code: def test_predict_triples(
      model: pykeen.models.Model,
      triples: AnyTriples,
      triples_factory: Optional[CoreTriplesFactory],
      batch_size: Optional[int],
  ):
      """Test triple scoring."""
      pack = pykeen.predict.predict_triples(
          model=model,
          triples=triples,
          triples_factory=triples_factory,
          batch_size=batch_size,
      )
      if not isinstance(
          triples, (torch.Tensor, numpy.ndarray)
      ) and isinstance(triples[0], str):
          num_triples = 1
      else:
          num_triples = len(triples)
      _check_score_pack(pack=pack, model=model, num_triples=num_triples)
  
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 8 for calling a global function with example usage: test_predict_triples(model, triples, triples_factory, batch_size) without return types