class_docstr: A filterer using Python sets for filtering.
  
  This filterer is expected to be rather slow due to the conversion from torch long tensors to Python tuples. It can
  still serve as a baseline for performance comparison.
docstr: Initialize the filterer.
  
  :param mapped_triples:
      The ID-based triples.
docstr_tok: ["Initialize","the","filterer",".",":","param","mapped_triples",":","The","ID-based","triples","."]
code: def __init__(self, mapped_triples: MappedTriples):
      """Initialize the filterer.
  
      :param mapped_triples:
          The ID-based triples.
      """
      super().__init__()
      # store set of triples
      self.triples = triple_tensor_to_set(mapped_triples)
  
imports: import math
  from abc import abstractmethod
  from typing import Iterable
  import torch
  from class_resolver import ClassResolver
  from torch import nn
  from ..typing import MappedTriples
  from ..utils import triple_tensor_to_set
label_desc: Use image node_id 1 to create a new PythonSetFilterer object from inherited base classes: Filterer with example: obj = PythonSetFilterer(mapped_triples)