code: def test_error_no_proba_provided(
      tweet_emotion_train_test_textdata,
      tweet_emotion_train_test_predictions,
  ):
      # Arrange
      _, test = tweet_emotion_train_test_textdata
      _, test_preds = tweet_emotion_train_test_predictions
      check = MetadataSegmentsPerformance()
  
      # Act & Assert
      assert_that(
          calling(check.run).with_args(test, predictions=test_preds),
          raises(
              DeepchecksNotSupportedError,
              "Predicted probabilities not supplied. The weak segment "
              "checks relies on cross entropy error that requires predicted "
              "probabilities, rather than only predicted classes.",
          ),
      )
  
file_path: deepchecks/tests/nlp/checks/model_evaluation/weak_segment_performance_test.py
imports: import numpy
  import pandas
  import pytest
  from hamcrest import assert_that, calling, close_to, equal_to, has_items, is_in, matches_regexp, raises
  from deepchecks.core.errors import DeepchecksNotSupportedError, NotEnoughSamplesError
  from deepchecks.nlp.checks import MetadataSegmentsPerformance, PropertySegmentsPerformance
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 1 for calling a global function with example usage: test_error_no_proba_provided(tweet_emotion_train_test_textdata, tweet_emotion_train_test_predictions) without return types