Refactor: macro -> function

3 files changed, 17 insertions, 17 deletions

diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java
index 2460e70bd8b..cba931e81f0 100644
--- a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java
+++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java
@@ -319,9 +319,9 @@ public class RankingExpressionWithTensorFlowTestCase {
     @Test
     public void testFunctionGeneration() {
         final String name = "mnist_saved";
-        final String expression = "join(join(reduce(join(join(join(imported_ml_macro_" + name + "_dnn_hidden2_add, reduce(constant(" + name + "_dnn_hidden2_Const), sum, d2), f(a,b)(a * b)), imported_ml_macro_" + name + "_dnn_hidden2_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(" + name + "_dnn_outputs_bias_read), f(a,b)(a + b)), tensor(d0[1])(1.0), f(a,b)(a * b))";
+        final String expression = "join(join(reduce(join(join(join(imported_ml_function_" + name + "_dnn_hidden2_add, reduce(constant(" + name + "_dnn_hidden2_Const), sum, d2), f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden2_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(" + name + "_dnn_outputs_bias_read), f(a,b)(a + b)), tensor(d0[1])(1.0), f(a,b)(a * b))";
         final String functionExpression1 = "join(reduce(join(reduce(rename(input, (d0, d1), (d0, d4)), sum, d0), constant(" + name + "_dnn_hidden1_weights_read), f(a,b)(a * b)), sum, d4), constant(" + name + "_dnn_hidden1_bias_read), f(a,b)(a + b))";
-        final String functionExpression2 = "join(reduce(join(join(join(imported_ml_macro_" + name + "_dnn_hidden1_add, 0.009999999776482582, f(a,b)(a * b)), imported_ml_macro_" + name + "_dnn_hidden1_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(" + name + "_dnn_hidden2_bias_read), f(a,b)(a + b))";
+        final String functionExpression2 = "join(reduce(join(join(join(imported_ml_function_" + name + "_dnn_hidden1_add, 0.009999999776482582, f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden1_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(" + name + "_dnn_hidden2_bias_read), f(a,b)(a + b))";
 
         RankProfileSearchFixture search = fixtureWith("tensor(d0[1],d1[784])(0.0)",
                                     "tensorflow('mnist/saved')",
@@ -330,8 +330,8 @@ public class RankingExpressionWithTensorFlowTestCase {
                                                       "input",
                                                       new StoringApplicationPackage(applicationDir));
         search.assertFirstPhaseExpression(expression, "my_profile");
-        search.assertFunction(functionExpression1, "imported_ml_macro_" + name + "_dnn_hidden1_add", "my_profile");
-        search.assertFunction(functionExpression2, "imported_ml_macro_" + name + "_dnn_hidden2_add", "my_profile");
+        search.assertFunction(functionExpression1, "imported_ml_function_" + name + "_dnn_hidden1_add", "my_profile");
+        search.assertFunction(functionExpression2, "imported_ml_function_" + name + "_dnn_hidden2_add", "my_profile");
     }
 
     @Test
@@ -349,9 +349,9 @@ public class RankingExpressionWithTensorFlowTestCase {
                 "  rank-profile my_profile_child inherits my_profile {\n" +
                 "  }";
 
-        final String expression = "join(join(reduce(join(join(join(imported_ml_macro_" + name + "_dnn_hidden2_add, reduce(constant(" + name + "_dnn_hidden2_Const), sum, d2), f(a,b)(a * b)), imported_ml_macro_" + name + "_dnn_hidden2_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(" + name + "_dnn_outputs_bias_read), f(a,b)(a + b)), tensor(d0[1])(1.0), f(a,b)(a * b))";
+        final String expression = "join(join(reduce(join(join(join(imported_ml_function_" + name + "_dnn_hidden2_add, reduce(constant(" + name + "_dnn_hidden2_Const), sum, d2), f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden2_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(" + name + "_dnn_outputs_bias_read), f(a,b)(a + b)), tensor(d0[1])(1.0), f(a,b)(a * b))";
         final String functionExpression1 = "join(reduce(join(reduce(rename(input, (d0, d1), (d0, d4)), sum, d0), constant(" + name + "_dnn_hidden1_weights_read), f(a,b)(a * b)), sum, d4), constant(" + name + "_dnn_hidden1_bias_read), f(a,b)(a + b))";
-        final String functionExpression2 = "join(reduce(join(join(join(imported_ml_macro_" + name + "_dnn_hidden1_add, 0.009999999776482582, f(a,b)(a * b)), imported_ml_macro_" + name + "_dnn_hidden1_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(" + name + "_dnn_hidden2_bias_read), f(a,b)(a + b))";
+        final String functionExpression2 = "join(reduce(join(join(join(imported_ml_function_" + name + "_dnn_hidden1_add, 0.009999999776482582, f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden1_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(" + name + "_dnn_hidden2_bias_read), f(a,b)(a + b))";
 
