Merge pull request #6847 from vespa-engine/bratseth/read-constants

Bratseth/read constants

11 files changed, 230 insertions, 144 deletions

diff --git a/config-lib/src/main/java/com/yahoo/config/PathNode.java b/config-lib/src/main/java/com/yahoo/config/PathNode.java
index b63dad4d1a7..9d73b5e23c2 100644
--- a/config-lib/src/main/java/com/yahoo/config/PathNode.java
+++ b/config-lib/src/main/java/com/yahoo/config/PathNode.java
@@ -14,7 +14,6 @@ import java.util.Map;
  * Represents a 'path' in a {@link ConfigInstance}, usually a filename.
  *
  * @author gjoranv
- * @since 5.1.30
  */
 public class PathNode extends LeafNode<Path> {
 
diff --git a/container-core/src/main/java/com/yahoo/container/core/BundleLoaderProperties.java b/container-core/src/main/java/com/yahoo/container/core/BundleLoaderProperties.java
index c94dc30fd6f..ee12c7d4c9f 100644
--- a/container-core/src/main/java/com/yahoo/container/core/BundleLoaderProperties.java
+++ b/container-core/src/main/java/com/yahoo/container/core/BundleLoaderProperties.java
@@ -3,12 +3,13 @@ package com.yahoo.container.core;
 
 /**
  * @author gjoranv
- * @since 5.46
  */
 public interface BundleLoaderProperties {
+
     // TODO: This should be removed. The prefix is used to separate the bundles in BundlesConfig
     // into those that are transferred with filedistribution and those that are preinstalled
     // on disk. Instead, the model should have put them in two different configs. I.e. create a new
     // config 'preinstalled-bundles.def'.
-    public static final String DISK_BUNDLE_PREFIX = "file:";
+    String DISK_BUNDLE_PREFIX = "file:";
+
 }
diff --git a/container-core/src/main/java/com/yahoo/container/core/config/BundleLoader.java b/container-core/src/main/java/com/yahoo/container/core/config/BundleLoader.java
index eceb41f9739..c0a68086212 100644
--- a/container-core/src/main/java/com/yahoo/container/core/config/BundleLoader.java
+++ b/container-core/src/main/java/com/yahoo/container/core/config/BundleLoader.java
@@ -95,7 +95,7 @@ public class BundleLoader {
         log.info("Installing bundle from disk with reference '" + reference.value() + "'");
 
         File file = new File(referenceFileName);
-        if (!file.exists()) {
+        if ( ! file.exists()) {
             throw new IllegalArgumentException("Reference '" + reference.value() + "' not found on disk.");
         }
 
diff --git a/docproc/src/main/java/com/yahoo/docproc/jdisc/messagebus/MbusRequestContext.java b/docproc/src/main/java/com/yahoo/docproc/jdisc/messagebus/MbusRequestContext.java
index 80f1f003412..0f3f3938701 100644
--- a/docproc/src/main/java/com/yahoo/docproc/jdisc/messagebus/MbusRequestContext.java
+++ b/docproc/src/main/java/com/yahoo/docproc/jdisc/messagebus/MbusRequestContext.java
@@ -34,7 +34,7 @@ import java.util.concurrent.atomic.AtomicBoolean;
 import java.util.logging.Logger;
 
 /**
- * @author <a href="mailto:einarmr@yahoo-inc.com">Einar M R Rosenvinge</a>
+ * @author Einar M R Rosenvinge
  */
 public class MbusRequestContext implements RequestContext, ResponseHandler {
 
diff --git a/jdisc_messagebus_service/src/main/java/com/yahoo/messagebus/jdisc/MbusServer.java b/jdisc_messagebus_service/src/main/java/com/yahoo/messagebus/jdisc/MbusServer.java
index d0f5de54b4f..bc3d1edda7c 100644
--- a/jdisc_messagebus_service/src/main/java/com/yahoo/messagebus/jdisc/MbusServer.java
+++ b/jdisc_messagebus_service/src/main/java/com/yahoo/messagebus/jdisc/MbusServer.java
@@ -32,7 +32,7 @@ public final class MbusServer extends AbstractResource implements ServerProvider
     private final ResourceReference sessionReference;
 
