diff options
| author | Jon Bratseth <bratseth@yahoo-inc.com> | 2018-01-09 16:07:43 +0100 |
|---|---|---|
| committer | Jon Bratseth <bratseth@yahoo-inc.com> | 2018-01-09 16:07:43 +0100 |
| commit | dc0f70fac9167acf487453daf565636c675934df (patch) | |
| tree | aaccfae7aaf4a48e35655a66c75ea57412ede6a6 /config-model | |
| parent | fa9fe82c82d6a562e3ae02b9577f536a16c72c92 (diff) | |
Basic TensorFlow integration
This wil replace any occurrence of tensorflow(...)
in ranking expressions with the corresponding translated expression.
It is functional but these tings are outstanding
- Propagate warnings
- Import a model just once even if referred multiple times
- Add constants as tensor files rather than config
Diffstat (limited to 'config-model')
21 files changed, 5516 insertions, 76 deletions
diff --git a/config-model/pom.xml b/config-model/pom.xml index 729d1a2ef9b..1e673578968 100644 --- a/config-model/pom.xml +++ b/config-model/pom.xml @@ -309,6 +309,21 @@ <artifactId>scala-xml_${scala.major-version}</artifactId> <scope>test</scope> </dependency> + <dependency> + <groupId>com.google.protobuf</groupId> + <artifactId>protobuf-java</artifactId> + <version>3.4.0</version> + </dependency> + <dependency> + <groupId>org.tensorflow</groupId> + <artifactId>proto</artifactId> + <version>1.4.0</version> + </dependency> + <dependency> + <groupId>org.tensorflow</groupId> + <artifactId>tensorflow</artifactId> + <version>1.4.0</version> + </dependency> </dependencies> <build> diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplier.java b/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplier.java index cdd089d9bf7..f9d71f03972 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplier.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplier.java @@ -6,9 +6,10 @@ import com.yahoo.searchdefinition.document.SDDocumentType; import com.yahoo.searchdefinition.document.SDField; /** - * @author <a href="mailto:einarmr@yahoo-inc.com">Einar M R Rosenvinge</a> + * @author Einar M R Rosenvinge */ public class FieldOperationApplier { + public void process(SDDocumentType sdoc) { if (!sdoc.isStruct()) { apply(sdoc); diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplierForSearch.java b/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplierForSearch.java index addaa4bc632..1019b794cdd 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplierForSearch.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplierForSearch.java @@ -5,7 +5,7 @@ import com.yahoo.document.Field; import com.yahoo.searchdefinition.document.SDDocumentType; /** - * @author <a href="mailto:einarmr@yahoo-inc.com">Einar M R Rosenvinge</a> + * @author Einar M R Rosenvinge */ public class FieldOperationApplierForSearch extends FieldOperationApplier { @Override diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplierForStructs.java b/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplierForStructs.java index 30fdcd01dd4..04b0fc6e331 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplierForStructs.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/FieldOperationApplierForStructs.java @@ -11,9 +11,10 @@ import java.util.Iterator; import java.util.List; /** - * @author <a href="mailto:einarmr@yahoo-inc.com">Einar M R Rosenvinge</a> + * @author Einar M R Rosenvinge */ public class FieldOperationApplierForStructs extends FieldOperationApplier { + @Override public void process(SDDocumentType sdoc) { for (SDDocumentType type : sdoc.getAllTypes()) { @@ -45,4 +46,5 @@ public class FieldOperationApplierForStructs extends FieldOperationApplier { } } } + } diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java b/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java index 1021227b0e6..cf92d1f979b 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java @@ -1,7 +1,9 @@ // Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. package com.yahoo.searchdefinition; +import com.yahoo.config.application.api.ApplicationPackage; import com.yahoo.search.query.ranking.Diversity; +import com.yahoo.searchdefinition.expressiontransforms.ExpressionTransforms; import com.yahoo.searchdefinition.parser.ParseException; import com.yahoo.searchlib.rankingexpression.ExpressionFunction; import com.yahoo.searchlib.rankingexpression.FeatureList; @@ -9,13 +11,22 @@ import com.yahoo.searchlib.rankingexpression.RankingExpression; import com.yahoo.searchlib.rankingexpression.evaluation.TensorValue; import com.yahoo.searchlib.rankingexpression.evaluation.Value; import com.yahoo.searchlib.rankingexpression.rule.ReferenceNode; -import com.yahoo.searchlib.rankingexpression.rule.SetMembershipNode; -import com.yahoo.searchlib.rankingexpression.transform.ConstantDereferencer; -import com.yahoo.searchlib.rankingexpression.transform.Simplifier; -import com.yahoo.config.application.api.ApplicationPackage; -import java.io.*; -import java.util.