code: def test_bad_explicit_evaluate_in_batches_with_implicit_data(
      test_implicit_interactions,
  ):
      with pytest.raises(ValueError):
          explicit_evaluate_in_batches(
              metric_list=[torchmetrics.MeanSquaredError()],
              test_interactions=test_implicit_interactions,
              model="test_model",
          )
  
imports: import copy
  from functools import partial
  import re
  from unittest import mock
  import numpy
  import pytest
  from sklearn.metrics import roc_auc_score
  import torch
  import torchmetrics
  from collie.metrics import _get_evaluate_in_batches_device, _get_labels, _get_user_item_pairs, auc, evaluate_in_batches, explicit_evaluate_in_batches, get_preds, mapk, mrr
label_desc: Use image node_id 13 for calling a global function with example usage: test_bad_explicit_evaluate_in_batches_with_implicit_data(test_implicit_interactions) without return types