     @Inject
-    public MbusServer(final CurrentContainer container, final ServerSession session) {
+    public MbusServer(CurrentContainer container, ServerSession session) {
         this.container = container;
         this.session = session;
         uri = URI.create("mbus://localhost/" + session.name());
@@ -60,7 +60,7 @@ public final class MbusServer extends AbstractResource implements ServerProvider
     }
 
     @Override
-    public void handleMessage(final Message msg) {
+    public void handleMessage(Message msg) {
         if (!running.get()) {
             dispatchErrorReply(msg, ErrorCode.SESSION_BUSY, "Session temporarily closed.");
             return;
@@ -73,7 +73,7 @@ public final class MbusServer extends AbstractResource implements ServerProvider
         try {
             request = new MbusRequest(container, uri, msg);
             content = request.connect(new ServerResponseHandler(msg));
-        } catch (final RuntimeException e) {
+        } catch (RuntimeException e) {
             dispatchErrorReply(msg, ErrorCode.APP_FATAL_ERROR, e.toString());
         } finally {
             if (request != null) {
@@ -89,8 +89,8 @@ public final class MbusServer extends AbstractResource implements ServerProvider
         return session.connectionSpec();
     }
 
-    private void dispatchErrorReply(final Message msg, final int errCode, final String errMsg) {
-        final Reply reply = new EmptyReply();
+    private void dispatchErrorReply(Message msg, int errCode, String errMsg) {
+        Reply reply = new EmptyReply();
         reply.swapState(msg);
         reply.addError(new Error(errCode, errMsg));
         session.sendReply(reply);
@@ -100,20 +100,20 @@ public final class MbusServer extends AbstractResource implements ServerProvider
 
         final Message msg;
 
-        ServerResponseHandler(final Message msg) {
+        ServerResponseHandler(Message msg) {
             this.msg = msg;
         }
 
         @Override
-        public ContentChannel handleResponse(final Response response) {
-            final Reply reply;
+        public ContentChannel handleResponse(Response response) {
+            Reply reply;
             if (response instanceof MbusResponse) {
                 reply = ((MbusResponse)response).getReply();
             } else {
                 reply = new EmptyReply();
                 reply.swapState(msg);
             }
-            final Error err = StatusCodes.toMbusError(response.getStatus());
+            Error err = StatusCodes.toMbusError(response.getStatus());
             if (err != null) {
                 if (err.isFatal()) {
                     if (!reply.hasFatalErrors()) {
diff --git a/messagebus/src/main/java/com/yahoo/messagebus/Message.java b/messagebus/src/main/java/com/yahoo/messagebus/Message.java
index 22496487f61..43f5c8d2dfd 100644
--- a/messagebus/src/main/java/com/yahoo/messagebus/Message.java
+++ b/messagebus/src/main/java/com/yahoo/messagebus/Message.java
@@ -5,9 +5,9 @@ import com.yahoo.concurrent.SystemTimer;
 import com.yahoo.messagebus.routing.Route;
 
 /**
- * <p>A message is a child of Routable, it is not a reply, and it has a sequencing identifier. Furthermore, a message
+ * A message is a child of Routable, it is not a reply, and it has a sequencing identifier. Furthermore, a message
  * contains a retry counter that holds what retry the message is currently on. See the method comment {@link #getRetry}
- * for more information.</p>
+ * for more information.
  *
  * @author Simon Thoresen Hult
  */
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 98c80ace047..cd21a0a6813 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
@@ -15,6 +15,7 @@ import com.yahoo.tensor.TensorType;
 import com.yahoo.tensor.serialization.TypedBinaryFormat;
 import com.yahoo.vespa.config.search.RankProfilesConfig;
 import com.yahoo.vespa.config.search.core.RankingConstantsConfig;
+import com.yahoo.vespa.defaults.Defaults;
 
 import java.io.File;
 import java.io.IOException;
@@ -119,18 +120,31 @@ class RankProfilesConfigImporter {
         return constants;
     }
 
