code: def test_map_k_too_big(targets, test_implicit_predicted_scores):
      user_ids = np.arange(test_implicit_predicted_scores.shape[0])
  
      with pytest.raises(ValueError):
          mapk(
              targets=targets,
              user_ids=user_ids,
              preds=test_implicit_predicted_scores[user_ids, :],
              k=(targets.shape[1] + 1),
          )
  
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 9 for calling a global function with example usage: test_map_k_too_big(targets, test_implicit_predicted_scores) without return types