class_docstr: Compute the Sorensen distance between the two sequences.
  They should contain hashable items.
  The return value is a float between 0 and 1, where 0 means equal,
  and 1 totally different.
  
  https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient
  https://github.com/Yomguithereal/talisman/blob/master/src/metrics/dice.js
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code: def __call__(self, *sequences: Sequence) -> float:
      result = self.quick_answer(*sequences)
      if result is not None:
          return result
  
      sequences = self._get_counters(*sequences)  # sets
      count = sum(self._count_counters(s) for s in sequences)
      intersection = self._intersect_counters(*sequences)  # set
      intersection = self._count_counters(intersection)  # int
      return 2.0 * intersection / count
  
imports: from __future__ import annotations
  from functools import reduce
  from itertools import islice, permutations, repeat
  from math import log
  from typing import Sequence
  from .base import Base, BaseSimilarity
  from .edit_based import DamerauLevenshtein
label_desc: Use image node_id 3 for calling the Sorensen obj's underlying member method code with example usage: obj.__call__() and returns: unknown, result