org.nd4j.linalg.api.ops.impl.shape.Diag Maven / Gradle / Ivy
package org.nd4j.linalg.api.ops.impl.shape;
import onnx.OnnxProto3;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
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.Arrays;
import java.util.List;
import java.util.Map;
/**
* Computes a diagonal matrix of shape (n, n) from a vector of length n.
* More generally puts a an n-dimensional tensor on the diagonal part
* of a tensor of 2*n dimensions.
*
* @author Max Pumperla
*/
public class Diag extends DynamicCustomOp {
public Diag() {
}
public Diag(INDArray[] inputs, INDArray[] outputs) {
super(null, inputs, outputs);
}
public Diag(SameDiff sameDiff, SDVariable[] args, boolean inPlace) {
super(null, sameDiff, args, inPlace);
}
@Override
public List doDiff(List i_v) {
SDVariable grad = i_v.get(0);
SDVariable ret = sameDiff.diagPart(grad);
return Arrays.asList(ret);
}
@Override
public String opName() {
return "diag";
}
@Override
public String tensorflowName() {
return "Diag";
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
super.initFromTensorFlow(nodeDef, initWith, attributesForNode, graph);
}
@Override
public void initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map attributesForNode, OnnxProto3.GraphProto graph) {
super.initFromOnnx(node, initWith, attributesForNode, graph);
}
}