Send global constants

15 files changed, 133 insertions, 71 deletions

diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/RankingConstants.java b/config-model/src/main/java/com/yahoo/searchdefinition/RankingConstants.java
index 164cb7f808e..5ac1418c0c7 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/RankingConstants.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/RankingConstants.java
@@ -1,6 +1,11 @@
 // Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
 package com.yahoo.searchdefinition;
 
+import com.yahoo.config.FileReference;
+import com.yahoo.vespa.model.AbstractService;
+import com.yahoo.vespa.model.utils.FileSender;
+
+import java.util.Collection;
 import java.util.Collections;
 import java.util.HashMap;
 import java.util.Map;
@@ -33,4 +38,14 @@ public class RankingConstants {
         return Collections.unmodifiableMap(constants);
     }
 
+    /** Initiate sending of these constants to some services over file distribution */
+    public void sendTo(Collection<? extends AbstractService> services) {
+        for (RankingConstant constant : constants.values()) {
+            FileReference reference = (constant.getPathType() == RankingConstant.PathType.FILE)
+                                      ? FileSender.sendFileToServices(constant.getFileName(), services)
+                                      : FileSender.sendUriToServices(constant.getUri(), services);
+            constant.setFileReference(reference.value());
+        }
+    }
+
 }
diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/derived/RankProfileList.java b/config-model/src/main/java/com/yahoo/searchdefinition/derived/RankProfileList.java
index e58b3da4f72..fcbfb47c597 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/derived/RankProfileList.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/derived/RankProfileList.java
@@ -10,7 +10,9 @@ import com.yahoo.vespa.config.search.RankProfilesConfig;
 import com.yahoo.searchdefinition.RankProfile;
 import com.yahoo.searchdefinition.Search;
 import com.yahoo.vespa.config.search.core.RankingConstantsConfig;
+import com.yahoo.vespa.model.AbstractService;
 
+import java.util.Collection;
 import java.util.Map;
 import java.util.logging.Logger;
 
@@ -79,6 +81,10 @@ public class RankProfileList extends Derived implements RankProfilesConfig.Produ
         return rankProfiles.get(name);
     }
 
+    public void sendConstantsTo(Collection<? extends AbstractService> services) {
+        rankingConstants.sendTo(services);
+    }
+
     @Override
     public String getDerivedName() { return "rank-profiles"; }
 
diff --git a/config-model/src/main/java/com/yahoo/vespa/model/container/ContainerCluster.java b/config-model/src/main/java/com/yahoo/vespa/model/container/ContainerCluster.java
index 0b434fd0c49..fbe86d26b02 100755
--- a/config-model/src/main/java/com/yahoo/vespa/model/container/ContainerCluster.java
+++ b/config-model/src/main/java/com/yahoo/vespa/model/container/ContainerCluster.java
@@ -87,7 +87,6 @@ import java.util.Map;
 import java.util.Objects;
 import java.util.Optional;
 import java.util.Set;
-import java.util.function.Function;
 import java.util.stream.Collectors;
 import java.util.stream.Stream;
 
@@ -361,6 +360,7 @@ public final class ContainerCluster
 
     public void prepare() {
         addAndSendApplicationBundles();
+        rankProfileList.sendConstantsTo(containers);
         sendUserConfiguredFiles();
         setApplicationMetaData();
         for (RestApi restApi : restApiGroup.getComponents())
diff --git a/config-model/src/main/java/com/yahoo/vespa/model/container/search/searchchain/FederationSearcher.java b/config-model/src/main/java/com/yahoo/vespa/model/container/search/searchchain/FederationSearcher.java
index 19d014e0a1d..ceb48732116 100644
--- a/config-model/src/main/java/com/yahoo/vespa/model/container/search/searchchain/FederationSearcher.java
+++ b/config-model/src/main/java/com/yahoo/vespa/model/container/search/searchchain/FederationSearcher.java
@@ -15,6 +15,7 @@ import java.util.*;
 
