org.nd4j.linalg.api.ops.impl.transforms.same.Identity Maven / Gradle / Ivy
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* * terms of the Apache License, Version 2.0 which is available at
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package org.nd4j.linalg.api.ops.impl.transforms.same;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.impl.transforms.BaseDynamicTransformOp;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
public class Identity extends BaseDynamicTransformOp {
public Identity(SameDiff sd, SDVariable input){
super(sd, new SDVariable[]{input}, false);
}
public Identity(INDArray x, INDArray z){
super(new INDArray[]{x}, new INDArray[]{z});
}
public Identity(INDArray x){
super(new INDArray[]{x}, null);
}
public Identity(){ }
@Override
public String opName() {
return "identity";
}
@Override
public String onnxName() {
return "Constant";
}
@Override
public String tensorflowName() {
return "Identity";
}
@Override
public String[] tensorflowNames() {
return new String[]{"Identity", "DeepCopy", "CopyHost"};
}
@Override
public List doDiff(List i_v) {
//Eventually we'll optimize this out
return Collections.singletonList(sameDiff.identity(i_v.get(0)));
}
@Override
public List calculateOutputDataTypes(List dataTypes) {
Preconditions.checkState(dataTypes != null && dataTypes.size() == 1, "Expected exactly 1 input datatype for %s, got input %s", getClass(), dataTypes);
if(!dArguments.isEmpty())
return Arrays.asList(dArguments.get(0));
return dataTypes;
}
}