original_docstring: 
  			Fits the model for a corpus -- that is, computes all necessary utterance attributes, and fits the underlying `PhrasingMotifs` and `PromptTypes` models.
  
  			:param corpus: Corpus
  			:return: None
  		
docstring: Fits the model for a corpus -- that is, computes all necessary utterance attributes, and fits the underlying `PhrasingMotifs` and `PromptTypes` models.
docstring_tokens: Fits the model for a corpus -- that is computes all necessary utterance attributes and fits the underlying ` PhrasingMotifs ` and ` PromptTypes ` models .
code: def fit(self, corpus, y=None):
  		"""
  			Fits the model for a corpus -- that is, computes all necessary utterance attributes, and fits the underlying `PhrasingMotifs` and `PromptTypes` models.
  
  			:param corpus: Corpus
  			:return: None
  		"""
  
  		self.pipe.fit(corpus, 
  				pt_model__prompt_selector=self.prompt_selector, pt_model__reference_selector=self.reference_selector)
code_tokens: def fit ( self , corpus , y = None ) : self . pipe . fit ( corpus , pt_model__prompt_selector = self . prompt_selector , pt_model__reference_selector = self . reference_selector )
short_docstring: Fits the model for a corpus -- that is, computes all necessary utterance attributes, and fits the underlying `PhrasingMotifs` and `PromptTypes` models.
short_docstring_tokens: Fits the model for a corpus -- that is computes all necessary utterance attributes and fits the underlying ` PhrasingMotifs ` and ` PromptTypes ` models .
comment: """
  			Fits the model for a corpus -- that is, computes all necessary utterance attributes, and fits the underlying `PhrasingMotifs` and `PromptTypes` models.
  
  			:param corpus: Corpus
  			:return: None
  		"""