 /**
  * Config producer for the FederationSearcher.
+ *
  * @author Tony Vaagenes
  */
 public class FederationSearcher extends Searcher<FederationSearcherModel> implements FederationConfig.Producer {
diff --git a/config-model/src/test/java/com/yahoo/config/model/ModelEvaluationTest.java b/config-model/src/test/java/com/yahoo/config/model/ModelEvaluationTest.java
index 91d7fd436f3..a16c32d47ab 100644
--- a/config-model/src/test/java/com/yahoo/config/model/ModelEvaluationTest.java
+++ b/config-model/src/test/java/com/yahoo/config/model/ModelEvaluationTest.java
@@ -70,31 +70,41 @@ public class ModelEvaluationTest {
         assertEquals(4, config.rankprofile().size());
         Set<String> modelNames = config.rankprofile().stream().map(v -> v.name()).collect(Collectors.toSet());
         assertTrue(modelNames.contains("xgboost_2_2"));
+        assertTrue(modelNames.contains("mnist_saved"));
         assertTrue(modelNames.contains("mnist_softmax"));
         assertTrue(modelNames.contains("mnist_softmax_saved"));
 
         ModelsEvaluator evaluator = new ModelsEvaluator(config, constantsConfig);
 
         assertEquals(4, evaluator.models().size());
+
         Model xgboost = evaluator.models().get("xgboost_2_2");
         assertNotNull(xgboost);
         assertNotNull(xgboost.evaluatorOf());
         assertNotNull(xgboost.evaluatorOf("xgboost_2_2"));
 
-        Model onnx = evaluator.models().get("mnist_softmax");
-        assertNotNull(onnx);
-        assertNotNull(onnx.evaluatorOf());
-        assertNotNull(onnx.evaluatorOf("default"));
-        assertNotNull(onnx.evaluatorOf("default", "add"));
-        assertNotNull(onnx.evaluatorOf("default.add"));
+        Model tensorflow_mnist = evaluator.models().get("mnist_saved");
+        assertNotNull(tensorflow_mnist);
+        assertNotNull(tensorflow_mnist.evaluatorOf("serving_default"));
+        assertNotNull(tensorflow_mnist.evaluatorOf("serving_default", "y"));
+        assertNotNull(tensorflow_mnist.evaluatorOf("serving_default.y"));
+        assertNotNull(evaluator.evaluatorOf("mnist_saved", "serving_default.y"));
+        assertNotNull(evaluator.evaluatorOf("mnist_saved", "serving_default", "y"));
+
+        Model onnx_mnist_softmax = evaluator.models().get("mnist_softmax");
+        assertNotNull(onnx_mnist_softmax);
+        assertNotNull(onnx_mnist_softmax.evaluatorOf());
+        assertNotNull(onnx_mnist_softmax.evaluatorOf("default"));
+        assertNotNull(onnx_mnist_softmax.evaluatorOf("default", "add"));
+        assertNotNull(onnx_mnist_softmax.evaluatorOf("default.add"));
         assertNotNull(evaluator.evaluatorOf("mnist_softmax", "default.add"));
         assertNotNull(evaluator.evaluatorOf("mnist_softmax", "default", "add"));
 
-        Model tensorflow = evaluator.models().get("mnist_softmax_saved");
-        assertNotNull(tensorflow);
-        assertNotNull(tensorflow.evaluatorOf());
-        assertNotNull(tensorflow.evaluatorOf("serving_default"));
-        assertNotNull(tensorflow.evaluatorOf("serving_default", "y"));
+        Model tensorflow_mnist_softmax = evaluator.models().get("mnist_softmax_saved");
+        assertNotNull(tensorflow_mnist_softmax);
+        assertNotNull(tensorflow_mnist_softmax.evaluatorOf());
+        assertNotNull(tensorflow_mnist_softmax.evaluatorOf("serving_default"));
+        assertNotNull(tensorflow_mnist_softmax.evaluatorOf("serving_default", "y"));
     }
 
