org.nd4j.linalg.api.ops.impl.shape.tensorops.BaseTensorOp Maven / Gradle / Ivy
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* * terms of the Apache License, Version 2.0 which is available at
* * https://www.apache.org/licenses/LICENSE-2.0.
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package org.nd4j.linalg.api.ops.impl.shape.tensorops;
import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.imports.graphmapper.tf.TFGraphMapper;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.api.ops.Op;
import org.nd4j.linalg.api.shape.LongShapeDescriptor;
import org.nd4j.linalg.factory.Nd4j;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.List;
import java.util.Map;
public abstract class BaseTensorOp extends DynamicCustomOp {
public BaseTensorOp(String name, SameDiff sameDiff, SDVariable[] args){
super(name, sameDiff, args);
}
public BaseTensorOp(SameDiff sameDiff, SDVariable[] args){
super(null, sameDiff, args);
}
public BaseTensorOp(){}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
val inputOne = nodeDef.getInput(1);
val varFor = initWith.getVariable(inputOne);
val nodeWithIndex = TFGraphMapper.getNodeWithNameFromGraph(graph,inputOne);
val var = TFGraphMapper.getArrayFrom(nodeWithIndex,graph);
if(var != null) {
val idx = var.getInt(0);
addIArgument(idx);
}
}
@Override
public List doDiff(List f1) {
throw new UnsupportedOperationException("Differentiation not yet implemented for " + getClass().getName());
}
@Override
public Op.Type opType() {
return Op.Type.CUSTOM;
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op name found for " + opName());
}
@Override
public String toString() {
return opName();
}
@Override
public List calculateOutputShape() {
throw new UnsupportedOperationException("calculateOutputShape() is not supported for tensor ops.");
}
@Override
public void computeArrays() {
addOutputArgument(Nd4j.scalar(1.0f));
}
@Override
public int getNumOutputs() {
//1 output in allay cases - sometimes just a dummy output, however
return 1;
}
}