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 predict_h(
      self, rt_batch: torch.LongTensor, **kwargs
  ) -> torch.FloatTensor:  # noqa: D102
      return self._mask(
          scores=super().predict_h(rt_batch, **kwargs),
          batch=rt_batch,
          target=LABEL_HEAD,
          in_training=False,
      )
  
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 10 for calling the CooccurrenceFilteredModel obj's underlying member method code with example usage: obj.predict_h(rt_batch) and returns: self