 }
diff --git a/documentapi/src/main/java/com/yahoo/documentapi/messagebus/protocol/ANDPolicy.java b/documentapi/src/main/java/com/yahoo/documentapi/messagebus/protocol/ANDPolicy.java
index 7423792693b..dbf68106e07 100755
--- a/documentapi/src/main/java/com/yahoo/documentapi/messagebus/protocol/ANDPolicy.java
+++ b/documentapi/src/main/java/com/yahoo/documentapi/messagebus/protocol/ANDPolicy.java
@@ -20,7 +20,7 @@ import java.util.List;
 public class ANDPolicy implements DocumentProtocolRoutingPolicy {
 
     // A list of hops that are to always be selected when select() is invoked.
-    private final List<Hop> hops = new ArrayList<Hop>();
+    private final List<Hop> hops = new ArrayList<>();
 
     /**
      * Constructs a new AND policy that requires all recipients to be ok for it to merge their replies to an ok reply.
diff --git a/documentapi/src/main/java/com/yahoo/documentapi/messagebus/protocol/MessageTypePolicy.java b/documentapi/src/main/java/com/yahoo/documentapi/messagebus/protocol/MessageTypePolicy.java
index 82679e17990..a5b3accac68 100644
--- a/documentapi/src/main/java/com/yahoo/documentapi/messagebus/protocol/MessageTypePolicy.java
+++ b/documentapi/src/main/java/com/yahoo/documentapi/messagebus/protocol/MessageTypePolicy.java
@@ -51,7 +51,7 @@ public class MessageTypePolicy implements DocumentProtocolRoutingPolicy, ConfigS
 
     @Override
     public void configure(MessagetyperouteselectorpolicyConfig cfg) {
-        Map<Integer, Route> h = new HashMap<Integer, Route>();
+        Map<Integer, Route> h = new HashMap<>();
         for (MessagetyperouteselectorpolicyConfig.Route selector : cfg.route()) {
             h.put(selector.messagetype(), Route.parse(selector.name()));
         }
diff --git a/linguistics/src/main/java/com/yahoo/language/detect/Detection.java b/linguistics/src/main/java/com/yahoo/language/detect/Detection.java
index c08bdc14cfb..4b816335154 100644
--- a/linguistics/src/main/java/com/yahoo/language/detect/Detection.java
+++ b/linguistics/src/main/java/com/yahoo/language/detect/Detection.java
@@ -7,7 +7,7 @@ import java.nio.charset.Charset;
 import java.nio.charset.UnsupportedCharsetException;
 
 /**
- * @author <a href="mailto:einarmr@yahoo-inc.com">Einar M R Rosenvinge</a>
+ * @author Einar M R Rosenvinge
  */
 public class Detection {
 
diff --git a/linguistics/src/main/java/com/yahoo/language/opennlp/OpenNlpLinguistics.java b/linguistics/src/main/java/com/yahoo/language/opennlp/OpenNlpLinguistics.java
index 12de309a2d3..7451a7f2c9c 100644
--- a/linguistics/src/main/java/com/yahoo/language/opennlp/OpenNlpLinguistics.java
+++ b/linguistics/src/main/java/com/yahoo/language/opennlp/OpenNlpLinguistics.java
@@ -4,8 +4,10 @@ import com.yahoo.language.process.Tokenizer;
 import com.yahoo.language.simple.SimpleLinguistics;
 
 public class OpenNlpLinguistics extends SimpleLinguistics {
+
     @Override
     public Tokenizer getTokenizer() {
         return new OpenNlpTokenizer(getNormalizer(), getTransformer());
     }
+
 }
diff --git a/linguistics/src/main/java/com/yahoo/language/simple/SimpleDetector.java b/linguistics/src/main/java/com/yahoo/language/simple/SimpleDetector.java
index 2b31f95675b..f29ec691c60 100644
--- a/linguistics/src/main/java/com/yahoo/language/simple/SimpleDetector.java
+++ b/linguistics/src/main/java/com/yahoo/language/simple/SimpleDetector.java
@@ -37,6 +37,7 @@ import java.util.Locale;
  * @author bjorncs
  */
 public class SimpleDetector implements Detector {
+
     static private TextObjectFactory textObjectFactory;
     static private LanguageDetector languageDetector;
 
diff --git a/messagebus/src/main/java/com/yahoo/messagebus/routing/Hop.java b/messagebus/src/main/java/com/yahoo/messagebus/routing/Hop.java
index 63514eca6dd..e21aeef1ee2 100755
--- a/messagebus/src/main/java/com/yahoo/messagebus/routing/Hop.java
+++ b/messagebus/src/main/java/com/yahoo/messagebus/routing/Hop.java
@@ -20,15 +20,15 @@ public class Hop {
     private String cache = null;
 
