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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.searchdefinition.expressiontransforms;
import com.yahoo.path.Path;
import com.yahoo.search.query.profile.QueryProfileRegistry;
import com.yahoo.searchdefinition.RankProfile;
import com.yahoo.searchlib.rankingexpression.integration.ml.ImportedModel;
import com.yahoo.searchlib.rankingexpression.integration.ml.TensorFlowImporter;
import com.yahoo.searchlib.rankingexpression.rule.Arguments;
import com.yahoo.searchlib.rankingexpression.rule.CompositeNode;
import com.yahoo.searchlib.rankingexpression.rule.ExpressionNode;
import com.yahoo.searchlib.rankingexpression.rule.ReferenceNode;
import java.io.UncheckedIOException;
import java.util.HashMap;
import java.util.Map;
/**
* Replaces instances of the tensorflow(model-path, signature, output)
* pseudofeature with the native Vespa ranking expression implementing
* the same computation.
*
* @author bratseth
*/
public class TensorFlowFeatureConverter extends MLImportFeatureConverter {
private final TensorFlowImporter tensorFlowImporter = new TensorFlowImporter();
/** A cache of imported models indexed by model path. This avoids importing the same model multiple times. */
private final Map<Path, ImportedModel> importedModels = new HashMap<>();
@Override
public ExpressionNode transform(ExpressionNode node, RankProfileTransformContext context) {
if (node instanceof ReferenceNode)
return transformFeature((ReferenceNode) node, context);
else if (node instanceof CompositeNode)
return super.transformChildren((CompositeNode) node, context);
else
return node;
}
private ExpressionNode transformFeature(ReferenceNode feature, RankProfileTransformContext context) {
if ( ! feature.getName().equals("tensorflow")) return feature;
try {
FeatureArguments arguments = new TensorFlowFeatureArguments(feature.getArguments());
ModelStore store = new ModelStore(context.rankProfile().getSearch().sourceApplication(), arguments);
if ( ! store.hasStoredModel()) // not converted yet - access TensorFlow model files
return transformFromTensorFlowModel(store, context.rankProfile(), context.queryProfiles());
else
return transformFromStoredModel(store, context.rankProfile());
}
catch (IllegalArgumentException | UncheckedIOException e) {
throw new IllegalArgumentException("Could not use tensorflow model from " + feature, e);
}
}
private ExpressionNode transformFromTensorFlowModel(ModelStore store,
RankProfile profile,
QueryProfileRegistry queryProfiles) {
ImportedModel model = importedModels.computeIfAbsent(store.arguments().modelPath(),
k -> tensorFlowImporter.importModel(store.arguments().modelName(),
store.modelDir()));
return transformFromImportedModel(model, store, profile, queryProfiles);
}
static class TensorFlowFeatureArguments extends FeatureArguments {
public TensorFlowFeatureArguments(Arguments arguments) {
if (arguments.isEmpty())
throw new IllegalArgumentException("A tensorflow node must take an argument pointing to " +
"the tensorflow model directory under [application]/models");
if (arguments.expressions().size() > 3)
throw new IllegalArgumentException("A tensorflow feature can have at most 3 arguments");
modelPath = Path.fromString(asString(arguments.expressions().get(0)));
signature = optionalArgument(1, arguments);
output = optionalArgument(2, arguments);
}
}
}
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