HashGNNConfig is not a proc config

So it should not be annotated or used directly in tests.
Instead, we use an actual config in tests (stream config).

Author: Mats-SX

algo/src/main/java/org/neo4j/gds/embeddings/hashgnn/HashGNNConfig.java

@@ -29,7 +29,6 @@
 import java.util.Map;
 import java.util.Optional;
 
-@Configuration
 interface HashGNNConfig extends AlgoBaseConfig, FeaturePropertiesConfig, RandomSeedConfig {
 
     @Configuration.IntegerRange(min = 1)

algo/src/test/java/org/neo4j/gds/embeddings/hashgnn/DensifyTaskTest.java

@@ -36,7 +36,7 @@ void shouldDensify() {
         var nodeCount = 3;
 
         var partition = new Partition(0, nodeCount);
-        var config = HashGNNConfigImpl
+        var config = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("f1", "f2"))
             .embeddingDensity(4)

algo/src/test/java/org/neo4j/gds/embeddings/hashgnn/GenerateFeaturesTaskTest.java

@@ -51,7 +51,7 @@ void shouldGenerateCorrectNumberOfFeatures() {
 
         var partition = new Partition(0, graph.nodeCount());
         var totalFeatureCount = new MutableLong(0);
-        var config = HashGNNConfigImpl
+        var config = HashGNNStreamConfigImpl
             .builder()
             .generateFeatures(Map.of("dimension", embeddingDimension, "densityLevel", densityLevel))
             .iterations(1337)

algo/src/test/java/org/neo4j/gds/embeddings/hashgnn/HashGNNConfigTest.java

@@ -31,7 +31,7 @@
 class HashGNNConfigTest {
     @Test
     void binarizationConfigCorrectType() {
-        var config = HashGNNConfigImpl
+        var config = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("x"))
             .binarizeFeatures(Map.of("dimension", 100))
@@ -44,7 +44,7 @@ void binarizationConfigCorrectType() {
     @Test
     void shouldNotAllowGeneratedAndFeatureProperties() {
         assertThatThrownBy(() -> {
-            HashGNNConfigImpl
+            HashGNNStreamConfigImpl
                 .builder()
                 .featureProperties(List.of("x"))
                 .generateFeatures(Map.of("dimension", 100, "densityLevel", 2))
@@ -57,7 +57,7 @@ void shouldNotAllowGeneratedAndFeatureProperties() {
     @Test
     void requiresFeaturePropertiesIfNoGeneratedFeatures() {
         assertThatThrownBy(() -> {
-            HashGNNConfigImpl
+            HashGNNStreamConfigImpl
                 .builder()
                 .embeddingDensity(4)
                 .iterations(100)
@@ -68,7 +68,7 @@ void requiresFeaturePropertiesIfNoGeneratedFeatures() {
     @Test
     void requiresDensityLevelAtMostDensity() {
         assertThatThrownBy(() -> {
-            HashGNNConfigImpl
+            HashGNNStreamConfigImpl
                 .builder()
                 .embeddingDensity(4)
                 .generateFeatures(Map.of("dimension", 4, "densityLevel", 5))
@@ -80,7 +80,7 @@ void requiresDensityLevelAtMostDensity() {
     @Test
     void failsOnInvalidBinarizationKeys() {
         assertThatThrownBy(() -> {
-            new HashGNNConfigImpl(CypherMapWrapper.create(
+            new HashGNNStreamConfigImpl(CypherMapWrapper.create(
                 Map.of(
                     "mutateProperty", "foo",
                     "featureProperties", List.of("x"),
@@ -97,7 +97,7 @@ void failsOnInvalidBinarizationKeys() {
     @Test
     void failsOnInvalidGenerateFeaturesKeys() {
         assertThatThrownBy(() -> {
-            new HashGNNConfigImpl(CypherMapWrapper.create(
+            new HashGNNStreamConfigImpl(CypherMapWrapper.create(
                 Map.of(
                     "generateFeatures", Map.of("dimension", 100, "densityElfen", 2),
                     "embeddingDensity", 4,

algo/src/test/java/org/neo4j/gds/embeddings/hashgnn/HashGNNTest.java

@@ -97,7 +97,7 @@ class HashGNNTest {
     @Test
     void binaryLowNeighborInfluence() {
         int embeddingDensity = 4;
-        var config = HashGNNConfigImpl
+        var config = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("f1", "f2"))
             .embeddingDensity(embeddingDensity)
@@ -114,7 +114,7 @@ void binaryLowNeighborInfluence() {
 
