aglinxinyuan commented on code in PR #4827: URL: https://github.com/apache/texera/pull/4827#discussion_r3177854293
########## common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/SklearnOpDescRegistrySpec.scala: ########## @@ -0,0 +1,339 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you 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. + */ + +package org.apache.texera.amber.operator.sklearn + +import org.apache.texera.amber.operator.sklearn.training._ +import org.scalatest.flatspec.AnyFlatSpec + +/** + * Pins the wiring (Python import statement + user-friendly model name) for + * every concrete `SklearnClassifierOpDesc` and `SklearnTrainingOpDesc`. A + * typo in either string would silently misroute downstream UI labels and + * breakage of the generated Python pipeline. + */ +class SklearnOpDescRegistrySpec extends AnyFlatSpec { + + // --------------------------------------------------------------------------- + // Classifier registry (24 concrete SklearnClassifierOpDesc subclasses) + // --------------------------------------------------------------------------- + + private val classifierEntries: List[(SklearnClassifierOpDesc, String, String)] = List( + ( + new SklearnAdaptiveBoostingOpDesc(), + "from sklearn.ensemble import AdaBoostClassifier", + "Adaptive Boosting" + ), + (new SklearnBaggingOpDesc(), "from sklearn.ensemble import BaggingClassifier", "Bagging"), + ( + new SklearnBernoulliNaiveBayesOpDesc(), + "from sklearn.naive_bayes import BernoulliNB", + "Bernoulli Naive Bayes" + ), + ( + new SklearnComplementNaiveBayesOpDesc(), + "from sklearn.naive_bayes import ComplementNB", + "Complement Naive Bayes" + ), + ( + new SklearnDecisionTreeOpDesc(), + "from sklearn.tree import DecisionTreeClassifier", + "Decision Tree" + ), + (new SklearnExtraTreeOpDesc(), "from sklearn.tree import ExtraTreeClassifier", "Extra Tree"), + ( + new SklearnExtraTreesOpDesc(), + "from sklearn.ensemble import ExtraTreesClassifier", + "Extra Trees" + ), + ( + new SklearnGaussianNaiveBayesOpDesc(), + "from sklearn.naive_bayes import GaussianNB", + "Gaussian Naive Bayes" + ), + ( + new SklearnGradientBoostingOpDesc(), + "from sklearn.ensemble import GradientBoostingClassifier", + "Gradient Boosting" + ), + ( + new SklearnKNNOpDesc(), + "from sklearn.neighbors import KNeighborsClassifier", + "K-nearest Neighbors" + ), + ( + new SklearnLinearSVMOpDesc(), + "from sklearn.svm import LinearSVC", + "Linear Support Vector Machine" + ), + ( + new SklearnLogisticRegressionCVOpDesc(), + "from sklearn.linear_model import LogisticRegressionCV", + "Logistic Regression Cross Validation" + ), + ( + new SklearnLogisticRegressionOpDesc(), + "from sklearn.linear_model import LogisticRegression", + "Logistic Regression" + ), + ( + new SklearnMultiLayerPerceptronOpDesc(), + "from sklearn.neural_network import MLPClassifier", + "Multi-layer Perceptron" + ), + ( + new SklearnMultinomialNaiveBayesOpDesc(), + "from sklearn.naive_bayes import MultinomialNB", + "Multinomial Naive Bayes" + ), + ( + new SklearnNearestCentroidOpDesc(), + "from sklearn.neighbors import NearestCentroid", + "Nearest Centroid" + ), + ( + new SklearnPassiveAggressiveOpDesc(), + "from sklearn.linear_model import PassiveAggressiveClassifier", + "Passive Aggressive" + ), + ( + new SklearnPerceptronOpDesc(), + "from sklearn.linear_model import Perceptron", + "Linear Perceptron" + ), + ( + new SklearnProbabilityCalibrationOpDesc(), + "from sklearn.calibration import CalibratedClassifierCV", + "Probability Calibration" + ), + ( + new SklearnRandomForestOpDesc(), + "from sklearn.ensemble import RandomForestClassifier", + "Random Forest" + ), + ( + new SklearnRidgeCVOpDesc(), + "from sklearn.linear_model import RidgeClassifierCV", + "Ridge Regression Cross Validation" + ), + ( + new SklearnRidgeOpDesc(), + "from sklearn.linear_model import RidgeClassifier", + "Ridge Regression" + ), + ( + new SklearnSDGOpDesc(), + "from sklearn.linear_model import SGDClassifier", + "Stochastic Gradient Descent" + ), + (new SklearnSVMOpDesc(), "from sklearn.svm import SVC", "Support Vector Machine") + ) + + classifierEntries.foreach { + case (desc, expectedImport, expectedName) => + val cls = desc.getClass.getSimpleName + cls should s"return import statement '$expectedImport'" in { + assert(desc.getImportStatements == expectedImport) + } + it should s"return user-friendly model name '$expectedName'" in { + assert(desc.getUserFriendlyModelName == expectedName) + } + } + + "SklearnClassifierOpDesc base class" should "default to empty strings before subclass overrides" in { + val anonymous = new SklearnClassifierOpDesc {} + assert(anonymous.getImportStatements == "") + assert(anonymous.getUserFriendlyModelName == "") + } + + it should "embed the import statement into generatePythonCode for a concrete subclass" in { + val desc = new SklearnLogisticRegressionOpDesc() + desc.target = "y" + desc.countVectorizer = false + // `tfidfTransformer` is a val on the base class, defaults to false. + val code = desc.generatePythonCode() + assert(code.contains("from sklearn.linear_model import LogisticRegression")) + // Classifier OpDescs emit a UDFTableOperator pipeline. + assert(code.contains("ProcessTableOperator")) + } + + // --------------------------------------------------------------------------- + // Training registry (26 concrete SklearnTrainingOpDesc subclasses) + // --------------------------------------------------------------------------- + + private val trainingEntries: List[(SklearnTrainingOpDesc, String, String)] = List( + ( + new SklearnTrainingAdaptiveBoostingOpDesc(), + "from sklearn.ensemble import AdaBoostClassifier", + "Training: Adaptive Boosting" + ), + ( + new SklearnTrainingBaggingOpDesc(), + "from sklearn.ensemble import BaggingClassifier", + "Training: Bagging Training" // current source value (typo-style duplication preserved) Review Comment: Done in d37d1ae5e8 — corrected the `getUserFriendlyModelName` to `Training: Bagging` to match the rest of the SklearnTraining* registry pattern, and updated the spec expectation accordingly. -- This is an automated message from the Apache Git Service. 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