     /**
-     * <p>Constructs an empty hop. You will need to add directives to the
-     * selector to make this usable.</p>
+     * Constructs an empty hop. You will need to add directives to the
+     * selector to make this usable.
      */
     public Hop() {
         // empty
     }
 
     /**
-     * <p>Implements the copy constructor.</p>
+     * Implements the copy constructor.
      *
      * @param hop The hop to copy.
      */
@@ -38,8 +38,8 @@ public class Hop {
     }
 
     /**
-     * <p>Constructs a fully populated hop. This is package private and used by
-     * the {@link HopBlueprint#create()} method.</p>
+     * Constructs a fully populated hop. This is package private and used by
+     * the {@link HopBlueprint#create()} method.
      *
      * @param selector     The selector to copy.
      * @param ignoreResult Whether or not to ignore the result of this hop.
@@ -50,8 +50,8 @@ public class Hop {
     }
 
     /**
-     * <p>Parses the given string as a single hop. The {@link #toString()}
-     * method is compatible with this parser.</p>
+     * Parses the given string as a single hop. The {@link #toString()}
+     * method is compatible with this parser.
      *
      * @param str The string to parse.
      * @return A hop that corresponds to the string.
@@ -65,8 +65,7 @@ public class Hop {
     }
 
     /**
-     * <p>Returns whether or not there are any directives contained in this
-     * hop.</p>
+     * Returns whether or not there are any directives contained in this hop.
      *
      * @return True if there is at least one directive.
      */
@@ -75,7 +74,7 @@ public class Hop {
     }
 
     /**
-     * <p>Returns the number of directives contained in this hop.</p>
+     * Returns the number of directives contained in this hop.
      *
      * @return The number of directives.
      */
@@ -84,7 +83,7 @@ public class Hop {
     }
 
     /**
-     * <p>Returns the directive at the given index.</p>
+     * Returns the directive at the given index.
      *
      * @param i The index of the directive to return.
      * @return The item.
@@ -94,7 +93,7 @@ public class Hop {
     }
 
     /**
-     * <p>Adds a new directive to this hop.</p>
+     * Adds a new directive to this hop.
      *
      * @param directive The directive to add.
      * @return This, to allow chaining.
@@ -106,7 +105,7 @@ public class Hop {
     }
 
     /**
-     * <p>Sets the directive at a given index.</p>
+     * Sets the directive at a given index.
      *
      * @param i         The index at which to set the directive.
      * @param directive The directive to set.
@@ -283,9 +282,10 @@ public class Hop {
 
     @Override
     public int hashCode() {
-        int result = selector != null ? selector.hashCode() : 0;
+        int result = selector.hashCode();
         result = 31 * result + (ignoreResult ? 1 : 0);
         result = 31 * result + (cache != null ? cache.hashCode() : 0);
         return result;
     }
+
 }
diff --git a/messagebus/src/main/java/com/yahoo/messagebus/routing/HopDirective.java b/messagebus/src/main/java/com/yahoo/messagebus/routing/HopDirective.java
index 809b2da69c4..838b11e7a02 100755
--- a/messagebus/src/main/java/com/yahoo/messagebus/routing/HopDirective.java
+++ b/messagebus/src/main/java/com/yahoo/messagebus/routing/HopDirective.java
@@ -14,13 +14,14 @@ public interface HopDirective {
      * @param dir The directive to compare this to.
      * @return True if this matches the argument.
      */
-    public boolean matches(HopDirective dir);
+    boolean matches(HopDirective dir);
 
