use Integer.toHexString on hashcode

3 files changed, 7 insertions, 7 deletions

diff --git a/config-model/src/main/java/com/yahoo/schema/expressiontransforms/TokenTransformer.java b/config-model/src/main/java/com/yahoo/schema/expressiontransforms/TokenTransformer.java
index de12de9b747..83ae6048051 100644
--- a/config-model/src/main/java/com/yahoo/schema/expressiontransforms/TokenTransformer.java
+++ b/config-model/src/main/java/com/yahoo/schema/expressiontransforms/TokenTransformer.java
@@ -208,7 +208,7 @@ public class TokenTransformer extends ExpressionTransformer<RankProfileTransform
     }
 
     private String lengthFunctionName(ReferenceNode arg) {
-        return "__token_length@" + arg.hashCode();
+        return "__token_length@" + Integer.toHexString(arg.hashCode());
     }
 
     private List<ExpressionNode> createTokenSequence(ReferenceNode feature) {
diff --git a/config-model/src/test/derived/globalphase_token_functions/rank-profiles.cfg b/config-model/src/test/derived/globalphase_token_functions/rank-profiles.cfg
index bf47dba9a71..be6ec0e3a51 100644
--- a/config-model/src/test/derived/globalphase_token_functions/rank-profiles.cfg
+++ b/config-model/src/test/derived/globalphase_token_functions/rank-profiles.cfg
@@ -13,20 +13,20 @@ rankprofile[].fef.property[].value "true"
 rankprofile[].fef.property[].name "vespa.type.attribute.tokens"
 rankprofile[].fef.property[].value "tensor(d0[128])"
 rankprofile[].name "using_model"
-rankprofile[].fef.property[].name "rankingExpression(__token_length@1019197748).rankingScript"
+rankprofile[].fef.property[].name "rankingExpression(__token_length@3cbfb934).rankingScript"
 rankprofile[].fef.property[].value "reduce(map(query(input), f(x)(x > 0)), sum)"
-rankprofile[].fef.property[].name "rankingExpression(__token_length@-812590320).rankingScript"
+rankprofile[].fef.property[].name "rankingExpression(__token_length@cf90db10).rankingScript"
 rankprofile[].fef.property[].value "reduce(map(attribute(tokens), f(x)(x > 0)), sum)"
 rankprofile[].fef.property[].name "rankingExpression(input_ids).rankingScript"
-rankprofile[].fef.property[].value "tensor<float>(d0[1],d1[128])((if (d1 < 1.0, 101.0, if (d1 < 1.0 + rankingExpression(__token_length@1019197748), query(input){d0:(d1 - (1.0))}, if (d1 < (1.0 + rankingExpression(__token_length@1019197748) + 1.0), 102.0, if (d1 < (1.0 + rankingExpression(__token_length@1019197748) + 1.0 + rankingExpression(__token_length@-812590320)), attribute(tokens){d0:(d1 - (1.0 + rankingExpression(__token_length@1019197748) + 1.0))}, if (d1 < (1.0 + rankingExpression(__token_length@1019197748) + 1.0 + rankingExpression(__token_length@-812590320) + 1.0), 102.0, 0.0)))))))"
+rankprofile[].fef.property[].value "tensor<float>(d0[1],d1[128])((if (d1 < 1.0, 101.0, if (d1 < 1.0 + rankingExpression(__token_length@3cbfb934), query(input){d0:(d1 - (1.0))}, if (d1 < (1.0 + rankingExpression(__token_length@3cbfb934) + 1.0), 102.0, if (d1 < (1.0 + rankingExpression(__token_length@3cbfb934) + 1.0 + rankingExpression(__token_length@cf90db10)), attribute(tokens){d0:(d1 - (1.0 + rankingExpression(__token_length@3cbfb934) + 1.0))}, if (d1 < (1.0 + rankingExpression(__token_length@3cbfb934) + 1.0 + rankingExpression(__token_length@cf90db10) + 1.0), 102.0, 0.0)))))))"
