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// Copyright Yahoo. 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.searchlib.rankingexpression.evaluation.DoubleValue;
import com.yahoo.searchlib.rankingexpression.evaluation.Value;
import com.yahoo.searchlib.rankingexpression.rule.ConstantNode;
import com.yahoo.searchlib.rankingexpression.rule.ExpressionNode;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorType;
import com.yahoo.tensor.functions.Generate;
import com.yahoo.tensor.functions.TensorFunction;
import java.util.Iterator;
import java.util.List;
import java.util.Optional;
import static com.yahoo.searchlib.rankingexpression.rule.TensorFunctionNode.wrapScalar;
public class ConstantOfShape extends IntermediateOperation {
private final AttributeMap attributeMap;
private TensorType.Value valueTypeOfTensor = TensorType.Value.DOUBLE;
private double valueToFillWith = 0.0;
public ConstantOfShape(String modelName, String nodeName, List<IntermediateOperation> inputs, AttributeMap attributeMap) {
super(modelName, nodeName, inputs);
this.attributeMap = attributeMap;
Optional<Value> value = attributeMap.get("value");
if (value.isPresent()) {
Tensor t = value.get().asTensor();
valueTypeOfTensor = t.type().valueType();
valueToFillWith = t.valueIterator().next();
}
}
@Override
protected OrderedTensorType lazyGetType() {
if ( ! allInputTypesPresent(1)) return null;
IntermediateOperation input = inputs.get(0);
if (input.getConstantValue().isEmpty()) {
throw new IllegalArgumentException("ConstantOfShape: 'shape' input must be a constant.");
}
Tensor shape = input.getConstantValue().get().asTensor();
if (shape.type().dimensions().size() > 1) {
throw new IllegalArgumentException("ConstantOfShape: 'shape' input must be a tensor with 0 or 1 dimensions.");
}
OrderedTensorType.Builder builder = new OrderedTensorType.Builder(valueTypeOfTensor);
Iterator<Double> iter = shape.valueIterator();
for (int i = 0; iter.hasNext(); i++) {
builder.add(TensorType.Dimension.indexed(vespaName() + "_" + i, iter.next().longValue()));
}
return builder.build();
}
@Override
protected TensorFunction<Reference> lazyGetFunction() {
if ( ! allInputTypesPresent(1)) return null;
ExpressionNode valueExpr = new ConstantNode(new DoubleValue(valueToFillWith));
TensorFunction<Reference> function = Generate.bound(type.type(), wrapScalar(valueExpr));
return function;
}
@Override
public void addDimensionNameConstraints(DimensionRenamer renamer) {
addConstraintsFrom(type, renamer);
}
@Override
public ConstantOfShape withInputs(List<IntermediateOperation> inputs) {
return new ConstantOfShape(modelName(), name(), inputs, attributeMap);
}
@Override
public String operationName() { return "ConstantOfShape"; }
}
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