diff options
| author | Arne Juul <arnej@yahooinc.com> | 2023-03-22 14:18:15 +0000 |
|---|---|---|
| committer | Arne Juul <arnej@yahooinc.com> | 2023-03-22 14:18:15 +0000 |
| commit | de315c066a6dd0b78431230a5035fa519ebac601 (patch) | |
| tree | f986435917ca55ba9db95c7dfddd9dfef11fa9d8 /config-model/src/test/derived | |
| parent | 39ef03dbfea4665dbe06b187d8d9d19d65e6d660 (diff) | |
use ExpressionFunction.Instance for consistency
Diffstat (limited to 'config-model/src/test/derived')
| -rw-r--r-- | config-model/src/test/derived/globalphase_token_functions/rank-profiles.cfg | 10 |
1 files changed, 5 insertions, 5 deletions
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 be6ec0e3a51..fc2453f3aa9 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@3cbfb934).rankingScript" +rankprofile[].fef.property[].name "rankingExpression(__token_length@4d7c1b66085df918).rankingScript" rankprofile[].fef.property[].value "reduce(map(query(input), f(x)(x > 0)), sum)" -rankprofile[].fef.property[].name "rankingExpression(__token_length@cf90db10).rankingScript" +rankprofile[].fef.property[].name "rankingExpression(__token_length@a16087c578950aea).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@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[].value "tensor<float>(d0[1],d1[128])((if (d1 < 1.0, 101.0, if (d1 < 1.0 + rankingExpression(__token_length@4d7c1b66085df918), query(input){d0:(d1 - (1.0))}, if (d1 < (1.0 + rankingExpression(__token_length@4d7c1b66085df918) + 1.0), 102.0, if (d1 < (1.0 + rankingExpression(__token_length@4d7c1b66085df918) + 1.0 + rankingExpression(__token_length@a16087c578950aea)), attribute(tokens){d0:(d1 - (1.0 + rankingExpression(__token_length@4d7c1b66085df918) + 1.0))}, if (d1 < (1.0 + rankingExpression(__token_length@4d7c1b66085df918) + 1.0 + rankingExpression(__token_length@a16087c578950aea) + 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@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[].value "tensor<float>(d0[1],d1[128])((if (d1 < (1.0 + rankingExpression(__token_length@4d7c1b66085df918) + 1.0), 0.0, if (d1 < (1.0 + rankingExpression(__token_length@4d7c1b66085df918) + 1.0 + rankingExpression(__token_length@a16087c578950aea) + 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@3cbfb934) + 1.0 + rankingExpression(__token_length@cf90db10) + 1.0), 1.0, 0.0)))" +rankprofile[].fef.property[].value "tensor<float>(d0[1],d1[128])((if (d1 < (1.0 + rankingExpression(__token_length@4d7c1b66085df918) + 1.0 + rankingExpression(__token_length@a16087c578950aea) + 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" |