1 files changed, 23 insertions, 3 deletions
diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/TensorFlowFeatureConverter.java b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/TensorFlowFeatureConverter.java
index d05027dda39..a36384ce6f2 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/TensorFlowFeatureConverter.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/TensorFlowFeatureConverter.java
@@ -1,17 +1,22 @@
 package com.yahoo.searchdefinition.expressiontransforms;
 
 import com.google.common.base.Joiner;
+import com.yahoo.config.application.api.ApplicationPackage;
+import com.yahoo.searchdefinition.RankProfile;
+import com.yahoo.searchdefinition.RankingConstant;
 import com.yahoo.searchlib.rankingexpression.RankingExpression;
 import com.yahoo.searchlib.rankingexpression.evaluation.TensorValue;
-import com.yahoo.searchlib.rankingexpression.integration.tensorflow.TensorFlowModel;
 import com.yahoo.searchlib.rankingexpression.integration.tensorflow.TensorFlowImporter;
+import com.yahoo.searchlib.rankingexpression.integration.tensorflow.TensorFlowModel;
 import com.yahoo.searchlib.rankingexpression.rule.Arguments;
 import com.yahoo.searchlib.rankingexpression.rule.CompositeNode;
 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.transform.ExpressionTransformer;
+import com.yahoo.tensor.Tensor;
 
+import java.io.File;
 import java.util.HashMap;
 import java.util.Map;
 import java.util.Optional;
@@ -48,7 +53,7 @@ public class TensorFlowFeatureConverter extends ExpressionTransformer<RankProfil
                 throw new IllegalArgumentException("A tensorflow node must take an argument pointing to " +
                                                    "the tensorflow model directory under [application]/models");
 
-            String modelPath = asString(feature.getArguments().expressions().get(0));
+            String modelPath = ApplicationPackage.MODELS_DIR + "/" + asString(feature.getArguments().expressions().get(0));
             TensorFlowModel result = importedModels.computeIfAbsent(modelPath, k -> tensorFlowImporter.importModel(modelPath));
 
             // Find the specified expression
@@ -58,7 +63,10 @@ public class TensorFlowFeatureConverter extends ExpressionTransformer<RankProfil
                                                         optionalArgument(2, feature.getArguments()));
 
             // Add all constants (after finding outputs to fail faster when the output is not found)
-            result.constants().forEach((k, v) -> context.rankProfile().addConstantTensor(k, new TensorValue(v)));
+            if (1==1)
+                result.constants().forEach((k, v) -> context.rankProfile().addConstantTensor(k, new TensorValue(v)));
+            else // correct way, disabled for now
+                result.constants().forEach((k, v) -> transformConstant(modelPath, context.rankProfile(), k, v));
 
             return expression.getRoot();
         }
@@ -120,6 +128,18 @@ public class TensorFlowFeatureConverter extends ExpressionTransformer<RankProfil
         }
     }
 
+    private void transformConstant(String modelPath, RankProfile profile, String constantName, Tensor constantValue) {
+        File constantFilePath = new File(modelPath, "converted_variables");
+        if ( ! constantFilePath.exists() ) {
+            if ( ! constantFilePath.mkdir() )
+                throw new IllegalStateException("Could not create directory " + constantFilePath);
+        }
+
+        File constantFile = new File(constantFilePath, constantName + ".json");
+        // writeAsVespaTensor(constantValue, constantFile);
+        profile.getSearch().addRankingConstant(new RankingConstant(constantName, constantValue.type(), constantFilePath.getPath()));
+    }
+
     private String skippedOutputsDescription(TensorFlowModel.Signature signature) {
         if (signature.skippedOutputs().isEmpty()) return "";
         StringBuilder b = new StringBuilder(": ");