-    private Tensor readTensorFromFile(String name, TensorType type, String fileReference) {
+    Tensor readTensorFromFile(String name, TensorType type, String fileReference) {
         try {
+            // TODO: Only allow these two fallbacks in testing mode
             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, "{}");
             }
-            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");
+            File dir = new File(Defaults.getDefaults().underVespaHome("var/db/vespa/filedistribution"), fileReference);
+            if ( ! dir.exists()) { // this may be the case in unit tests
+                log.warning("Got reference to nonexisting file " + dir + "e 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: Move these 2 lines to FileReference
+
+            dir = new File(Defaults.getDefaults().underVespaHome("var/db/vespa/filedistribution"), fileReference);
+            File file = dir.listFiles()[0]; // directory contains one file having the original name
+
+            if (file.getName().endsWith(".tbf"))
+                return TypedBinaryFormat.decode(Optional.of(type),
+                                                GrowableByteBuffer.wrap(IOUtils.readFileBytes(file)));
+            else
+                throw new IllegalArgumentException("Constant files on other formats than .tbf are not supported, got " +
+                                                   file + " for constant " + name);
             // TODO: Support json and json.lz4
         }
         catch (IOException e) {
diff --git a/model-evaluation/src/test/java/ai/vespa/models/evaluation/MlModelsImportingTest.java b/model-evaluation/src/test/java/ai/vespa/models/evaluation/MlModelsImportingTest.java
new file mode 100644
index 00000000000..a823f16d727
--- /dev/null
+++ b/model-evaluation/src/test/java/ai/vespa/models/evaluation/MlModelsImportingTest.java
@@ -0,0 +1,82 @@
+// Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+package ai.vespa.models.evaluation;
+
+import com.yahoo.config.subscription.ConfigGetter;
+import com.yahoo.config.subscription.FileSource;
+import com.yahoo.path.Path;
+import com.yahoo.searchlib.rankingexpression.ExpressionFunction;
+import com.yahoo.tensor.Tensor;
+import com.yahoo.tensor.TensorType;
+import com.yahoo.vespa.config.search.RankProfilesConfig;
+import com.yahoo.vespa.config.search.core.RankingConstantsConfig;
+import org.junit.Test;
+
+import java.io.File;
+import java.util.HashMap;
+import java.util.Map;
+import java.util.logging.Logger;
+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.
+ *
+ * @author bratseth
+ */
+public class MlModelsImportingTest {
+
+    @Test
+    public void testImportingModels() {
+        ModelTester tester = new ModelTester("src/test/resources/config/models/");
+
+        assertEquals(4, tester.models().size());
+
+        // TODO: When we get type information in Models, replace the evaluator.context().names() check below by that
+        {
+            Model xgboost = tester.models().get("xgboost_2_2");
+            tester.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 = tester.models().get("mnist_softmax");
+            tester.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 = tester.models().get("mnist_softmax_saved");
+            tester.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 = tester.models().get("mnist_saved");
+            tester.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:
+            tester.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(", ")));
+        }
+    }
+
+}
diff --git a/model-evaluation/src/test/java/ai/vespa/models/evaluation/ModelTester.java b/model-evaluation/src/test/java/ai/vespa/models/evaluation/ModelTester.java
new file mode 100644
index 00000000000..63e17e37bde
--- /dev/null
+++ b/model-evaluation/src/test/java/ai/vespa/models/evaluation/ModelTester.java
@@ -0,0 +1,77 @@
+// Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+package ai.vespa.models.evaluation;
+
+import com.yahoo.config.subscription.ConfigGetter;
+import com.yahoo.config.subscription.FileSource;
+import com.yahoo.path.Path;
+import com.yahoo.searchlib.rankingexpression.ExpressionFunction;
+import com.yahoo.tensor.Tensor;
+import com.yahoo.tensor.TensorType;