 rankprofile[].fef.property[].name "rankingExpression(input_ids).type"
 rankprofile[].fef.property[].value "tensor<float>(d0[1],d1[128])"
 rankprofile[].fef.property[].name "rankingExpression(token_type_ids).rankingScript"
-rankprofile[].fef.property[].value "tensor<float>(d0[1],d1[128])((if (d1 < (1.0 + rankingExpression(__token_length@1019197748) + 1.0), 0.0, if (d1 < (1.0 + rankingExpression(__token_length@1019197748) + 1.0 + rankingExpression(__token_length@-812590320) + 1.0), 1.0, 0.0))))"
+rankprofile[].fef.property[].value "tensor<float>(d0[1],d1[128])((if (d1 < (1.0 + rankingExpression(__token_length@3cbfb934) + 1.0), 0.0, if (d1 < (1.0 + rankingExpression(__token_length@3cbfb934) + 1.0 + rankingExpression(__token_length@cf90db10) + 1.0), 1.0, 0.0))))"
 rankprofile[].fef.property[].name "rankingExpression(token_type_ids).type"
 rankprofile[].fef.property[].value "tensor<float>(d0[1],d1[128])"
 rankprofile[].fef.property[].name "rankingExpression(attention_mask).rankingScript"
-rankprofile[].fef.property[].value "tensor<float>(d0[1],d1[128])((if (d1 < (1.0 + rankingExpression(__token_length@1019197748) + 1.0 + rankingExpression(__token_length@-812590320) + 1.0), 1.0, 0.0)))"
+rankprofile[].fef.property[].value "tensor<float>(d0[1],d1[128])((if (d1 < (1.0 + rankingExpression(__token_length@3cbfb934) + 1.0 + rankingExpression(__token_length@cf90db10) + 1.0), 1.0, 0.0)))"
 rankprofile[].fef.property[].name "rankingExpression(attention_mask).type"
 rankprofile[].fef.property[].value "tensor<float>(d0[1],d1[128])"
 rankprofile[].fef.property[].name "vespa.rank.globalphase"
diff --git a/config-model/src/test/java/com/yahoo/schema/processing/RankingExpressionWithOnnxModelTestCase.java b/config-model/src/test/java/com/yahoo/schema/processing/RankingExpressionWithOnnxModelTestCase.java
index e9b674a8c87..69c68124908 100644
--- a/config-model/src/test/java/com/yahoo/schema/processing/RankingExpressionWithOnnxModelTestCase.java
+++ b/config-model/src/test/java/com/yahoo/schema/processing/RankingExpressionWithOnnxModelTestCase.java
@@ -171,7 +171,7 @@ public class RankingExpressionWithOnnxModelTestCase {
 
         assertEquals("test_dynamic_model_with_transformer_tokens", config.rankprofile(7).name());
         assertEquals("rankingExpression(my_function).rankingScript", config.rankprofile(7).fef().property(1).name());
-        assertEquals("tensor<float>(d0[1],d1[10])((if (d1 < (1.0 + rankingExpression(__token_length@-1993461420) + 1.0), 0.0, if (d1 < (1.0 + rankingExpression(__token_length@-1993461420) + 1.0 + rankingExpression(__token_length@-1993461420) + 1.0), 1.0, 0.0))))", config.rankprofile(7).fef().property(1).value());
+        assertEquals("tensor<float>(d0[1],d1[10])((if (d1 < (1.0 + rankingExpression(__token_length@892e3154) + 1.0), 0.0, if (d1 < (1.0 + rankingExpression(__token_length@892e3154) + 1.0 + rankingExpression(__token_length@892e3154) + 1.0), 1.0, 0.0))))", config.rankprofile(7).fef().property(1).value());
 
         assertEquals("test_unbound_model", config.rankprofile(8).name());
         assertEquals("rankingExpression(my_function).rankingScript", config.rankprofile(8).fef().property(0).name());