     /**
      * Returns a string representation of this that can be debugged but not parsed.
      *
      * @return The debug string.
      */
-    public String toDebugString();
+    String toDebugString();
+
 }
 
diff --git a/messagebus/src/main/java/com/yahoo/messagebus/routing/Route.java b/messagebus/src/main/java/com/yahoo/messagebus/routing/Route.java
index a07c6e16100..9190b680ebf 100755
--- a/messagebus/src/main/java/com/yahoo/messagebus/routing/Route.java
+++ b/messagebus/src/main/java/com/yahoo/messagebus/routing/Route.java
@@ -20,7 +20,7 @@ import java.util.List;
  */
 public class Route {
 
-    private final List<Hop> hops = new ArrayList<Hop>();
+    private final List<Hop> hops = new ArrayList<>();
     private String cache = null;
 
     /**
diff --git a/model-evaluation/src/main/java/ai/vespa/models/evaluation/RankProfilesConfigImporter.java b/model-evaluation/src/main/java/ai/vespa/models/evaluation/RankProfilesConfigImporter.java
index b9e7a27c013..98c80ace047 100644
--- a/model-evaluation/src/main/java/ai/vespa/models/evaluation/RankProfilesConfigImporter.java
+++ b/model-evaluation/src/main/java/ai/vespa/models/evaluation/RankProfilesConfigImporter.java
@@ -26,6 +26,7 @@ import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
+import java.util.logging.Logger;
 
 /**
  * Converts RankProfilesConfig instances to RankingExpressions for evaluation.
@@ -35,19 +36,13 @@ import java.util.Optional;
  */
 class RankProfilesConfigImporter {
 
-    /**
-     * Constants already imported in this while reading some expression.
-     * This is to avoid re-reading constants referenced
-     * multiple places, as that is potentially costly.
-     */
-    private Map<String, Constant> globalImportedConstants = new HashMap<>();
+    private static final Logger log = Logger.getLogger("CONSTANTS");
 
     /**
      * Returns a map of the models contained in this config, indexed on name.
      * The map is modifiable and owned by the caller.
      */
     Map<String, Model> importFrom(RankProfilesConfig config, RankingConstantsConfig constantsConfig) {
-        globalImportedConstants.clear();
         try {
             Map<String, Model> models = new HashMap<>();
             for (RankProfilesConfig.Rankprofile profile : config.rankprofile()) {
@@ -61,7 +56,8 @@ class RankProfilesConfigImporter {
         }
     }
 
-    private Model importProfile(RankProfilesConfig.Rankprofile profile, RankingConstantsConfig constantsConfig) throws ParseException {
+    private Model importProfile(RankProfilesConfig.Rankprofile profile, RankingConstantsConfig constantsConfig)
+            throws ParseException {
         List<ExpressionFunction> functions = new ArrayList<>();
         Map<FunctionReference, ExpressionFunction> referencedFunctions = new HashMap<>();
         ExpressionFunction firstPhase = null;
@@ -79,7 +75,8 @@ class RankProfilesConfigImporter {
                     functions.add(new ExpressionFunction(reference.get().functionName(), arguments, expression)); //
 
                 // Make all functions, bound or not available under the name they are referenced by in expressions
-                referencedFunctions.put(reference.get(), new ExpressionFunction(reference.get().serialForm(), arguments, expression));
+                referencedFunctions.put(reference.get(),
+                                        new ExpressionFunction(reference.get().serialForm(), arguments, expression));
             }
             else if (property.name().equals("vespa.rank.firstphase")) { // Include in addition to macros
                 firstPhase = new ExpressionFunction("firstphase", new ArrayList<>(),
@@ -112,24 +109,29 @@ class RankProfilesConfigImporter {
 
     private List<Constant> readConstants(RankingConstantsConfig constantsConfig) {
         List<Constant> constants = new ArrayList<>();
+
         for (RankingConstantsConfig.Constant constantConfig : constantsConfig.constant()) {
             constants.add(new Constant(constantConfig.name(),
-                                       readTensorFromFile(TensorType.fromSpec(constantConfig.type()),
+                                       readTensorFromFile(constantConfig.name(),
+                                                          TensorType.fromSpec(constantConfig.type()),
                                                           constantConfig.fileref().value())));
         }
         return constants;
     }
 
