我正在尝试将一个经过训练的模型保存到s3存储中，然后尝试通过pyspark.ml中的pipeline包加载和预测这个模型。下面是我如何保存模型的示例。

# stage_1 to stage_4 are some basic trasnformation on data one-hot encoding e.t.c
# define stage 5: logistic regression model
 stage_5 = LogisticRegression(featuresCol='features',labelCol='label')
 # SETUP THE PIPELINE
 regression_pipeline = Pipeline(stages= [stage_1, stage_2, stage_3, stage_4, stage_5])
 # fit the pipeline for the trainind data
 model = regression_pipeline.fit(dataFrame1)
 model_path ="s3://s3-dummy_path-orch/dummy models/pipeline_testing_1.model"
 model.save(model_path)

我能够成功地保存模型&在上面提到的模型路径上创建了两个文件夹
阶段
元数据。
然而，当我试图加载模型，它给了我以下的错误。

Traceback (most recent call last):
  File "/tmp/pythonScript_85ff2462_e087_4805_9f50_0c75fc4302e2958379757178872310.py", line 75, in <module>
    pipelineModel = Pipeline.load(model_path)
  File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/ml/util.py", line 362, in load
  File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/ml/pipeline.py", line 207, in load
  File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/ml/util.py", line 300, in load
  File "/usr/lib/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
  File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 79, in deco
pyspark.sql.utils.IllegalArgumentException: 'requirement failed: Error loading metadata: Expected class name org.apache.spark.ml.Pipeline but found class name org.apache.spark.ml.PipelineModel'

我正在尝试加载模型，如下所示：

from pyspark.ml import Pipeline
## same path used while #model.save in the above code snippet
model_path ="s3://s3-dummy_path-orch/dummy models/pipeline_testing_1.model" 
pipelineModel = Pipeline.load(model_path)

我怎样才能纠正这个问题呢？