*; +import java.io.File; +import java.io.IOException; +import java.io.Reader; +import java.io.Serializable; +import java.io.StringReader; +import java.util.ArrayList; +import java.util.Collections; +import java.util.HashMap; +import java.util.HashSet; +import java.util.Iterator; +import java.util.LinkedHashMap; +import java.util.LinkedHashSet; +import java.util.List; +import java.util.Map; +import java.util.Set; /** * Represents a rank profile - a named set of ranking settings @@ -40,7 +51,7 @@ public class RankProfile implements Serializable, Cloneable { protected Set<RankSetting> rankSettings = new java.util.LinkedHashSet<>(); /** The ranking expression to be used for first phase */ - private RankingExpression firstPhaseRanking= null; + private RankingExpression firstPhaseRanking= null; /** The ranking expression to be used for second phase */ private RankingExpression secondPhaseRanking = null; @@ -485,7 +496,7 @@ public class RankProfile implements Serializable, Cloneable { /** * Returns the string form of the second phase ranking expression. - * + * * @return string form of second phase ranking expression */ public String getSecondPhaseRankingString() { @@ -702,12 +713,7 @@ public class RankProfile implements Serializable, Cloneable { Map<String, Macro> inlineMacros) { if (expression == null) return null; Map<String, String> rankPropertiesOutput = new HashMap<>(); - expression = new ConstantDereferencer(constants).transform(expression); - expression = new ConstantTensorTransformer(constants, rankPropertiesOutput).transform(expression); - expression = new MacroInliner(inlineMacros).transform(expression); - expression = new MacroShadower(getMacros()).transform(expression); - expression = new TensorTransformer(this).transform(expression); - expression = new Simplifier().transform(expression); + expression = new ExpressionTransforms().transform(expression, this, constants, inlineMacros, rankPropertiesOutput); for (Map.Entry<String, String> rankProperty : rankPropertiesOutput.entrySet()) { addRankProperty(rankProperty.getKey(), rankProperty.getValue()); } @@ -975,7 +981,7 @@ public class RankProfile implements Serializable, Cloneable { throw new IllegalArgumentException("match-phase did not set max-hits > 0"); } } - + } public static class TypeSettings { diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/UnprocessingSearchBuilder.java b/config-model/src/main/java/com/yahoo/searchdefinition/UnprocessingSearchBuilder.java index 1b292007ef3..b448005c6a5 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/UnprocessingSearchBuilder.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/UnprocessingSearchBuilder.java @@ -10,7 +10,6 @@ import java.io.IOException; /** * A SearchBuilder that does not run the processing chain for searches - * */ public class UnprocessingSearchBuilder extends SearchBuilder { diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/UnrankedRankProfile.java b/config-model/src/main/java/com/yahoo/searchdefinition/UnrankedRankProfile.java index d8f7e56539e..b58f696cbdf 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/UnrankedRankProfile.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/UnrankedRankProfile.java @@ -25,4 +25,5 @@ public class UnrankedRankProfile extends RankProfile { this.setKeepRankCount(0); this.setRerankCount(0); } + } diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/ConstantTensorTransformer.java b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/ConstantTensorTransformer.java index c75864f81b7..e061ead465e 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/ConstantTensorTransformer.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/ConstantTensorTransformer.java @@ -1,5 +1,5 @@ // Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. -package com.yahoo.searchdefinition; +package com.yahoo.searchdefinition.expressiontransforms; import com.yahoo.searchlib.rankingexpression.evaluation.TensorValue; import com.yahoo.searchlib.rankingexpression.evaluation.Value; @@ -19,7 +19,7 @@ import java.util.Map; * * @author geirst */ -class ConstantTensorTransformer extends ExpressionTransformer { +public class ConstantTensorTransformer extends ExpressionTransformer { public static final String CONSTANT = "constant"; diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/ExpressionTransforms.java b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/ExpressionTransforms.java new file mode 100644 index 00000000000..ee5cccccb29 --- /dev/null +++ b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/ExpressionTransforms.java @@ -0,0 +1,34 @@ +package com.yahoo.searchdefinition.expressiontransforms; + +import com.yahoo.searchdefinition.RankProfile; +import com.yahoo.searchlib.rankingexpression.RankingExpression; +import com.yahoo.searchlib.rankingexpression.evaluation.Value; +import com.yahoo.searchlib.rankingexpression.transform.ConstantDereferencer; +import