Hi, I'm not sure if this is the right place to raise this, if not hopefully you can direct me to the right place.
I believe I have discovered a bug when loading MultilayerPerceptronClassificationModel in spark 3.0.0, scala 2.1.2 which I have tested and can see is not there in at least Spark 2.4.3, Scala 2.11. (I'm not sure if the Scala version is important). I am using pyspark on a databricks cluster and importing the library "from pyspark.ml.classification import MultilayerPerceptronClassificationModel" When running model=MultilayerPerceptronClassificationModel.("load") and then model. transform (df) I get the following error: IllegalArgumentException: MultilayerPerceptronClassifier_8055d1368e78 parameter solver given invalid value auto. This issue can be easily replicated by running the example given on the spark documents: http://spark.apache.org/docs/latest/ml-classification-regression.html#multilayer-perceptron-classifier Then adding a save model, load model and transform statement as such: from pyspark.ml.classification import MultilayerPerceptronClassifier from pyspark.ml.evaluation import MulticlassClassificationEvaluator # Load training data data = spark.read.format("libsvm")\ .load("data/mllib/sample_multiclass_classification_data.txt") # Split the data into train and test splits = data.randomSplit([0.6, 0.4], 1234) train = splits[0] test = splits[1] # specify layers for the neural network: # input layer of size 4 (features), two intermediate of size 5 and 4 # and output of size 3 (classes) layers = [4, 5, 4, 3] # create the trainer and set its parameters trainer = MultilayerPerceptronClassifier(maxIter=100, layers=layers, blockSize=128, seed=1234) # train the model model = trainer.fit(train) # compute accuracy on the test set result = model.transform(test) predictionAndLabels = result.select("prediction", "label") evaluator = MulticlassClassificationEvaluator(metricName="accuracy") print("Test set accuracy = " + str(evaluator.evaluate(predictionAndLabels))) from pyspark.ml.classification import MultilayerPerceptronClassifier, MultilayerPerceptronClassificationModel model.save(Save_location) model2. MultilayerPerceptronClassificationModel.load(Save_location) result_from_loaded = model2.transform(test)