code: def _iter_predict_target_inputs() -> (
      Iterable[
          Tuple[
              pykeen.models.Model,
              int,
              int,
              int,
              Optional[CoreTriplesFactory],
              Optional[Sequence[int]],
          ]
      ]
  ):
      # comment: we only use id-based input, since the normalization has already been tested
      # create model
      factory = Nations().training
      model = pykeen.models.mocks.FixedModel(triples_factory=factory)
      for factory_ in (None, factory):
          # id-based head/relation/tail prediction, no restriction
          yield model, None, 0, 1, factory_, None
          yield model, 1, None, 2, factory_, None
          yield model, 0, 1, None, factory_, None
          # restriction by list of ints
          yield model, 0, 1, None, factory_, [0, 3, 7]
  
imports: from typing import Any, Collection, Iterable, MutableMapping, Optional, Sequence, Tuple, Union
  import numpy
  import pandas
  import pytest
  import torch
  import unittest_templates
  import pykeen.models
  import pykeen.models.mocks
  import pykeen.predict
  import pykeen.regularizers
  import pykeen.typing
  from pykeen.constants import COLUMN_LABELS
  from pykeen.datasets.nations import Nations
  from pykeen.triples.triples_factory import AnyTriples, CoreTriplesFactory, KGInfo
  from pykeen.utils import resolve_device
  from tests import cases
label_desc: Use image node_id 13 for calling a global function with example usage: _iter_predict_target_inputs() without return types