+import com.yahoo.vespa.config.search.RankProfilesConfig;
+import com.yahoo.vespa.config.search.core.RankingConstantsConfig;
+
+import java.util.HashMap;
+import java.util.Map;
+import java.util.logging.Logger;
+
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertNotNull;
+
+/**
+ * Helper for testing model import and evaluation
+ *
+ * @author bratseth
+ */
+public class ModelTester {
+
+    private final Map<String, Model> models;
+
+    public ModelTester(String modelConfigDirectory) {
+        models = createModels(modelConfigDirectory);
+    }
+
+    public Map<String, Model> models() { return models; }
+
+    private static Map<String, Model> createModels(String path) {
+        Path configDir = Path.fromString(path);
+        RankProfilesConfig config = new ConfigGetter<>(new FileSource(configDir.append("rank-profiles.cfg").toFile()),
+                                                       RankProfilesConfig.class).getConfig("");
+        RankingConstantsConfig constantsConfig = new ConfigGetter<>(new FileSource(configDir.append("ranking-constants.cfg").toFile()),
+                                                                    RankingConstantsConfig.class).getConfig("");
+        return new RankProfilesConfigImporterWithMockedConstants().importFrom(config, constantsConfig);
+    }
+
+    public void assertFunction(String name, String expression, Model model) {
+        assertNotNull("Model is present in config", model);
+        ExpressionFunction function = model.function(name);
+        assertNotNull("Function '" + name + "' is in " + model, function);
+        assertEquals(name, function.getName());
+        assertEquals(expression, function.getBody().getRoot().toString());
+    }
+
+    public void assertBoundFunction(String name, String expression, Model model) {
+        ExpressionFunction function = model.referencedFunctions().get(FunctionReference.fromSerial(name).get());
+        assertNotNull("Function '" + name + "' is present", function);
+        assertEquals(name, function.getName());
+        assertEquals(expression, function.getBody().getRoot().toString());
+    }
+
+    /** Allows us to provide canned tensor constants during import since file distribution does not work in tests */
+    private static class RankProfilesConfigImporterWithMockedConstants extends RankProfilesConfigImporter {
+
+        private static final Logger log = Logger.getLogger(RankProfilesConfigImporterWithMockedConstants.class.getName());
+
+        Map<String, Tensor> constants = new HashMap<>();
+
+        @Override
+        Tensor readTensorFromFile(String name, TensorType type, String fileReference) {
+            if ( ! constants.containsKey(name)) {
+                log.warning("Missing a mocked tensor constant for '" + name + "': Returning an empty tensor");
+                return Tensor.from(type, "{}");
+            }
+            return constants.get(name);
+        }
+
+    }
+
+}
diff --git a/model-evaluation/src/test/java/ai/vespa/models/evaluation/RankProfileImportingTest.java b/model-evaluation/src/test/java/ai/vespa/models/evaluation/RankProfileImportingTest.java
new file mode 100644
index 00000000000..210ffb823b2
--- /dev/null
+++ b/model-evaluation/src/test/java/ai/vespa/models/evaluation/RankProfileImportingTest.java
@@ -0,0 +1,36 @@
+// Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+package ai.vespa.models.evaluation;
+
+import org.junit.Test;
+
+import java.util.Map;
+
+import static org.junit.Assert.assertEquals;
+
+/**
+ * @author bratseth
+ */
+public class RankProfileImportingTest {
+
+    @Test
+    public void testImportingRankExpressions() {
+        ModelTester tester = new ModelTester("src/test/resources/config/rankexpression/");
+
+        assertEquals(18, tester.models().size());
+
+        Model macros = tester.models().get("macros");
+        assertEquals("macros", macros.name());
+        assertEquals(4, macros.functions().size());
+        tester.assertFunction("fourtimessum", "4 * (var1 + var2)", macros);
+        tester.assertFunction("firstphase", "match + fieldMatch(title) + rankingExpression(myfeature)", macros);
+        tester.assertFunction("secondphase", "rankingExpression(fourtimessum@5cf279212355b980.67f1e87166cfef86)", macros);