com.yahoo.searchlib.rankingexpression.transform.Simplifier; + +import java.util.Map; + +/** + * The transformations done on ranking expressions done at config time before passing them on to the Vespa + * engine for execution. + * + * @author bratseth + */ +public class ExpressionTransforms { + + public RankingExpression transform(RankingExpression expression, + RankProfile rankProfile, + Map<String, Value> constants, + Map<String, RankProfile.Macro> inlineMacros, + Map<String, String> rankPropertiesOutput) { + expression = new TensorFlowFeatureConverter(rankProfile).transform(expression); + expression = new ConstantDereferencer(constants).transform(expression); + expression = new ConstantTensorTransformer(constants, rankPropertiesOutput).transform(expression); + expression = new MacroInliner(inlineMacros).transform(expression); + expression = new MacroShadower(rankProfile.getMacros()).transform(expression); + expression = new TensorTransformer(rankProfile).transform(expression); + expression = new Simplifier().transform(expression); + return expression; + } + +} diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/MacroInliner.java b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/MacroInliner.java index 4702fac30a8..a3933e6f8e2 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/MacroInliner.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/MacroInliner.java @@ -1,6 +1,7 @@ // Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. -package com.yahoo.searchdefinition; +package com.yahoo.searchdefinition.expressiontransforms; +import com.yahoo.searchdefinition.RankProfile; import com.yahoo.searchlib.rankingexpression.rule.CompositeNode; import com.yahoo.searchlib.rankingexpression.rule.ExpressionNode; import com.yahoo.searchlib.rankingexpression.rule.ReferenceNode; @@ -13,7 +14,7 @@ import java.util.Map; * * @author bratseth */ -class MacroInliner extends ExpressionTransformer { +public class MacroInliner extends ExpressionTransformer { private final Map<String, RankProfile.Macro> macros; diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/MacroShadower.java b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/MacroShadower.java index edf0ce69819..1d9769d0d78 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/MacroShadower.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/MacroShadower.java @@ -1,6 +1,7 @@ // Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. -package com.yahoo.searchdefinition; +package com.yahoo.searchdefinition.expressiontransforms; +import com.yahoo.searchdefinition.RankProfile; import com.yahoo.searchlib.rankingexpression.RankingExpression; import com.yahoo.searchlib.rankingexpression.rule.*; import com.yahoo.searchlib.rankingexpression.transform.ExpressionTransformer; @@ -20,7 +21,7 @@ import java.util.Map; * * @author lesters */ -class MacroShadower extends ExpressionTransformer { +public class MacroShadower extends ExpressionTransformer { private final Map<String, RankProfile.Macro> macros; diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/TensorFlowFeatureConverter.java b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/TensorFlowFeatureConverter.java new file mode 100644 index 00000000000..e5886030d44 --- /dev/null +++ b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/TensorFlowFeatureConverter.java @@ -0,0 +1,114 @@ +package com.yahoo.searchdefinition.expressiontransforms; + +import com.yahoo.searchdefinition.RankProfile; +import com.yahoo.searchlib.rankingexpression.evaluation.TensorValue; +import com.yahoo.searchlib.rankingexpression.integration.tensorflow.ImportResult; +import com.yahoo.searchlib.rankingexpression.integration.tensorflow.TensorFlowImporter; +import com.yahoo.searchlib.rankingexpression.rule.Arguments; +import com.yahoo.searchlib.rankingexpression.rule.CompositeNode; +import com.yahoo.searchlib.rankingexpression.rule.ConstantNode; +import com.yahoo.searchlib.rankingexpression.rule.ExpressionNode; +import com.yahoo.searchlib.rankingexpression.rule.ReferenceNode; +import com.yahoo.searchlib.rankingexpression.transform.ExpressionTransformer; + +import java.util.Map; +import java.util.Optional; + +/** + * Replaces instances of the tensorflow(model-path, signature, output) + * pseudofeature with the native Vespa ranking expression implementing + * the same computation. + * + * @author bratseth + */ +public class TensorFlowFeatureConverter extends ExpressionTransformer { + + private final TensorFlowImporter tensorFlowImporter = new TensorFlowImporter(); + private final RankProfile profile; + + public TensorFlowFeatureConverter(RankProfile profile) { + this.profile = profile; + } + + @Override + public ExpressionNode transform(ExpressionNode node) { + if (node instanceof ReferenceNode) + return transformFeature((ReferenceNode) node); + else if (node instanceof CompositeNode) + return super.transformChildren((CompositeNode) node); + else + return