diff options
Diffstat (limited to 'config-model')
5 files changed, 83 insertions, 44 deletions
diff --git a/config-model/src/main/javacc/SchemaParser.jj b/config-model/src/main/javacc/SchemaParser.jj index 421894e51cd..86a623071b5 100644 --- a/config-model/src/main/javacc/SchemaParser.jj +++ b/config-model/src/main/javacc/SchemaParser.jj @@ -1667,15 +1667,15 @@ void indexBody(ParsedIndex index) : double threshold; } { - ( <PREFIX> { index.setPrefix(true); } - | <ALIAS> <COLON> str = identifierWithDash() { index.addAlias(str); } - | <STEMMING> <COLON> str = identifierWithDash() { index.setStemming(Stemming.get(str)); } - | <ARITY> <COLON> arity = integer() { index.setArity(arity); } - | <LOWERBOUND> <COLON> num = consumeLong() { index.setLowerBound(num); } - | <UPPERBOUND> <COLON> num = consumeLong() { index.setUpperBound(num); } - | <DENSEPOSTINGLISTTHRESHOLD> <COLON> threshold = consumeFloat() { index.setDensePostingListThreshold(threshold); } - | <ENABLE_BM25> { index.setEnableBm25(true); } - | hnswIndex(index) { } + ( <PREFIX> { index.setPrefix(true); } + | <ALIAS> <COLON> str = identifierWithDash() { index.addAlias(str); } + | <STEMMING> <COLON> str = identifierWithDash() { index.setStemming(Stemming.get(str)); } + | <ARITY> <COLON> arity = integer() { index.setArity(arity); } + | <LOWERBOUND> <COLON> num = longValue() { index.setLowerBound(num); } + | <UPPERBOUND> <COLON> num = longValue() { index.setUpperBound(num); } + | <DENSEPOSTINGLISTTHRESHOLD> <COLON> threshold = floatValue() { index.setDensePostingListThreshold(threshold); } + | <ENABLE_BM25> { index.setEnableBm25(true); } + | hnswIndex(index) { } ) } @@ -1793,6 +1793,7 @@ String fileItem() : { (<FILE> <COLON> ( <FILE_PATH> | <STRING> | <IDENTIFIER>) { path = com.yahoo.path.Path.fromString(token.image).getRelative(); } { } (<NL>)*) { return path; } } + String uriItem() : { String path; @@ -1905,7 +1906,7 @@ String mutate_expr() : Number constant = null; } { - (("+=" | "-=" | "=") { op = token.image; } constant = consumeNumber()) + (("+=" | "-=" | "=") { op = token.image; } constant = number()) { return constant != null ? (op + constant) : op; } } @@ -1977,9 +1978,9 @@ void matchPhaseItem(MatchPhaseSettings settings) : | <ORDER> <COLON> ( <ASCENDING> { settings.setAscending(true); } | <DESCENDING> { settings.setAscending(false); } ) | <MAXHITS> <COLON> num = integer() { settings.setMaxHits(num); } - | <MAXFILTERCOVERAGE> <COLON> coverage = consumeFloat() { settings.setMaxFilterCoverage(coverage); } - | <EVALUATION_POINT> <COLON> multiplier = consumeFloat() { settings.setEvaluationPoint(multiplier); } - | <PRE_POST_FILTER_TIPPING_POINT> <COLON> multiplier = consumeFloat() { settings.setPrePostFilterTippingPoint(multiplier); } + | <MAXFILTERCOVERAGE> <COLON> coverage = floatValue() { settings.setMaxFilterCoverage(coverage); } + | <EVALUATION_POINT> <COLON> multiplier = floatValue() { settings.setEvaluationPoint(multiplier); } + | <PRE_POST_FILTER_TIPPING_POINT> <COLON> multiplier = floatValue() { settings.setPrePostFilterTippingPoint(multiplier); } ) } @@ -2008,7 +2009,7 @@ void diversityItem(DiversitySettings settings) : { ( <ATTRIBUTE> <COLON> str = identifier() { settings.setAttribute(str); } | <MIN_GROUPS> <COLON> num = integer() { settings.setMinGroups(num); } - | <CUTOFF_FACTOR> <COLON> multiplier = consumeFloat() { settings.setCutoffFactor(multiplier); } + | <CUTOFF_FACTOR> <COLON> multiplier = floatValue() { settings.setCutoffFactor(multiplier); } | <CUTOFF_STRATEGY> <COLON> ( <STRICT> { settings.setCutoffStrategy(Diversity.CutoffStrategy.strict); } | <LOOSE> { settings.setCutoffStrategy(Diversity.CutoffStrategy.loose); } @@ -2038,9 +2039,9 @@ void firstPhaseItem(ParsedRankProfile profile) : double dropLimit; } { - ( expression = expression() { profile.setFirstPhaseRanking(expression); } - | (<KEEPRANKCOUNT> <COLON> keepRankCount = integer()) { profile.setKeepRankCount(keepRankCount); } - | (<RANKSCOREDROPLIMIT> <COLON> dropLimit = consumeFloat()) { profile.setRankScoreDropLimit(dropLimit); } + ( expression = expression() { profile.setFirstPhaseRanking(expression); } + | (<KEEPRANKCOUNT> <COLON> keepRankCount = integer()) { profile.setKeepRankCount(keepRankCount); } + | (<RANKSCOREDROPLIMIT> <COLON> dropLimit = floatValue()) { profile.setRankScoreDropLimit(dropLimit); } ) } @@ -2254,7 +2255,7 @@ void termwiseLimit(ParsedRankProfile profile) : double num; } { - (<TERMWISELIMIT> <COLON> num = consumeFloat()) { profile.setTermwiseLimit(num); } + (<TERMWISELIMIT> <COLON> num = floatValue()) { profile.setTermwiseLimit(num); } } /** @@ -2267,7 +2268,7 @@ void postFilterThreshold(ParsedRankProfile profile) : double threshold; } { - (<POSTFILTERTHRESHOLD> <COLON> threshold = consumeFloat()) { profile.setPostFilterThreshold(threshold); } + (<POSTFILTERTHRESHOLD> <COLON> threshold = floatValue()) { profile.setPostFilterThreshold(threshold); } } /** @@ -2280,7 +2281,7 @@ void approximateThreshold(ParsedRankProfile profile) : double threshold; } { - (<APPROXIMATETHRESHOLD> <COLON> threshold = consumeFloat()) { profile.setApproximateThreshold(threshold); } + (<APPROXIMATETHRESHOLD> <COLON> threshold = floatValue()) { profile.setApproximateThreshold(threshold); } } /** @@ -2381,7 +2382,7 @@ void rankDegradationBinSize() : double freq; } { - <RPBINSIZE> <COLON> freq = consumeFloat() + <RPBINSIZE> <COLON> freq = floatValue() { deployLogger.logApplicationPackage(Level.WARNING, "Specifying 'doc-frequency' in 'rank-degradation' is deprecated and has no effect."); } } @@ -2406,7 +2407,7 @@ void rankDegradationPosbinSize() : double avgOcc; } { - <RPPOSBINSIZE> <COLON> avgOcc = consumeFloat() + <RPPOSBINSIZE> <COLON> avgOcc = floatValue() { deployLogger.logApplicationPackage(Level.WARNING, "Specifying 'occurrences-per-doc' in 'rank-degradation' is deprecated and has no effect."); } } @@ -2429,7 +2430,7 @@ void rankDegradation() : double freq; } { - ( <RANKDEGRADATIONFREQ> <COLON> freq = consumeFloat() + ( <RANKDEGRADATIONFREQ> <COLON> freq = floatValue() { deployLogger.logApplicationPackage(Level.WARNING, "Specifying 'rank-degradation-frequency' in 'rank-profile' is deprecated and has no effect."); } | <RANKDEGRADATION> lbrace() ( rankDegradationItem() (<NL>)*)+ <RBRACE> ) @@ -2526,7 +2527,7 @@ Tensor tensorValue(TensorType type) : Number doubleValue = null; } { - ( mappedTensorValue(builder) | indexedTensorValues(builder) | doubleValue = consumeNumber() ) + ( mappedTensorValue(builder) | indexedTensorValues(builder) | doubleValue = number() ) { if (doubleValue != null) { if (type.rank() > 0) @@ -2540,7 +2541,10 @@ Tensor tensorValue(TensorType type) : /** A mapped or mixed tensor value. */ void mappedTensorValue(Tensor.Builder builder) : {} { - "{" ( mappedTensorBlock(builder) )* ( <COMMA> (<NL>)* mappedTensorBlock(builder) )* "}" + "{" + ( mappedTensorBlock(builder) )* + ( <COMMA> (<NL>)* mappedTensorBlock(builder) )* + "}" } @@ -2549,11 +2553,11 @@ void mappedTensorBlock(Tensor.Builder builder) : TensorAddress mappedAddress; } { - mappedAddress = tensorAddress(builder.type().mappedSubtype()) <COLON> (<NL>)* + mappedAddress = tensorAddress(builder.type()) <COLON> (<NL>)* ( mappedTensorCellValue(mappedAddress, builder) | indexedTensorBlockValues(mappedAddress, builder) ) } -void indexedTensorBlockValues(TensorAddress sparseAddress, Tensor.Builder builder) : +void indexedTensorBlockValues(TensorAddress mappedAddress, Tensor.Builder builder) : { List<Double> values = new ArrayList<Double>(); } @@ -2565,7 +2569,7 @@ void indexedTensorBlockValues(TensorAddress sparseAddress, Tensor.Builder builde for (int i = 0; i < values.size(); i++ ) { arrayValues[i] = values.get(i); } - boundBuilder.block(sparseAddress, arrayValues); + boundBuilder.block(mappedAddress, arrayValues); } } @@ -2598,7 +2602,7 @@ void indexedTensorValue(List<Double> values) : Number value; } { - value = consumeNumber() + value = number() { values.add(value.doubleValue()); } } @@ -2613,7 +2617,7 @@ void mappedTensorCellValue(TensorAddress address, Tensor.Builder builder) : TensorAddress tensorAddress(TensorType type) : { - TensorAddress.Builder builder = new TensorAddress.Builder(type); + TensorAddress.Builder builder = new TensorAddress.PartialBuilder(type); String label; } { @@ -2649,7 +2653,7 @@ double tensorCellValue() : Number value; } { - value = consumeNumber() + value = number() { return value.doubleValue(); } } @@ -2922,7 +2926,7 @@ int integer() : { } } /** Consumes a long or integer token and returns its numeric value. */ -long consumeLong() : { } +long longValue() : { } { ( <INTEGER> { return Long.parseLong(token.image); } | <LONG> { return Long.parseLong(token.image.substring(0, token.image.length()-1)); } @@ -2930,17 +2934,17 @@ long consumeLong() : { } } /** Consumes a floating-point token and returns its numeric value. */ -double consumeFloat() : { } +double floatValue() : { } { <DOUBLE> { return Double.valueOf(token.image); } } -Number consumeNumber() : +Number number() : { Number num; } { - (num = consumeFloat() | num = consumeLong()) { return num; } + ( num = floatValue() | num = longValue() ) { return num; } } /** Consumes an opening brace with leading and trailing newline tokens. */ diff --git a/config-model/src/test/cfg/application/stateless_eval/example.model b/config-model/src/test/cfg/application/stateless_eval/example.model index 1d2db15c3ba..af1c85be4f0 100644 --- a/config-model/src/test/cfg/application/stateless_eval/example.model +++ b/config-model/src/test/cfg/application/stateless_eval/example.model @@ -7,7 +7,6 @@ model example { constants { constant1: tensor(x[3]):{{x:0}:0.5, {x:1}:1.5, {x:2}:2.5} constant2: 3.0 - #constant1asLarge tensor(x[3]): file:constant1asLarge.json } constant constant1asLarge { diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/parser/SchemaParserTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/parser/SchemaParserTestCase.java index 17d94639d87..2284acc705c 100644 --- a/config-model/src/test/java/com/yahoo/searchdefinition/parser/SchemaParserTestCase.java +++ b/config-model/src/test/java/com/yahoo/searchdefinition/parser/SchemaParserTestCase.java @@ -93,6 +93,7 @@ public class SchemaParserTestCase { assertNotEquals("", schema.name()); } + // TODO: