class_docstr: A sampler that accounts for which entities co-occur with a relation.
  
  To generate a corrupted head entity for triple $(h, r, t)$, only those entities are considered which occur as a
  head entity in a triple with the relation $r$.
  
  .. warning:: With this type of sampler, filtering for false negatives is more important.
docstr: Instantiate the pseudo-typed negative sampler.
  
  :param mapped_triples:
      the positive training triples
  :param kwargs:
      Additional keyword based arguments passed to :class:`pykeen.sampling.NegativeSampler`.
code: def __init__(
      self,
      *,
      mapped_triples: MappedTriples,
      **kwargs,
  ):
      """
      Instantiate the pseudo-typed negative sampler.
  
      :param mapped_triples:
          the positive training triples
      :param kwargs:
          Additional keyword based arguments passed to :class:`pykeen.sampling.NegativeSampler`.
      """
      super().__init__(mapped_triples=mapped_triples, **kwargs)
      self.data, self.offsets = create_index(
          mapped_triples=mapped_triples,
          num_relations=self.num_relations,
      )
  
file_path: pykeen/src/pykeen/sampling/pseudo_type.py
imports: import itertools
  import logging
  from typing import Tuple
  import torch
  from .negative_sampler import NegativeSampler
  from ..typing import MappedTriples
  from ..utils import create_relation_to_entity_set_mapping
label_desc: Use image node_id 1 to create a new PseudoTypedNegativeSampler object from inherited base classes: NegativeSampler with example: obj = PseudoTypedNegativeSampler()