node; + } + + private ExpressionNode transformFeature(ReferenceNode feature) { + try { + if ( ! feature.getName().equals("tensorflow")) return feature; + + if (feature.getArguments().isEmpty()) + throw new IllegalArgumentException("A tensorflow node must take an argument pointing to " + + "the tensorflow model directory under [application]/models"); + + // Find the specified expression + ImportResult result = tensorFlowImporter.importModel(asString(feature.getArguments().expressions().get(0))); + ImportResult.Signature signature = chooseOrDefault("signatures", result.signatures(), + optionalArgument(1, feature.getArguments())); + String output = chooseOrDefault("outputs", signature.outputs(), + optionalArgument(2, feature.getArguments())); + + // Add all constants + result.constants().forEach((k, v) -> profile.addConstantTensor(k, new TensorValue(v))); + + return result.expressions().get(output).getRoot(); + } + catch (IllegalArgumentException e) { + throw new IllegalArgumentException("Could not import tensorflow model from " + feature, e); + } + } + + /** + * Returns the specified, existing map value, or the only map value if no key is specified. + * Throws IllegalArgumentException in all other cases. + */ + private <T> T chooseOrDefault(String valueDescription, Map<String, T> map, Optional<String> key) { + if ( ! key.isPresent()) { + if (map.size() == 0) + throw new IllegalArgumentException("No " + valueDescription + " are present"); + if (map.size() > 1) + throw new IllegalArgumentException("Model has multiple " + valueDescription + ", but no " + + valueDescription + " argument is specified"); + return map.values().stream().findFirst().get(); + } + else { + T value = map.get(key.get()); + if (value == null) + throw new IllegalArgumentException("Model does not have the specified " + + valueDescription + " '" + key.get() + "'"); + return value; + } + } + + private Optional<String> optionalArgument(int argumentIndex, Arguments arguments) { + if (argumentIndex >= arguments.expressions().size()) + return Optional.empty(); + return Optional.of(asString(arguments.expressions().get(argumentIndex))); + } + + private String asString(ExpressionNode node) { + if ( ! (node instanceof ConstantNode)) + throw new IllegalArgumentException("Expected a constant string as tensorflow argument, but got '" + node); + return stripQuotes(((ConstantNode)node).sourceString()); + } + + private String stripQuotes(String s) { + if ( ! isQuoteSign(s.codePointAt(0))) return s; + if ( ! isQuoteSign(s.codePointAt(s.length() - 1 ))) + throw new IllegalArgumentException("tensorflow argument [" + s + "] is missing endquote"); + return s.substring(1, s.length()-1); + } + + private boolean isQuoteSign(int c) { + return c == '\'' || c == '"'; + } + + +} diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/TensorTransformer.java b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/TensorTransformer.java index 65176006a2a..70a7372dbe9 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/TensorTransformer.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/expressiontransforms/TensorTransformer.java @@ -1,6 +1,9 @@ // Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. -package com.yahoo.searchdefinition; +package com.yahoo.searchdefinition.expressiontransforms; +import com.yahoo.searchdefinition.RankProfile; +import com.yahoo.searchdefinition.RankingConstant; +import com.yahoo.searchdefinition.Search; import com.yahoo.searchdefinition.document.Attribute; import com.yahoo.searchlib.rankingexpression.evaluation.Context; import com.yahoo.searchlib.rankingexpression.evaluation.DoubleValue; diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/processing/PredicateProcessor.java b/config-model/src/main/java/com/yahoo/searchdefinition/processing/PredicateProcessor.java index 450c24d8e3e..4b9b090cdc5 100644 --- a/config-model/src/main/java/com/yahoo/searchdefinition/processing/PredicateProcessor.java +++ b/config-model/src/main/java/com/yahoo/searchdefinition/processing/PredicateProcessor.java @@ -24,7 +24,7 @@ import java.util.List; /** * Validates the predicate fields. * - * @author <a href="mailto:lesters@yahoo-inc.com">Lester Solbakken</a> + * @author Lester Solbakken */ public class PredicateProcessor extends Processor { diff --git a/config-model/src/test/integration/tensorflow/mnist_softmax/mnist_sftmax_with_saving.py b/config-model/src/test/integration/tensorflow/mnist_softmax/mnist_sftmax_with_saving.py new file mode 100644 index 00000000000..a1861a1c981 --- /dev/null +++ b/config-model/src/test/integration/tensorflow/mnist_softmax/mnist_sftmax_with_saving.py @@ -0,0 +1,89 @@ +# Copyright 2015 The TensorFlow Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== + +"""A very simple MNIST classifier. + +See extensive documentation at +https://www.tensorflow.org/get_started/mnist/beginners +""" +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import