Many (all)? of the files below are parsed from other tests and can be removed from here @Test public void parse_various_old_sdfiles() throws Exception { checkFileParses("src/test/cfg/search/data/travel/schemas/TTData.sd"); @@ -180,7 +181,6 @@ public class SchemaParserTestCase { checkFileParses("src/test/derived/namecollision/collision.sd"); checkFileParses("src/test/derived/namecollision/collisionstruct.sd"); checkFileParses("src/test/derived/nearestneighbor/test.sd"); - checkFileParses("src/test/derived/neuralnet/neuralnet.sd"); checkFileParses("src/test/derived/newrank/newrank.sd"); checkFileParses("src/test/derived/nuwa/newsindex.sd"); checkFileParses("src/test/derived/orderilscripts/orderilscripts.sd"); diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorTestCase.java index 114486a5ddc..5bf2115c3f7 100644 --- a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorTestCase.java +++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorTestCase.java @@ -13,7 +13,7 @@ import static org.junit.Assert.fail; public class RankingExpressionWithTensorTestCase { @Test - public void requireThatSingleLineConstantTensorAndTypeCanBeParsed() throws ParseException { + public void requireThatSingleLineConstantMappedTensorCanBeParsed() throws ParseException { RankProfileSearchFixture f = new RankProfileSearchFixture( " rank-profile my_profile {\n" + " first-phase {\n" + @@ -30,6 +30,40 @@ public class RankingExpressionWithTensorTestCase { } @Test + public void requireThatSingleLineConstantIndexedTensorCanBeParsed() throws ParseException { + RankProfileSearchFixture f = new RankProfileSearchFixture( + " rank-profile my_profile {\n" + + " first-phase {\n" + + " expression: sum(my_tensor)\n" + + " }\n" + + " constants {\n" + + " my_tensor tensor(x[3]):{ {x:0}:1, {x:1}:2, {x:2}:3 }\n" + + " }\n" + + " }"); + f.compileRankProfile("my_profile"); + f.assertFirstPhaseExpression("reduce(constant(my_tensor), sum)", "my_profile"); + f.assertRankProperty("tensor(x[3]):[1.0, 2.0, 3.0]", "constant(my_tensor).value", "my_profile"); + f.assertRankProperty("tensor(x[3])", "constant(my_tensor).type", "my_profile"); + } + + @Test + public void requireThatSingleLineConstantIndexedTensorShortFormCanBeParsed() throws ParseException { + RankProfileSearchFixture f = new RankProfileSearchFixture( + " rank-profile my_profile {\n" + + " first-phase {\n" + + " expression: sum(my_tensor)\n" + + " }\n" + + " constants {\n" + + " my_tensor tensor(x[3]):[1, 2, 3]\n" + + " }\n" + + " }"); + f.compileRankProfile("my_profile"); + f.assertFirstPhaseExpression("reduce(constant(my_tensor), sum)", "my_profile"); + f.assertRankProperty("tensor(x[3]):[1.0, 2.0, 3.0]", "constant(my_tensor).value", "my_profile"); + f.assertRankProperty("tensor(x[3])", "constant(my_tensor).type", "my_profile"); + } + + @Test public void requireConstantTensorCanBeReferredViaConstantFeature() throws ParseException { RankProfileSearchFixture f = new RankProfileSearchFixture( " rank-profile my_profile {\n" + diff --git a/config-model/src/test/java/com/yahoo/vespa/model/search/test/SchemaInfoTestCase.java b/config-model/src/test/java/com/yahoo/vespa/model/search/test/SchemaInfoTestCase.java index 34afca703e9..b8a14bc763b 100644 --- a/config-model/src/test/java/com/yahoo/vespa/model/search/test/SchemaInfoTestCase.java +++ b/config-model/src/test/java/com/yahoo/vespa/model/search/test/SchemaInfoTestCase.java @@ -25,7 +25,8 @@ public class SchemaInfoTestCase { " query(myDouble1) double: 0.5" + " query(myDouble2) tensor()" + " query(myMap) tensor(key{}): { label1:1.0,\n \"label2\": 2.0, 'label3': 3.0 }" + - " query(myVector) tensor(x[3]):\n\n[1 ,2.0,3]" + + " query(myVector1) tensor(x[3]):\n\n[1 ,2.0,3]" + + " query(myVector2) tensor(x[3]):{{x:0}:1,{x: 1}: 2 , { x:2}:3.0 }" + " query(myMatrix) tensor(x[2],y[3]):[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]" + " query(myMixed1) tensor(key{},x[2]): { key1:[-1.0, 1.1], key2: [1,2]}" + " query(myMixed2) tensor(k1{},k2{},x[2]): { {k1:l1,k2:l1}:[-1.0, 1.1], {k1:l1,k2:l2}: [1,2]}" + @@ -58,7 +59,7 @@ public class SchemaInfoTestCase { tester.assertRankProfile(schema, 5, "rankfeatures", false, true); var schemaInfoProfile = tester.assertRankProfile(schema, 6, "inputs", false, false); - assertEquals(9, schemaInfoProfile.input().size()); + assertEquals(10, schemaInfoProfile.input().size()); var rankProfilesProfile = rankProfilesConfig.rankprofile().get(6); assertEquals("inputs", rankProfilesProfile.name()); assertInput("query(foo)", "tensor<float>(x[10])", null, 0, schemaInfoProfile, rankProfilesProfile); @@ -66,10 +67,11 @@ public class SchemaInfoTestCase { assertInput("query(myDouble1)", "tensor()", "0.5", 2, schemaInfoProfile, rankProfilesProfile); assertInput("query(myDouble2)", "tensor()", null, 3, schemaInfoProfile, rankProfilesProfile); assertInput("query(myMap)", "tensor(key{})", "tensor(key{}):{{key:label1}:1.0, {key:label2}:2.0, {key:label3}:3.0}", 4, schemaInfoProfile, rankProfilesProfile); - assertInput("query(myVector)", "tensor(x[3])", "tensor(x[3]):{{x:0}:1.0, {x:1}:2.0, {x:2}:3.0}", 5, schemaInfoProfile, rankProfilesProfile); - assertInput("query(myMatrix)", "tensor(x[2],y[3])", "tensor(x[2],y[3]):{{x:0,y:0}:1.0, {x:0,y:1}:2.0, {x:0,y:2}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0, {x:1,y:2}:6.0}", 6, schemaInfoProfile, rankProfilesProfile); - assertInput("query(myMixed1)", "tensor(key{},x[2])", "tensor(key{},x[2]):{{key:key1,x:0}:-1.0, {key:key1,x:1}:1.1, {key:key2,x:0}:1.0, {key:key2,x:1}:2.0}", 7, schemaInfoProfile, rankProfilesProfile); - assertInput("query(myMixed2)", "tensor(k1{},k2{},x[2])", "tensor(k1{},k2{},x[2]):{{k1:l1,k2:l1,x:0}:-1.0, {k1:l1,k2:l1,x:1}:1.1, {k1:l1,k2:l2,x:0}:1.0, {k1:l1,k2:l2,x:1}:2.0}", 8, schemaInfoProfile, rankProfilesProfile); + assertInput("query(myVector1)", "tensor(x[3])", "tensor(x[3]):{{x:0}:1.0, {x:1}:2.0, {x:2}:3.0}", 5, schemaInfoProfile, rankProfilesProfile); + assertInput("query(myVector2)", "tensor(x[3])", "tensor(x[3]):{{x:0}:1.0, {x:1}:2.0, {x:2}:3.0}", 6, schemaInfoProfile, rankProfilesProfile); + assertInput("query(myMatrix)", "tensor(x[2],y[3])", "tensor(x[2],y[3]):{{x:0,y:0}:1.0, {x:0,y:1}:2.0, {x:0,y:2}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0, {x:1,y:2}:6.0}", 7, schemaInfoProfile, rankProfilesProfile); + assertInput("query(myMixed1)", "tensor(key{},x[2])", "tensor(key{},x[2]):{{key:key1,x:0}:-1.0, {key:key1,x:1}:1.1, {key:key2,x:0}:1.0, {key:key2,x:1}:2.0}", 8, schemaInfoProfile, rankProfilesProfile); + assertInput("query(myMixed2)", "tensor(k1{},k2{},x[2])", "tensor(k1{},k2{},x[2]):{{k1:l1,k2:l1,x:0}:-1.0, {k1:l1,k2:l1,x:1}:1.1, {k1:l1,k2:l2,x:0}:1.0, {k1:l1,k2:l2,x:1}:2.0}", 9, schemaInfoProfile, rankProfilesProfile); assertEquals(2, schema.summaryclass().size()); assertEquals("default", schema.summaryclass(0).name()); |