class_docstr: A filterer for negative triples based on the Bloom filter.
  
  Pure PyTorch, a proper module which can be moved to GPU, and support batch-wise computation.
  
  .. seealso ::
      * https://github.com/hiway/python-bloom-filter/ - for calculation of sizes, and rough structure of code
      * https://github.com/skeeto/hash-prospector#two-round-functions - for parts of the hash function
code: def __repr__(self):  # noqa:D105
      return (
          f"{self.__class__.__name__}("
          f"error_rate={self.error_rate}, "
          f"size={self.bit_array.shape[0]}, "
          f"rounds={self.rounds}, "
          f"ideal_num_elements={self.ideal_num_elements}, "
          f")"
      )
  
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 2 for calling the BloomFilterer obj's underlying member method code with example usage: obj.__repr__() and returns: self, str, self, str, self, str, self, str, self, str