IllegalArgumentException：MultilayerPerceptronClassifier _...参数求解器给出了无效的自动值
我相信我在我测试过的Spark 3.0.0，Scala 2.1.2中加载MultilayerPerceptronClassificationModel时发现了一个错误，该错误至少在Spark 2.4.3，Scala 2.11中不存在。
我正在databricks群集上使用pyspark并“从pyspark.ml.classification import MultilayerPerceptronClassificationModel”导入库
运行模型时= MultilayerPerceptronClassificationModel。（“负载”），然后进行建模。转换（df），出现以下错误：IllegalArgumentException：MultilayerPerceptronClassifier_8055d1368e78参数求解器给出了无效的自动值。
上给出的示例，可以轻松地复制此问题。然后添加保存模型，装入模型和转换语句，如下所示：
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)