有什么方法可以从 PySpark PipelineModel 的各个阶段访问方法? [英] Any way to access methods from individual stages in PySpark PipelineModel?

问题描述

我创建了一个 PipelineModel 用于在 Spark 2.0 中执行 LDA(通过 PySpark API):

I've created a PipelineModel for doing LDA in Spark 2.0 (via PySpark API):

def create_lda_pipeline(minTokenLength=1, minDF=1, minTF=1, numTopics=10, seed=42, pattern='[\W]+'):
    """
    Create a pipeline for running an LDA model on a corpus. This function does not need data and will not actually do
    any fitting until invoked by the caller.
    Args:
        minTokenLength:
        minDF: minimum number of documents word is present in corpus
        minTF: minimum number of times word is found in a document
        numTopics:
        seed:
        pattern: regular expression to split words

    Returns:
        pipeline: class pyspark.ml.PipelineModel
    """
    reTokenizer = RegexTokenizer(inputCol="text", outputCol="tokens", pattern=pattern, minTokenLength=minTokenLength)
    cntVec = CountVectorizer(inputCol=reTokenizer.getOutputCol(), outputCol="vectors", minDF=minDF, minTF=minTF)
    lda = LDA(k=numTopics, seed=seed, optimizer="em", featuresCol=cntVec.getOutputCol())
    pipeline = Pipeline(stages=[reTokenizer, cntVec, lda])
    return pipeline

我想使用经过训练的模型和 LDAModel.logPerplexity() 方法计算数据集的困惑度，所以我尝试运行以下命令:

I want to calculate the perplexity on a dataset using the trained model with the LDAModel.logPerplexity() method, so I tried running the following:

try:
    training = get_20_newsgroups_data(test_or_train='test')
    pipeline = create_lda_pipeline(numTopics=20, minDF=3, minTokenLength=5)
    model = pipeline.fit(training)  # train model on training data
    testing = get_20_newsgroups_data(test_or_train='test')
    perplexity = model.logPerplexity(testing)
    pprint(perplexity)

这只会导致以下AttributeError:

'PipelineModel' object has no attribute 'logPerplexity'

我明白为什么会发生这个错误，因为 logPerplexity 方法属于 LDAModel，而不是 PipelineModel，但我想知道是否有从那个阶段访问方法的方法.

I understand why this error happens, since the logPerplexity method belongs to LDAModel, not PipelineModel, but I am wondering if there is a way to access the method from that stage.

推荐答案

管道中的所有转换器都存储在 stages 属性中.提取 stages，选择最后一个，你就可以开始了:

All transformers in the pipeline are stored in stages property. Extract stages, take the last one, and you're ready to go:

model.stages[-1].logPerplexity(testing)

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