有没有办法从PySpark PipelineModel中的各个阶段访问方法？

from pyspark.ml import Pipeline
from pyspark.ml.feature import StringIndexer, VectorAssembler
from pyspark.ml.classification import RandomForestClassifier

# 创建阶段
stringIndexer = StringIndexer(inputCol="category", outputCol="categoryIndex")
vectorAssembler = VectorAssembler(inputCols=["feature1", "feature2"], outputCol="features")
classifier = RandomForestClassifier(labelCol="label", featuresCol="features")

# 创建Pipeline
pipeline = Pipeline(stages=[stringIndexer, vectorAssembler, classifier])

# 训练PipelineModel
model = pipeline.fit(trainingData)

# 获取PipelineModel的阶段列表
stages = model.stages

# 遍历阶段列表，并访问各个阶段的方法
for stage in stages:
    if isinstance(stage, StringIndexer):
        # 访问StringIndexer的方法
        print(stage.getHandleInvalid())
    elif isinstance(stage, VectorAssembler):
        # 访问VectorAssembler的方法
        print(stage.getInputCols())
    elif isinstance(stage, RandomForestClassifier):
        # 访问RandomForestClassifier的方法
        print(stage.getNumTrees())