-    private Tensor readTensorFromFile(TensorType type, String fileName) {
+    private Tensor readTensorFromFile(String name, TensorType type, String fileReference) {
         try {
-            if (fileName.endsWith(".tbf"))
-                return TypedBinaryFormat.decode(Optional.of(type),
-                                                GrowableByteBuffer.wrap(IOUtils.readFileBytes(new File(fileName))));
-            // TODO: Support json and json.lz4
-
-            if (fileName.isEmpty()) // this is the case in unit tests
+            if (fileReference.isEmpty()) { // this may be the case in unit tests
+                log.warning("Got empty file reference for constant '" + name + "', using an empty tensor");
                 return Tensor.from(type, "{}");
-            throw new IllegalArgumentException("Unknown tensor file format (determined by file ending): " + fileName);
+            }
+            if ( ! new File(fileReference).exists()) { // this may be the case in unit tests
+                log.warning("Got empty file reference for constant '" + name + "', using an empty tensor");
+                return Tensor.from(type, "{}");
+            }
+            return TypedBinaryFormat.decode(Optional.of(type),
+                                            GrowableByteBuffer.wrap(IOUtils.readFileBytes(new File(fileReference))));
+            // TODO: Support json and json.lz4
         }
         catch (IOException e) {
             throw new UncheckedIOException(e);
diff --git a/model-evaluation/src/test/java/ai/vespa/models/evaluation/RankProfilesImporterTest.java b/model-evaluation/src/test/java/ai/vespa/models/evaluation/RankProfilesImporterTest.java
index 84e01e58280..2cb9602dfa7 100644
--- a/model-evaluation/src/test/java/ai/vespa/models/evaluation/RankProfilesImporterTest.java
+++ b/model-evaluation/src/test/java/ai/vespa/models/evaluation/RankProfilesImporterTest.java
@@ -11,9 +11,11 @@ import org.junit.Test;
 
 import java.io.File;
 import java.util.Map;
+import java.util.stream.Collectors;
 
 import static org.junit.Assert.assertEquals;
 import static org.junit.Assert.assertNotNull;
+import static org.junit.Assert.assertTrue;
 
 /**
  * Tests instantiating models from rank-profiles configs.
@@ -28,27 +30,49 @@ public class RankProfilesImporterTest {
 
         assertEquals(4, models.size());
 
