class_docstr: A pair of predicted scores and corresponding uncertainty.
  
  Since the uncertainty scores come from Monte-Carlo dropout, they are guaranteed to be non-negative
  with larger scores indicating higher uncertainty.
class_docstr_tok: ["A","pair","of","predicted","scores","and","corresponding","uncertainty",".","Since","the","uncertainty","scores","come","from","Monte-Carlo","dropout",",","they","are","guaranteed","to","be","non-negative","with","larger","scores","indicating","higher","uncertainty","."]
docstr: Make an instance from scores.
docstr_tok: ["Make","an","instance","from","scores","."]
code: def from_scores(cls, scores: torch.Tensor):
      """Make an instance from scores."""
      return cls(
          score=scores.mean(dim=0), uncertainty=scores.var(dim=0)
      )
  
file_path: pykeen/src/pykeen/models/uncertainty.py
imports: from typing import Callable, NamedTuple, Optional
  import torch
  from .base import Model
  from ..typing import InductiveMode
  from ..utils import get_dropout_modules
label_desc: Use image node_id 1 for calling the UncertainPrediction obj's underlying member method code with example usage: obj.from_scores(cls, scores) and returns: cls