class_docstr: Creates stretched versions of the input NoteSequence.
class_docstr_tok: ["Creates","stretched","versions","of","the","input","NoteSequence","."]
docstr: Creates a StretchPipeline.
  
  Args:
    stretch_factors: A Python list of uniform stretch factors to apply.
    name: Pipeline name.
docstr_tok: ["Creates","a","StretchPipeline",".","Args",":","stretch_factors",":","A","Python","list","of","uniform","stretch","factors","to","apply",".","name",":","Pipeline","name","."]
code: def __init__(self, stretch_factors, name=None):
      """Creates a StretchPipeline.
  
      Args:
        stretch_factors: A Python list of uniform stretch factors to apply.
        name: Pipeline name.
      """
      super(StretchPipeline, self).__init__(name=name)
      self._stretch_factors = stretch_factors
  
imports: import copy
  from magenta.pipelines import pipeline
  from magenta.pipelines import statistics
  from note_seq import constants
  from note_seq import sequences_lib
  from note_seq.protobuf import music_pb2
  import tensorflow.compat.v1
label_desc: Use image node_id 1 to create a new StretchPipeline object from inherited base classes: NoteSequencePipeline with example: obj = StretchPipeline(stretch_factors, name)