class_docstr: A model which filters predictions by co-occurence.
  
  ---
  citation:
      author: Berrendorf
      year: 2022
      link: https://github.com/pykeen/pykeen/pull/943
      github: pykeen/pykeen
code: def score_t(
      self, hr_batch: torch.LongTensor, **kwargs
  ) -> torch.FloatTensor:  # noqa: D102
      return self._mask(
          scores=self.base.score_t(hr_batch=hr_batch, **kwargs),
          batch=hr_batch,
          target=LABEL_TAIL,
          in_training=True,
      )
  
imports: from typing import Any, ClassVar, List, Mapping, Optional, Union
  import scipy.sparse
  import torch
  from class_resolver import HintOrType
  from docdata import parse_docdata
  from ..base import Model
  from ..baseline.utils import get_csr_matrix
  from ...constants import TARGET_TO_INDEX
  from ...triples.triples_factory import CoreTriplesFactory
  from ...typing import LABEL_HEAD, LABEL_RELATION, LABEL_TAIL, InductiveMode, MappedTriples, Target
  from ...utils import prepare_filter_triples
label_desc: Use image node_id 9 for calling the CooccurrenceFilteredModel obj's underlying member method code with example usage: obj.score_t(hr_batch) and returns: self