argparse +import sys + +from tensorflow.examples.tutorials.mnist import input_data + +import tensorflow as tf + +FLAGS = None + + +def main(_): + # Import data + mnist = input_data.read_data_sets(FLAGS.data_dir, one_hot=True) + + # Create the model + x = tf.placeholder(tf.float32, [None, 784]) + W = tf.Variable(tf.zeros([784, 10])) + b = tf.Variable(tf.zeros([10])) + y = tf.matmul(x, W) + b + + # Define loss and optimizer + y_ = tf.placeholder(tf.float32, [None, 10]) + + # The raw formulation of cross-entropy, + # + # tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(tf.nn.softmax(y)), + # reduction_indices=[1])) + # + # can be numerically unstable. + # + # So here we use tf.nn.softmax_cross_entropy_with_logits on the raw + # outputs of 'y', and then average across the batch. + cross_entropy = tf.reduce_mean( + tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y)) + train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy) + + sess = tf.InteractiveSession() + tf.global_variables_initializer().run() + # Train + for _ in range(1000): + batch_xs, batch_ys = mnist.train.next_batch(100) + sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys}) + + # Test trained model + correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1)) + accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32)) + print(sess.run(accuracy, feed_dict={x: mnist.test.images, + y_: mnist.test.labels})) + + # Save the model + export_path = "saved" + print('Exporting trained model to ', export_path) + builder = tf.saved_model.builder.SavedModelBuilder(export_path) + signature = tf.saved_model.signature_def_utils.predict_signature_def(inputs = {'x':x}, outputs = {'y':y}) + builder.add_meta_graph_and_variables(sess, + [tf.saved_model.tag_constants.SERVING], + signature_def_map={'serving_default':signature}) + builder.save(as_text=True) + +if __name__ == '__main__': + parser = argparse.ArgumentParser() + parser.add_argument('--data_dir', type=str, default='/tmp/tensorflow/mnist/input_data', + help='Directory for storing input data') + FLAGS, unparsed = parser.parse_known_args() + tf.app.run(main=main, argv=[sys.argv[0]] + unparsed) diff --git a/config-model/src/test/integration/tensorflow/mnist_softmax/saved/saved_model.pbtxt b/config-model/src/test/integration/tensorflow/mnist_softmax/saved/saved_model.pbtxt new file mode 100644 index 00000000000..8100dfd594d --- /dev/null +++ b/config-model/src/test/integration/tensorflow/mnist_softmax/saved/saved_model.pbtxt @@ -0,0 +1,5039 @@ +saved_model_schema_version: 1 +meta_graphs { + meta_info_def { + stripped_op_list { + op { + name: "Add" + input_arg { + name: "x" + type_attr: "T" + } + input_arg { + name: "y" + type_attr: "T" + } + output_arg { + name: "z" + type_attr: "T" + } + attr { + name: "T" + type: "type" + allowed_values { + list { + type: DT_HALF + type: DT_FLOAT + type: DT_DOUBLE + type: DT_UINT8 + type: DT_INT8 + type: DT_INT16 + type: DT_INT32 + type: DT_INT64 + type: DT_COMPLEX64 + type: DT_COMPLEX128 + type: DT_STRING + } + } + } + } + op { + name: "ApplyGradientDescent" + input_arg { + name: "var" + type_attr: "T" + is_ref: true + } + input_arg { + name: "alpha" + type_attr: "T" + } + input_arg { + name: "delta" + type_attr: "T" + } + output_arg { + name: "out" + type_attr: "T" + is_ref: true + } + attr { + name: "T" + type: "type" + allowed_values { + list { + type: DT_FLOAT + type: DT_DOUBLE + type: DT_INT64 + type: DT_INT32 + type: DT_UINT8 + type: DT_UINT16 + type: DT_INT16 + type: DT_INT8 + type: DT_COMPLEX64 + type: DT_COMPLEX128 + type: DT_QINT8 + type: DT_QUINT8 + type: DT_QINT32 + type: DT_HALF + } + } + } + attr { + name: "use_locking" + type: "bool" + default_value { + b: false + } + } + } + op { + name: "ArgMax" + input_arg { + name: "input" + type_attr: "T" + } + input_arg { + name: "dimension" + type_attr: "Tidx" + } + output_arg { + name: "output" + type_attr: "output_type" + } + attr { + name: "T" + type: "type" + allowed_values { + list { + type: DT_FLOAT + type: DT_DOUBLE + type: DT_INT64 + type: DT_INT32 + type: DT_UINT8 + type: DT_UINT16 + type: DT_INT16 + type: DT_INT8 + type: DT_COMPLEX64 + type: DT_COMPLEX128 + type: DT_QINT8 + type: DT_QUINT8 + type: DT_QINT32 + type: DT_HALF + } + } + } + attr { + name: "Tidx" + type: "type" + default_value { + type: DT_INT32 + } + allowed_values { + list { + type: DT_INT32 + type: DT_INT64 + } + } + } + attr { + name: "output_type" + type: "type" + default_value { + type: DT_INT64 + } + allowed_values { + list { + type: DT_INT32 + type: DT_INT64 + } + } + } + } + op { + name: "Assign" + input_arg { + name: "ref" + type_attr: "T" + is_ref: true + } + input_arg { + name: "value" + type_attr: "T" + } + output_arg { + name: "output_ref" + type_attr: "T" + is_ref: true + } + attr { + name: "T" + type: "type" + } + attr { + name: "validate_shape" + type: "bool" + default_value { + b: true + } + } + attr { + name: "use_locking" + type: "bool" + default_value { + b: true + } + } + allows_uninitialized_input: true + } + op { + name: "BroadcastGradientArgs" 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{ + dim { + size: 10 + } + } + } + } + } + attr { + key: "use_locking" + value { + b: true + } + } + attr { + key: "validate_shape" + value { + b: true + } + } + } + node { + name: "save/restore_shard" + op: "NoOp" + input: "^save/Assign" + input: "^save/Assign_1" + } + node { + name: "save/restore_all" + op: "NoOp" + input: "^save/restore_shard" + } + versions { + producer: 24 + } + } + saver_def { + filename_tensor_name: "save/Const:0" + save_tensor_name: "save/Identity:0" + restore_op_name: "save/restore_all" + max_to_keep: 5 + sharded: true + keep_checkpoint_every_n_hours: 10000.0 + version: V2 + } + collection_def { + key: "train_op" + value { + node_list { + value: "GradientDescent" + } + } + } + collection_def { + key: "trainable_variables" + value { + bytes_list { + value: "\n\nVariable:0\022\017Variable/Assign\032\017Variable/read:02\007zeros:0" + value: "\n\014Variable_1:0\022\021Variable_1/Assign\032\021Variable_1/read:02\tzeros_1:0" + } + } + } + collection_def { + key: "variables" + value { + bytes_list { + value: "\n\nVariable:0\022\017Variable/Assign\032\017Variable/read:02\007zeros:0" + value: "\n\014Variable_1:0\022\021Variable_1/Assign\032\021Variable_1/read:02\tzeros_1:0" + } + } + } + signature_def { + key: "serving_default" + value { + inputs { + key: "x" + value { + name: "Placeholder:0" + dtype: DT_FLOAT + tensor_shape { + dim { + size: -1 + } + dim { + size: 784 + } + } + } + } + outputs { + key: "y" + value { + name: "add:0" + dtype: DT_FLOAT + tensor_shape { + dim { + size: -1 + } + dim { + size: 10 + } + } + } + } + method_name: "tensorflow/serving/predict" + } + } +} diff --git a/config-model/src/test/integration/tensorflow/mnist_softmax/saved/variables/variables.data-00000-of-00001 b/config-model/src/test/integration/tensorflow/mnist_softmax/saved/variables/variables.data-00000-of-00001 Binary files differnew file mode 100644 index 00000000000..8474aa0a04c --- /dev/null +++ b/config-model/src/test/integration/tensorflow/mnist_softmax/saved/variables/variables.data-00000-of-00001 diff --git a/config-model/src/test/integration/tensorflow/mnist_softmax/saved/variables/variables.index b/config-model/src/test/integration/tensorflow/mnist_softmax/saved/variables/variables.index Binary files differnew file mode 100644 index 00000000000..cfcdac20409 --- /dev/null +++ b/config-model/src/test/integration/tensorflow/mnist_softmax/saved/variables/variables.index diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankProfileSearchFixture.java b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankProfileSearchFixture.java new file mode 100644 index 00000000000..e71a627d7db --- /dev/null +++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankProfileSearchFixture.java @@ -0,0 +1,58 @@ +package com.yahoo.searchdefinition.processing; + +import com.yahoo.searchdefinition.RankProfile; +import com.yahoo.searchdefinition.RankProfileRegistry; +import com.yahoo.searchdefinition.Search; +import com.yahoo.searchdefinition.SearchBuilder; +import com.yahoo.searchdefinition.parser.ParseException; + +import java.util.List; + +import static org.junit.Assert.assertEquals; + +/** + * Helper class for setting up and asserting over a Search instance with a rank profile given literally + * in the search definition language. + * + * @author geirst + */ +class RankProfileSearchFixture { + + private RankProfileRegistry rankProfileRegistry = new RankProfileRegistry(); + private Search search; + + RankProfileSearchFixture(String rankProfiles) throws ParseException { + SearchBuilder builder = new SearchBuilder(rankProfileRegistry); + String sdContent = "search test {\n" + + " document test {\n" + + " }\n" + + rankProfiles + + "\n" + + "}"; + builder.importString(sdContent); + builder.build(); + search = builder.getSearch(); + } + + public void assertFirstPhaseExpression(String expExpression, String rankProfile) { + assertEquals(expExpression, rankProfile(rankProfile).getFirstPhaseRanking().getRoot().toString()); + } + + public void assertSecondPhaseExpression(String expExpression, String rankProfile) { + assertEquals(expExpression, rankProfile(rankProfile).getSecondPhaseRanking().getRoot().toString()); + } + + public void assertRankProperty(String expValue, String name, String rankProfile) { + List<RankProfile.RankProperty> rankPropertyList = rankProfile(rankProfile).getRankPropertyMap().get(name); + assertEquals(1, rankPropertyList.size()); + assertEquals(expValue, rankPropertyList.get(0).getValue()); + } + + public void assertMacro(String expExpression, String macroName, String rankProfile) { + assertEquals(expExpression, rankProfile(rankProfile).getMacros().get(macroName).getRankingExpression().getRoot().toString()); + } + + public