code: def test_discover_facts():
      X = np.array(
          [
              ["a", "y", "b"],
              ["b", "y", "a"],
              ["a", "y", "c"],
              ["c", "y", "a"],
              ["a", "y", "d"],
              ["c", "y", "d"],
              ["b", "y", "c"],
              ["f", "y", "e"],
          ]
      )
      model = ScoringBasedEmbeddingModel(
          eta=5, k=10, scoring_type="ComplEx"
      )
  
      model.compile(optimizer="adam", loss="multiclass_nll")
  
      with pytest.raises(ValueError):
          discover_facts(X, model)
  
      model.fit(X, epochs=10, batch_size=3)
  
      with pytest.raises(ValueError):
          discover_facts(X, model, strategy="error")
  
      with pytest.raises(ValueError):
          discover_facts(
              X, model, strategy="random_uniform", target_rel="error"
          )
  
file_path: AmpliGraph/tests/ampligraph/discovery/test_discovery.py
imports: import numpy
  import pytest
  from sklearn.cluster import DBSCAN
  from ampligraph.discovery.discovery import discover_facts, generate_candidates, _setdiff2d, find_clusters, find_duplicates, query_topn
  from ampligraph.latent_features import ScoringBasedEmbeddingModel
label_desc: Use image node_id 1 for calling a global function with example usage: test_discover_facts() without return types