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// Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package com.yahoo.searchlib.rankingexpression.integration.tensorflow.importer.operations;
import com.yahoo.searchlib.rankingexpression.evaluation.BooleanValue;
import com.yahoo.searchlib.rankingexpression.evaluation.DoubleValue;
import com.yahoo.searchlib.rankingexpression.evaluation.TensorValue;
import com.yahoo.searchlib.rankingexpression.evaluation.Value;
import com.yahoo.searchlib.rankingexpression.integration.tensorflow.importer.DimensionRenamer;
import com.yahoo.searchlib.rankingexpression.integration.tensorflow.importer.OrderedTensorType;
import com.yahoo.searchlib.rankingexpression.integration.tensorflow.importer.TensorConverter;
import com.yahoo.searchlib.rankingexpression.rule.ConstantNode;
import com.yahoo.searchlib.rankingexpression.rule.ExpressionNode;
import com.yahoo.searchlib.rankingexpression.rule.ReferenceNode;
import com.yahoo.searchlib.rankingexpression.rule.TensorFunctionNode;
import com.yahoo.tensor.TensorType;
import com.yahoo.tensor.functions.TensorFunction;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.NodeDef;
import java.util.List;
import java.util.Optional;
public class Const extends TensorFlowOperation {
public Const(NodeDef node, List<TensorFlowOperation> inputs, int port) {
super(node, inputs, port);
setConstantValue(value());
}
@Override
protected OrderedTensorType lazyGetType() {
return OrderedTensorType.fromTensorFlowType(node, vespaName() + "_");
}
@Override
public Optional<TensorFunction> function() {
if (function == null) {
function = lazyGetFunction();
}
return Optional.ofNullable(function);
}
@Override
protected TensorFunction lazyGetFunction() {
ExpressionNode expressionNode;
if (type.type().rank() == 0 && getConstantValue().isPresent()) {
expressionNode = new ConstantNode(getConstantValue().get().asDoubleValue());
} else {
expressionNode = new ReferenceNode("constant(\"" + vespaName() + "\")");
}
return new TensorFunctionNode.TensorFunctionExpressionNode(expressionNode);
}
@Override
public void addDimensionNameConstraints(DimensionRenamer renamer) {
for (TensorType.Dimension dimension : type.type().dimensions()) {
renamer.addDimension(dimension.name());
}
}
@Override
public void renameDimensions(DimensionRenamer renamer) {
super.renameDimensions(renamer);
setConstantValue(value());
}
@Override
public boolean isConstant() {
return true;
}
private Value value() {
if (!node.getAttrMap().containsKey("value")) {
throw new IllegalArgumentException("Node '" + node.getName() + "' of type " +
"const has missing 'value' attribute");
}
AttrValue attrValue = node.getAttrMap().get("value");
if (attrValue.getValueCase() == AttrValue.ValueCase.TENSOR) {
return new TensorValue(TensorConverter.toVespaTensor(attrValue.getTensor(), type().get().type()));
}
if (attrValue.getValueCase() == AttrValue.ValueCase.B) {
return new BooleanValue(attrValue.getB());
}
if (attrValue.getValueCase() == AttrValue.ValueCase.I) {
return new DoubleValue(attrValue.getI());
}
if (attrValue.getValueCase() == AttrValue.ValueCase.F) {
return new DoubleValue(attrValue.getF());
}
throw new IllegalArgumentException("Requesting value of constant in " +
node.getName() + " but type is not recognized.");
}
}
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