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// Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package ai.vespa.rankingexpression.importer.operations;
import ai.vespa.rankingexpression.importer.DimensionRenamer;
import ai.vespa.rankingexpression.importer.OrderedTensorType;
import com.yahoo.searchlib.rankingexpression.Reference;
import com.yahoo.tensor.functions.Reduce;
import com.yahoo.tensor.functions.TensorFunction;
import java.util.List;
public class ConcatReduce extends IntermediateOperation {
private final static String tmpDimensionName = "__concat_reduce_tmp_dimension_name__";
private final Reduce.Aggregator aggregator;
public ConcatReduce(String modelName, String nodeName, List<IntermediateOperation> inputs, Reduce.Aggregator aggregator) {
super(modelName, nodeName, inputs);
this.aggregator = aggregator;
}
@Override
protected OrderedTensorType lazyGetType() {
if ( ! allInputTypesPresent(inputs.size())) return null;
return inputs.get(0).type().get();
}
@Override
protected TensorFunction<Reference> lazyGetFunction() {
if ( ! allInputFunctionsPresent(inputs.size())) return null;
TensorFunction<Reference> result = inputs.get(0).function().get();
for (int i = 1; i < inputs.size(); ++i) {
TensorFunction<Reference> b = inputs.get(i).function().get();
result = new com.yahoo.tensor.functions.Concat<>(result, b, tmpDimensionName);
}
return new com.yahoo.tensor.functions.Reduce<>(result, aggregator, tmpDimensionName);
}
@Override
public void addDimensionNameConstraints(DimensionRenamer renamer) {
if ( ! allInputTypesPresent(inputs.size())) return;
OrderedTensorType a = inputs.get(0).type().get();
for (int i = 1; i < inputs.size(); ++i) {
OrderedTensorType b = inputs.get(i).type().get();
OrderedTensorType largest = largestInput(a, b);
OrderedTensorType smallest = smallestInput(a, b);
int sizeDifference = largest.rank() - smallest.rank();
for (int j = 0; j < smallest.rank(); ++j) {
String bDim = smallest.dimensions().get(j).name();
String aDim = largest.dimensions().get(j + sizeDifference).name();
renamer.addConstraint(aDim, bDim, DimensionRenamer.Constraint.equal(false), this);
}
a = b;
}
}
private OrderedTensorType largestInput(OrderedTensorType a, OrderedTensorType b) {
return a.rank() >= b.rank() ? a : b;
}
private OrderedTensorType smallestInput(OrderedTensorType a, OrderedTensorType b) {
return a.rank() < b.rank() ? a : b;
}
@Override
public ConcatReduce withInputs(List<IntermediateOperation> inputs) {
return new ConcatReduce(modelName(), name(), inputs, aggregator);
}
@Override
public String operationName() { return "ConcatReduce"; }
}
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