class_docstr: Defines a pipeline for transforming sequence data.
  
  The input is assumed to be utf-8 encoded `str` (Python 3) or
  `unicode` (Python 2).
  
  Attributes:
      convert_token: The function to apply to input sequence data.
      pipes: The Pipelines that will be applid to input sequence
          data in order.
docstr: Apply _only_ the convert_token function of the current pipeline
  to the input. If the input is a list, a list with the results of
  applying the `convert_token` function to all input elements is
  returned.
  
  Arguments:
      x: The input to apply the convert_token function to.
      Positional arguments: Forwarded to the `convert_token` function
          of the current Pipeline.
docstr_tok: ["Apply","_only_","the","convert_token","function","of","the","current","pipeline","to","the","input",".","If","the","input","is","a","list",",","a","list","with","the","results","of","applying","the","`","convert_token","`","function","to","all","input","elements","is","returned",".","Arguments",":","x",":","The","input","to","apply","the","convert_token","function","to",".","Positional","arguments",":","Forwarded","to","the","`","convert_token","`","function","of","the","current","Pipeline","."]
code: def call(self, x, *args):
      """Apply _only_ the convert_token function of the current pipeline
      to the input. If the input is a list, a list with the results of
      applying the `convert_token` function to all input elements is
      returned.
  
      Arguments:
          x: The input to apply the convert_token function to.
          Positional arguments: Forwarded to the `convert_token` function
              of the current Pipeline.
      """
      if isinstance(x, list):
          return [self.convert_token(tok, *args) for tok in x]
      return self.convert_token(x, *args)
  
file_path: decanlp/text/torchtext/data/pipeline.py
label_desc: Use image node_id 3 for calling the Pipeline obj's underlying member method code with example usage: obj.call(x) and returns: self, unknown