RankProfile rankProfile(String rankProfile) { + return rankProfileRegistry.getRankProfile(search, rankProfile).compile(); + } +} 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 new file mode 100644 index 00000000000..5ad85ac872c --- /dev/null +++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java @@ -0,0 +1,119 @@ +// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. +package com.yahoo.searchdefinition.processing; + +import com.yahoo.searchdefinition.parser.ParseException; +import com.yahoo.tensor.Tensor; +import com.yahoo.yolean.Exceptions; +import org.junit.Test; + +import static org.junit.Assert.assertEquals; +import static org.junit.Assert.assertNotNull; +import static org.junit.Assert.fail; + +/** + * @author bratseth + */ +public class RankingExpressionWithTensorFlowTestCase { + + private final String modelDirectory = "src/test/integration/tensorflow/mnist_softmax/saved"; + private final String vespaExpression = "join(rename(reduce(join(Placeholder, rename(constant(Variable), (d0, d1), (d1, d3)), f(a,b)(a * b)), sum, d1), d3, d1), rename(constant(Variable_1), d0, d1), f(a,b)(a + b))"; + + @Test + public void testMinimalTensorFlowReference() throws ParseException { + RankProfileSearchFixture search = new RankProfileSearchFixture( + " rank-profile my_profile {\n" + + " first-phase {\n" + + " expression: tensorflow('" + modelDirectory + "')" + + " }\n" + + " }"); + search.assertFirstPhaseExpression(vespaExpression, "my_profile"); + + Tensor variable_1 = search.rankProfile("my_profile").getConstants().get("Variable_1").asTensor(); + assertNotNull("Variable_1 is imported", variable_1); + assertEquals(10, variable_1.size()); + + Tensor variable = search.rankProfile("my_profile").getConstants().get("Variable").asTensor(); + assertNotNull("Variable is imported", variable); + assertEquals(7840, variable.size()); + } + + @Test + public void testNestedTensorFlowReference() throws ParseException { + RankProfileSearchFixture search = new RankProfileSearchFixture( + " rank-profile my_profile {\n" + + " first-phase {\n" + + " expression: 5 + sum(tensorflow('" + modelDirectory + "'))" + + " }\n" + + " }"); + search.assertFirstPhaseExpression("5 + reduce(" + vespaExpression + ", sum)", "my_profile"); + + Tensor variable_1 = search.rankProfile("my_profile").getConstants().get("Variable_1").asTensor(); + assertNotNull("Variable_1 is imported", variable_1); + assertEquals(10, variable_1.size()); + + Tensor variable = search.rankProfile("my_profile").getConstants().get("Variable").asTensor(); + assertNotNull("Variable is imported", variable); + assertEquals(7840, variable.size()); + } + + @Test + public void testTensorFlowReferenceSpecifyingSignature() throws ParseException { + RankProfileSearchFixture search = new RankProfileSearchFixture( + " rank-profile my_profile {\n" + + " first-phase {\n" + + " expression: tensorflow('" + modelDirectory + "', 'serving_default')" + + " }\n" + + " }"); + search.assertFirstPhaseExpression(vespaExpression, "my_profile"); + } + + @Test + public void testTensorFlowReferenceSpecifyingSignatureAndOutput() throws ParseException { + RankProfileSearchFixture search = new RankProfileSearchFixture( + " rank-profile my_profile {\n" + + " first-phase {\n" + + " expression: tensorflow('" + modelDirectory + "', 'serving_default', 'y')" + + " }\n" + + " }"); + search.assertFirstPhaseExpression(vespaExpression, "my_profile"); + } + + @Test + public void testTensorFlowReferenceSpecifyingNonExistingSignature() throws ParseException { + try { + RankProfileSearchFixture search = new RankProfileSearchFixture( + " rank-profile my_profile {\n" + + " first-phase {\n" + + " expression: tensorflow('" + modelDirectory + "', 'serving_defaultz')" + + " }\n" + + " }"); + search.assertFirstPhaseExpression(vespaExpression, "my_profile"); + fail("Expecting exception"); + } + catch (IllegalArgumentException expected) { + assertEquals("Rank profile 'my_profile' is invalid: Could not import tensorflow model from tensorflow('" + + modelDirectory + "','serving_defaultz'): Model does not have the specified signatures 'serving_defaultz'", + Exceptions.toMessageString(expected)); + } + } + + @Test + public void testTensorFlowReferenceSpecifyingNonExistingOutput() throws ParseException { + try { + RankProfileSearchFixture search = new RankProfileSearchFixture( + " rank-profile my_profile {\n" + + " first-phase {\n" + + " expression: tensorflow('" + modelDirectory + "', 'serving_default', 'x')" + + " }\n" + + " }"); + search.assertFirstPhaseExpression(vespaExpression, "my_profile"); + fail("Expecting exception"); + } + catch (IllegalArgumentException expected) { + assertEquals("Rank profile 'my_profile' is invalid: Could not import tensorflow model from tensorflow('" + + modelDirectory + "','serving_default','x'): Model does not have the specified outputs 