code: def __init__(
      self,
      nlp,
      X_factory,
      mX_factory,
      term_idx_store,
      metadata_idx_store,
      term_doc_mat_fact,
  ):
      if nlp == chinese_nlp:
          raise Exception(
              "Chinese NLP not yet supported.  Preparse chinese documents, and use CorpusFromParsedDocuments or a similar class."
          )
      (
          self.X_factory,
          self.mX_factory,
          self.term_idx_store,
          self.metadata_idx_store,
          self.nlp,
      ) = (
          X_factory,
          mX_factory,
          term_idx_store,
          metadata_idx_store,
          nlp,
      )
      self._term_doc_mat_fact = term_doc_mat_fact
      self._text_col = self._term_doc_mat_fact._text_col
      self._clean_function = self._term_doc_mat_fact._clean_function
      self._verbose = self._term_doc_mat_fact._verbose
  
imports: import numpy
  import pandas
  from scattertext.AsianNLP import chinese_nlp
  from scattertext.CSRMatrixTools import CSRMatrixFactory
  from scattertext.TermDocMatrix import TermDocMatrix
  from scattertext.TermDocMatrixFactory import TermDocMatrixFactory
  from scattertext.TermDocMatrixWithoutCategories import TermDocMatrixWithoutCategories
  from scattertext.indexstore.IndexStore import IndexStore
label_desc: Use image node_id 1 to create a new ParsePipelineFactoryWithoutCategories object from inherited base classes: object with example: obj = ParsePipelineFactoryWithoutCategories(nlp, X_factory, mX_factory, term_idx_store, metadata_idx_store, term_doc_mat_fact)