-        Model xgboost = models.get("xgboost_2_2");
-        assertFunction("xgboost_2_2",
-                       "(optimized sum of condition trees of size 192 bytes)",
-                       xgboost);
-
-        Model onnxMnistSoftmax = models.get("mnist_softmax");
-        assertFunction("default.add",
-                       "join(reduce(join(rename(Placeholder, (d0, d1), (d0, d2)), constant(mnist_softmax_Variable), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_Variable_1), f(a,b)(a + b))",
-                       onnxMnistSoftmax);
-        assertEquals("tensor(d1[10],d2[784])",
-                     onnxMnistSoftmax.evaluatorOf("default.add").context().get("constant(mnist_softmax_Variable)").type().toString());
-
-        Model tfMnistSoftmax = models.get("mnist_softmax_saved");
-        assertFunction("serving_default.y",
-                       "join(reduce(join(rename(Placeholder, (d0, d1), (d0, d2)), constant(mnist_softmax_saved_layer_Variable_read), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_saved_layer_Variable_1_read), f(a,b)(a + b))",
-                       tfMnistSoftmax);
-
-        Model tfMnist = models.get("mnist_saved");
-        assertFunction("serving_default.y",
-                       "join(reduce(join(map(join(reduce(join(join(join(rankingExpression(imported_ml_macro_mnist_saved_dnn_hidden1_add), 0.009999999776482582, f(a,b)(a * b)), rankingExpression(imported_ml_macro_mnist_saved_dnn_hidden1_add), f(a,b)(max(a,b))), constant(mnist_saved_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(mnist_saved_dnn_hidden2_bias_read), f(a,b)(a + b)), f(a)(1.050701 * if (a >= 0, a, 1.673263 * (exp(a) - 1)))), constant(mnist_saved_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(mnist_saved_dnn_outputs_bias_read), f(a,b)(a + b))",
-                       tfMnist);
+        // TODO: When we get type information in Models, replace the evaluator.context().names() check below by that
+        {
+            Model xgboost = models.get("xgboost_2_2");
+            assertFunction("xgboost_2_2",
+                           "(optimized sum of condition trees of size 192 bytes)",
+                           xgboost);
+            FunctionEvaluator evaluator = xgboost.evaluatorOf();
+            assertEquals("f109, f29, f56, f60", evaluator.context().names().stream().sorted().collect(Collectors.joining(", ")));
+        }
+
+        {
+
+            Model onnxMnistSoftmax = models.get("mnist_softmax");
+            assertFunction("default.add",
+                           "join(reduce(join(rename(Placeholder, (d0, d1), (d0, d2)), constant(mnist_softmax_Variable), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_Variable_1), f(a,b)(a + b))",
+                           onnxMnistSoftmax);
+            assertEquals("tensor(d1[10],d2[784])",
+                         onnxMnistSoftmax.evaluatorOf("default.add").context().get("constant(mnist_softmax_Variable)").type().toString());
+            FunctionEvaluator evaluator = onnxMnistSoftmax.evaluatorOf(); // Verify exactly one output available
+            assertEquals("Placeholder, constant(mnist_softmax_Variable), constant(mnist_softmax_Variable_1)", evaluator.context().names().stream().sorted().collect(Collectors.joining(", ")));
+        }
+
+        {
+            Model tfMnistSoftmax = models.get("mnist_softmax_saved");
+            assertFunction("serving_default.y",
+                           "join(reduce(join(rename(Placeholder, (d0, d1), (d0, d2)), constant(mnist_softmax_saved_layer_Variable_read), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_saved_layer_Variable_1_read), f(a,b)(a + b))",
+                           tfMnistSoftmax);
+            FunctionEvaluator evaluator = tfMnistSoftmax.evaluatorOf(); // Verify exactly one output available
+            assertEquals("Placeholder, constant(mnist_softmax_saved_layer_Variable_1_read), constant(mnist_softmax_saved_layer_Variable_read)", evaluator.context().names().stream().sorted().collect(Collectors.joining(", ")));
+        }
+
+        {
+            Model tfMnist = models.get("mnist_saved");
+            assertFunction("serving_default.y",
+                           "join(reduce(join(map(join(reduce(join(join(join(rankingExpression(imported_ml_macro_mnist_saved_dnn_hidden1_add), 0.009999999776482582, f(a,b)(a * b)), rankingExpression(imported_ml_macro_mnist_saved_dnn_hidden1_add), f(a,b)(max(a,b))), constant(mnist_saved_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(mnist_saved_dnn_hidden2_bias_read), f(a,b)(a + b)), f(a)(1.050701 * if (a >= 0, a, 1.673263 * (exp(a) - 1)))), constant(mnist_saved_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(mnist_saved_dnn_outputs_bias_read), f(a,b)(a + b))",
+                           tfMnist);
+            // Macro:
+            assertFunction("imported_ml_macro_mnist_saved_dnn_hidden1_add",
+                           "join(reduce(join(rename(input, (d0, d1), (d0, d4)), constant(mnist_saved_dnn_hidden1_weights_read), f(a,b)(a * b)), sum, d4), constant(mnist_saved_dnn_hidden1_bias_read), f(a,b)(a + b))",
+                           tfMnist);
+            FunctionEvaluator evaluator = tfMnist.evaluatorOf("serving_default"); // TODO: Macro is offered as an alternative output currently, so need to specify argument
+            assertEquals("constant(mnist_saved_dnn_hidden1_bias_read), constant(mnist_saved_dnn_hidden1_weights_read), constant(mnist_saved_dnn_hidden2_bias_read), constant(mnist_saved_dnn_hidden2_weights_read), constant(mnist_saved_dnn_outputs_bias_read), constant(mnist_saved_dnn_outputs_weights_read), input, rankingExpression(imported_ml_macro_mnist_saved_dnn_hidden1_add)", evaluator.context().names().stream().sorted().collect(Collectors.joining(", ")));
+        }
     }
 
     @Test