code: def _make_distribution(self, scores: np.ndarray) -> np.ndarray:
      rank = rankdata(-scores)
      weights = rank ** (-1 / self.temperature)
      normalized_weights: np.ndarray = weights / weights.sum()
      return normalized_weights
  
imports: import types
  import numpy
  import structlog
  from scipy.special import softmax
  from scipy.stats import rankdata
  from baal.active.heuristics import AbstractHeuristic, Sequence
label_desc: Use image node_id 2 for calling the RankBasedSampling obj's underlying member method code with example usage: obj._make_distribution(scores) and returns: normalized_weights