nd4j.linalg.api.ops.impl.transforms.HistogramFixedWidth 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.NoOpNameFoundException;
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 HistogramFixedWidth extends DynamicCustomOp {
public HistogramFixedWidth(SameDiff sameDiff, SDVariable values, SDVariable valuesRange, SDVariable numBins) {
super(sameDiff, numBins == null ? new SDVariable[]{values, valuesRange} : new SDVariable[]{values, valuesRange, numBins}, false);
}
public HistogramFixedWidth() {
//no-op
}
@Override
public String opName() {
return "histogram_fixed_width";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
return "HistogramFixedWidth";
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
//No op - just need the inputs
}
@Override
public List doDiff(List f1) {
throw new UnsupportedOperationException("Not supported");
}
@Override
public List calculateOutputDataTypes(List dataTypes){
//1 or 2 possible: 2 for TF import (fill with specified value
Preconditions.checkState(dataTypes != null && (dataTypes.size() == 2 || dataTypes.size() == 3),
"Expected 2 or 3 input datatypes for %s, got %s", getClass(), dataTypes);
//TODO MAKE CONFIGURABLE
return Collections.singletonList(DataType.INT);
}
}