+        tester.assertFunction("myfeature",
+                              "70 * fieldMatch(title).completeness * pow(0 - fieldMatch(title).earliness,2) + " +
+                              "30 * pow(0 - fieldMatch(description).earliness,2)",
+                              macros);
+        assertEquals(4, macros.referencedFunctions().size());
+        tester.assertBoundFunction("rankingExpression(fourtimessum@5cf279212355b980.67f1e87166cfef86)",
+                                   "4 * (match + rankBoost)", macros);
+    }
+
+}
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
deleted file mode 100644
index 2cb9602dfa7..00000000000
--- a/model-evaluation/src/test/java/ai/vespa/models/evaluation/RankProfilesImporterTest.java
+++ /dev/null
@@ -1,123 +0,0 @@
-// Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package ai.vespa.models.evaluation;
-
-import com.yahoo.config.subscription.ConfigGetter;
-import com.yahoo.config.subscription.FileSource;
-import com.yahoo.path.Path;
-import com.yahoo.searchlib.rankingexpression.ExpressionFunction;
-import com.yahoo.vespa.config.search.RankProfilesConfig;
-import com.yahoo.vespa.config.search.core.RankingConstantsConfig;
-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.
- *
- * @author bratseth
- */
-public class RankProfilesImporterTest {
-
-    @Test
-    public void testImportingModels() {
-        Map<String, Model> models = createModels("src/test/resources/config/models/");
-
-        assertEquals(4, models.size());
-
-        // 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
-    public void testImportingRankExpressions() {
-        Map<String, Model> models = createModels("src/test/resources/config/rankexpression/");
-
-        assertEquals(18, models.size());
-
-        Model macros = models.get("macros");
-        assertEquals("macros", macros.name());
-        assertEquals(4, macros.functions().size());
-        assertFunction("fourtimessum", "4 * (var1 + var2)", macros);
-        assertFunction("firstphase", "match + fieldMatch(title) + rankingExpression(myfeature)", macros);
-        assertFunction("secondphase", "rankingExpression(fourtimessum@5cf279212355b980.67f1e87166cfef86)", macros);
-        assertFunction("myfeature",
-                       "70 * fieldMatch(title).completeness * pow(0 - fieldMatch(title).earliness,2) + " +
-                       "30 * pow(0 - fieldMatch(description).earliness,2)",
-                       macros);
-        assertEquals(4, macros.referencedFunctions().size());
-        assertBoundFunction("rankingExpression(fourtimessum@5cf279212355b980.67f1e87166cfef86)",
-                            "4 * (match + rankBoost)", macros);
-    }
-
-    private void assertFunction(String name, String expression, Model model) {
-        assertNotNull("Model is present in config", model);
-        ExpressionFunction function = model.function(name);
-        assertNotNull("Function '" + name + "' is in " + model, function);
-        assertEquals(name, function.getName());
-        assertEquals(expression, function.getBody().getRoot().toString());
-    }
-
-    private void assertBoundFunction(String name, String expression, Model model) {
-        ExpressionFunction function = model.referencedFunctions().get(FunctionReference.fromSerial(name).get());
-        assertNotNull("Function '" + name + "' is present", function);
-        assertEquals(name, function.getName());
-        assertEquals(expression, function.getBody().getRoot().toString());
-    }
-
-    private Map<String, Model> createModels(String path) {
-        Path configDir = Path.fromString(path);
-        RankProfilesConfig config = new ConfigGetter<>(new FileSource(configDir.append("rank-profiles.cfg").toFile()),
-                                                       RankProfilesConfig.class).getConfig("");
-        RankingConstantsConfig constantsConfig = new ConfigGetter<>(new FileSource(configDir.append("ranking-constants.cfg").toFile()),
-                                                                    RankingConstantsConfig.class).getConfig("");
-        return new RankProfilesConfigImporter().importFrom(config, constantsConfig);
-    }
-
-}