         RankProfileSearchFixture search = fixtureWithUncompiled(rankProfiles, new StoringApplicationPackage(applicationDir));
         search.compileRankProfile("my_profile", applicationDir.append("models"));
@@ -359,10 +359,10 @@ public class RankingExpressionWithTensorFlowTestCase {
         search.assertFirstPhaseExpression(expression, "my_profile");
         search.assertFirstPhaseExpression(expression, "my_profile_child");
         assertSmallConstant(name + "_dnn_hidden1_mul_x", TensorType.fromSpec("tensor()"), search);
-        search.assertFunction(functionExpression1, "imported_ml_macro_" + name + "_dnn_hidden1_add", "my_profile");
-        search.assertFunction(functionExpression1, "imported_ml_macro_" + name + "_dnn_hidden1_add", "my_profile_child");
-        search.assertFunction(functionExpression2, "imported_ml_macro_" + name + "_dnn_hidden2_add", "my_profile");
-        search.assertFunction(functionExpression2, "imported_ml_macro_" + name + "_dnn_hidden2_add", "my_profile_child");
+        search.assertFunction(functionExpression1, "imported_ml_function_" + name + "_dnn_hidden1_add", "my_profile");
+        search.assertFunction(functionExpression1, "imported_ml_function_" + name + "_dnn_hidden1_add", "my_profile_child");
+        search.assertFunction(functionExpression2, "imported_ml_function_" + name + "_dnn_hidden2_add", "my_profile");
+        search.assertFunction(functionExpression2, "imported_ml_function_" + name + "_dnn_hidden2_add", "my_profile_child");
 
         // At this point the expression is stored - copy application to another location which do not have a models dir
         Path storedApplicationDirectory = applicationDir.getParentPath().append("copy");
@@ -377,10 +377,10 @@ public class RankingExpressionWithTensorFlowTestCase {
             searchFromStored.assertFirstPhaseExpression(expression, "my_profile");
             searchFromStored.assertFirstPhaseExpression(expression, "my_profile_child");
             assertSmallConstant(name + "_dnn_hidden1_mul_x", TensorType.fromSpec("tensor()"), search);
-            searchFromStored.assertFunction(functionExpression1, "imported_ml_macro_" + name + "_dnn_hidden1_add", "my_profile");
-            searchFromStored.assertFunction(functionExpression1, "imported_ml_macro_" + name + "_dnn_hidden1_add", "my_profile_child");
-            searchFromStored.assertFunction(functionExpression2, "imported_ml_macro_" + name + "_dnn_hidden2_add", "my_profile");
-            searchFromStored.assertFunction(functionExpression2, "imported_ml_macro_" + name + "_dnn_hidden2_add", "my_profile_child");
+            searchFromStored.assertFunction(functionExpression1, "imported_ml_function_" + name + "_dnn_hidden1_add", "my_profile");
+            searchFromStored.assertFunction(functionExpression1, "imported_ml_function_" + name + "_dnn_hidden1_add", "my_profile_child");
+            searchFromStored.assertFunction(functionExpression2, "imported_ml_function_" + name + "_dnn_hidden2_add", "my_profile");
+            searchFromStored.assertFunction(functionExpression2, "imported_ml_function_" + name + "_dnn_hidden2_add", "my_profile_child");
         }
         finally {
             IOUtils.recursiveDeleteDir(storedApplicationDirectory.toFile());
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/integration/ml/importer/operations/IntermediateOperation.java b/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/integration/ml/importer/operations/IntermediateOperation.java
index da1445b885c..5daf5c69548 100644
--- a/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/integration/ml/importer/operations/IntermediateOperation.java
+++ b/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/integration/ml/importer/operations/IntermediateOperation.java
@@ -29,7 +29,7 @@ import java.util.function.Function;
  */
 public abstract class IntermediateOperation {
 
-    private final static String MACRO_PREFIX = "imported_ml_macro_";
+    private final static String FUNCTION_PREFIX = "imported_ml_function_";
 
     protected final String name;
     protected final String modelName;
@@ -132,7 +132,7 @@ public abstract class IntermediateOperation {
     public String vespaName(String name) { return name != null ? namePartOf(name).replace('/', '_') : null; }
 
     /** Retrieve the valid Vespa name of this node if it is a macro */
-    public String macroName() { return vespaName() != null ? MACRO_PREFIX + modelName + "_" + vespaName() : null; }
+    public String macroName() { return vespaName() != null ? FUNCTION_PREFIX + modelName + "_" + vespaName() : null; }
 
     /** Retrieve the list of warnings produced during its lifetime */
     public List<String> warnings() { return Collections.unmodifiableList(importWarnings); }
diff --git a/searchlib/src/test/java/com/yahoo/searchlib/rankingexpression/integration/ml/DropoutImportTestCase.java b/searchlib/src/test/java/com/yahoo/searchlib/rankingexpression/integration/ml/DropoutImportTestCase.java
index 1c73f97e929..f3cb93e929b 100644
--- a/searchlib/src/test/java/com/yahoo/searchlib/rankingexpression/integration/ml/DropoutImportTestCase.java
+++ b/searchlib/src/test/java/com/yahoo/searchlib/rankingexpression/integration/ml/DropoutImportTestCase.java
@@ -32,7 +32,7 @@ public class DropoutImportTestCase {
         RankingExpression output = signature.outputExpression("y");
         assertNotNull(output);
         assertEquals("outputs/Maximum", output.getName());
-        assertEquals("join(join(imported_ml_macro_test_outputs_BiasAdd, reduce(constant(test_outputs_Const), sum, d1), f(a,b)(a * b)), imported_ml_macro_test_outputs_BiasAdd, f(a,b)(max(a,b)))",
+        assertEquals("join(join(imported_ml_function_test_outputs_BiasAdd, reduce(constant(test_outputs_Const), sum, d1), f(a,b)(a * b)), imported_ml_function_test_outputs_BiasAdd, f(a,b)(max(a,b)))",
                 output.getRoot().toString());
         model.assertEqualResult("X", output.getName());
     }