class_docstr: Apply sequential transformations to input sample.
  Default generate transformed samples of combination number of contained
  transformations.
code: def __repr__(self):
      return "Pipeline_" + "_".join(
          [format(trans) for trans in self[:]]
      )
  
file_path: textflint/textflint/generation/transformation/pipeline.py
imports: from ..transformation import Transformation
label_desc: Use image node_id 2 for calling the Pipeline obj's underlying member method code with example usage: obj.__repr__() and returns: unknown