code: def test_log_pipeline_parameters(self):
      if self.pipelineModel:
          self.logger.log_pipeline_parameters(self.pipelineModel)
      else:
          raise ValueError("Pipeline was not trained in test_monitor.")
  
file_path: spark-nlp/python/test/thirdparty/comet.py
imports: import unittest
  from sparknlp.base import *
  from sparknlp.annotator import *
  from sparknlp.logging.comet import CometLogger
  import comet_ml
  import os
  import glob
  from test.util import SparkContextForTest
label_desc: Use image node_id 4 for calling the CometTestSpec obj's underlying member method code with example usage: obj.test_log_pipeline_parameters() without return types