title: Attribute Error: pipeline object has not attribute transform
body: <p>I have built a logistic regression model using spark ml pipelines and saved it. I am trying to apply the pipeline on new set of records and receiving an error. My pipeline has vector assembler, standard scaler and logistic regression model in it.</p>
  
  <p>I tried <code>pipeline.transform</code> and received the below error</p>
  
  <blockquote>
    <p>AttributeError: 'Pipeline' object has no attribute 'transform'</p>
  </blockquote>
  
  <p>Below is the code   </p>
  
  <pre><code>from pyspark.ml import Pipeline
  pipelineModel = Pipeline.load("/user/userid/lr_pipe")
  scored_temp = pipelineModel.transform(combined_data_imputed_final)
  </code></pre>
  
  <p>Here is how I saved my pipeline</p>
  
  <pre><code>from pyspark.ml.classification import LogisticRegression
  
  vector = VectorAssembler(inputCols=final_features, outputCol="final_features")
  scaler = StandardScaler(inputCol="final_features", outputCol="final_scaled_features")
  lr = LogisticRegression(labelCol="label", featuresCol="final_scaled_features", maxIter=30)
  
  stages = [vector,scaler,lr]
  
  pipe = Pipeline(stages=stages)
  
  lrModel = pipe.fit(train_transformed_data_1).transform(train_transformed_data_1)
  pipe.save("lr_pipe")
  </code></pre>
  
  <p>I am expecting it to complete all the pipeline steps and score the records.</p>