     @Test
     void binaryHighEmbeddingDensityHighNeighborInfluence() {
-        var config = HashGNNConfigImpl
+        var config = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("f1", "f2"))
             .embeddingDensity(200)
@@ -143,7 +143,7 @@ static Stream<Arguments> determinismParams() {
     @ParameterizedTest
     @MethodSource("determinismParams")
     void shouldBeDeterministic(int concurrency, boolean binarize, boolean dimReduce) {
-        var configBuilder = HashGNNConfigImpl
+        var configBuilder = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("f1", "f2"))
             .embeddingDensity(2)
@@ -177,7 +177,7 @@ void shouldRunOnDoublesAndBeDeterministicEqualNeighborInfluence() {
         // not all random seeds will give b a unique feature
         // this intends to test that if b has a unique feature before the first iteration, then it also has it after the first iteration
         // however we simulate what is before the first iteration by running with neighborInfluence 0
-        var configBuilder = HashGNNConfigImpl
+        var configBuilder = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("f1", "f2"))
             .embeddingDensity(embeddingDensity)
@@ -216,7 +216,7 @@ void shouldRunOnDoublesAndBeDeterministicHighNeighborInfluence() {
         int embeddingDensity = 100;
         int binarizationDimension = 8;
 
-        var configBuilder = HashGNNConfigImpl
+        var configBuilder = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("f1", "f2"))
             .embeddingDensity(embeddingDensity)
@@ -251,7 +251,7 @@ void shouldRunOnDoublesAndBeDeterministicHighNeighborInfluence() {
     void outputDimensionIsApplied() {
         int embeddingDensity = 200;
         double avgDegree = binaryGraph.relationshipCount() / (double) binaryGraph.nodeCount();
-        var config = HashGNNConfigImpl
+        var config = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("f1", "f2"))
             .embeddingDensity(embeddingDensity)
@@ -295,7 +295,7 @@ void shouldEstimateMemory(
         int concurrency,
         long expectedMemory
     ) {
-        var config = HashGNNConfigImpl
+        var config = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("f1", "f2"))
             .embeddingDensity(embeddingDensity)
@@ -318,7 +318,7 @@ void shouldLogProgress(boolean dense) {
 
         int embeddingDensity = 200;
         double avgDegree = g.relationshipCount() / (double) g.nodeCount();
-        var configBuilder = HashGNNConfigImpl
+        var configBuilder = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("f1", "f2"))
             .embeddingDensity(embeddingDensity)
@@ -414,7 +414,7 @@ void shouldBeDeterministicGivenSameOriginalIds() {
         var firstGraph = GraphFactory.create(firstIdMap, firstRelationships);
         var secondGraph = GraphFactory.create(secondIdMap, secondRelationships);
 
-        var config = HashGNNConfigImpl
+        var config = HashGNNStreamConfigImpl
             .builder()
             .embeddingDensity(8)
             .generateFeatures(Map.of("dimension", embeddingDimension, "densityLevel", 2))

algo/src/test/java/org/neo4j/gds/embeddings/hashgnn/HashTaskTest.java

@@ -36,7 +36,7 @@ void shouldHash() {
         int NUMBER_OF_RELATIONSHIPS = 3;
         int EMBEDDING_DIMENSION = 10;
 
-        var config = HashGNNConfigImpl
+        var config = HashGNNStreamConfigImpl
             .builder()
             .featureProperties(List.of("f1", "f2"))
             .iterations(ITERATIONS)