class_docstr: Filter samples based on text length
  
  Example::
  
      sample 1: "I love textflint", score: 3
      sample 2: "I love textflint very much", score: 5
class_docstr_tok: ["Filter","samples","based","on","text","length","Example",":",":","sample","1",":","``","I","love","textflint","''",",","score",":","3","sample","2",":","``","I","love","textflint","very","much","''",",","score",":","5"]
code: def __init__(self, intervals=["0%", "20%"]):
      if intervals is None:
          raise ValueError(
              "Intervals should be initialized for LengthSubPopulation"
          )
      super().__init__(intervals=intervals)
  
imports: from ..subpopulation import SubPopulation
label_desc: Use image node_id 1 to create a new LengthSubPopulation object from inherited base classes: SubPopulation with example: obj = LengthSubPopulation(intervals)