'x'", + Exceptions.toMessageString(expected)); + } + } + +} 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 4dcf7523fd0..dba2bdbfbbf 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 @@ -1,61 +1,19 @@ // Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. package com.yahoo.searchdefinition.processing; -import com.yahoo.searchdefinition.RankProfile; -import com.yahoo.searchdefinition.RankProfileRegistry; -import com.yahoo.searchdefinition.Search; -import com.yahoo.searchdefinition.SearchBuilder; import com.yahoo.searchdefinition.parser.ParseException; import org.junit.Rule; import org.junit.Test; import org.junit.rules.ExpectedException; -import java.util.List; - -import static org.junit.Assert.assertEquals; - /** * @author geirst */ public class RankingExpressionWithTensorTestCase { - private static class SearchFixture { - RankProfileRegistry rankProfileRegistry = new RankProfileRegistry(); - Search search; - SearchFixture(String rankProfiles) throws ParseException { - SearchBuilder builder = new SearchBuilder(rankProfileRegistry); - String sdContent = "search test {\n" + - " document test {\n" + - " }\n" + - rankProfiles + - "\n" + - "}"; - builder.importString(sdContent); - builder.build(); - search = builder.getSearch(); - } - public void assertFirstPhaseExpression(String expExpression, String rankProfile) { - assertEquals(expExpression, getRankProfile(rankProfile).getFirstPhaseRanking().getRoot().toString()); - } - public void assertSecondPhaseExpression(String expExpression, String rankProfile) { - assertEquals(expExpression, getRankProfile(rankProfile).getSecondPhaseRanking().getRoot().toString()); - } - public void assertRankProperty(String expValue, String name, String rankProfile) { - List<RankProfile.RankProperty> rankPropertyList = getRankProfile(rankProfile).getRankPropertyMap().get(name); - assertEquals(1, rankPropertyList.size()); - assertEquals(expValue, rankPropertyList.get(0).getValue()); - } - public void assertMacro(String expExpression, String macroName, String rankProfile) { - assertEquals(expExpression, getRankProfile(rankProfile).getMacros().get(macroName).getRankingExpression().getRoot().toString()); - } - private RankProfile getRankProfile(String rankProfile) { - return rankProfileRegistry.getRankProfile(search, rankProfile).compile(); - } - } - @Test public void requireThatSingleLineConstantTensorAndTypeCanBeParsed() throws ParseException { - SearchFixture f = new SearchFixture( + RankProfileSearchFixture f = new RankProfileSearchFixture( " rank-profile my_profile {\n" + " first-phase {\n" + " expression: sum(my_tensor)\n" + @@ -74,7 +32,7 @@ public class RankingExpressionWithTensorTestCase { @Test public void requireThatMultiLineConstantTensorAndTypeCanBeParsed() throws ParseException { - SearchFixture f = new SearchFixture( + RankProfileSearchFixture f = new RankProfileSearchFixture( " rank-profile my_profile {\n" + " first-phase {\n" + " expression: sum(my_tensor)\n" + @@ -96,7 +54,7 @@ public class RankingExpressionWithTensorTestCase { @Test public void requireThatConstantTensorsCanBeUsedInSecondPhaseExpression() throws ParseException { - SearchFixture f = new SearchFixture( + RankProfileSearchFixture f = new RankProfileSearchFixture( " rank-profile my_profile {\n" + " second-phase {\n" + " expression: sum(my_tensor)\n" + @@ -114,7 +72,7 @@ public class RankingExpressionWithTensorTestCase { @Test public void requireThatConstantTensorsCanBeUsedInInheritedRankProfile() throws ParseException { - SearchFixture f = new SearchFixture( + RankProfileSearchFixture f = new RankProfileSearchFixture( " rank-profile parent {\n" + " constants {\n" + " my_tensor {\n" + @@ -134,7 +92,7 @@ public class RankingExpressionWithTensorTestCase { @Test public void requireThatConstantTensorsCanBeUsedInMacro() throws ParseException { - SearchFixture f = new SearchFixture( + RankProfileSearchFixture f = new RankProfileSearchFixture( " rank-profile my_profile {\n" + " macro my_macro() {\n" + " expression: sum(my_tensor)\n" + @@ -156,7 +114,7 @@ public class RankingExpressionWithTensorTestCase { @Test public void requireThatCombinationOfConstantTensorsAndConstantValuesCanBeUsed() throws ParseException { - SearchFixture f = new SearchFixture( + RankProfileSearchFixture f = new RankProfileSearchFixture( " rank-profile my_profile {\n" + " first-phase {\n" + " expression: my_number_1 + sum(my_tensor) + my_number_2\n" + @@ -181,7 +139,7 @@ public class RankingExpressionWithTensorTestCase { public void requireThatInvalidTensorTypeSpecThrowsException() throws ParseException { exception.expect(IllegalArgumentException.class); exception.expectMessage("For constant tensor 'my_tensor' in rank profile 'my_profile': Illegal tensor type spec: Failed parsing element 'x' in type spec 'tensor(x)'"); - new SearchFixture( + new RankProfileSearchFixture( " rank-profile my_profile {\n" + " constants {\n" + " my_tensor {\n" + |