code: def test_validate_and_update_inference_response_wrong_input():
      cic = copy.copy(CLASSIFICATION_INFERENCE_CONTAINERS)
  
      with pytest.raises(ValueError) as excinfo:
          AutoML.validate_and_update_inference_response(
              inference_containers=cic,
              inference_response_keys=[
                  "wrong_key",
                  "wrong_label",
                  "probabilities",
                  "probability",
              ],
          )
      message = (
          "Requested inference output keys [wrong_key, wrong_label] are unsupported. "
          "The supported inference keys are [probability, probabilities, predicted_label, labels]"
      )
      assert message in str(excinfo.value)
  
imports: from __future__ import absolute_import
  import copy
  import pytest
  from mock import Mock, patch
  from sagemaker import AutoML, AutoMLJob, AutoMLInput, CandidateEstimator, PipelineModel
  from sagemaker.predictor import Predictor
  from sagemaker.session_settings import SessionSettings
  from sagemaker.workflow.functions import Join
  from tests.unit import SAGEMAKER_CONFIG_AUTO_ML, SAGEMAKER_CONFIG_TRAINING_JOB, _test_default_bucket_and_prefix_combinations, DEFAULT_S3_BUCKET_NAME, DEFAULT_S3_OBJECT_KEY_PREFIX_NAME
label_desc: Use image node_id 30 for calling a global function with example usage: test_validate_and_update_inference_response_wrong_input() without return types