code: def test_update_endpoint_no_one_default_model_name_with_instance_type_and_count():
      sagemaker_session = empty_sagemaker_session()
      predictor = Predictor(
          ENDPOINT, sagemaker_session=sagemaker_session
      )
  
      with pytest.raises(ValueError) as exception:
          predictor.update_endpoint(
              initial_instance_count=2, instance_type="ml.c4.xlarge"
          )
  
      assert (
          "Unable to choose a default model for a new EndpointConfig"
          in str(exception.value)
      )
  
imports: from __future__ import absolute_import
  import io
  import json
  import pytest
  from mock import Mock, call, patch
  from sagemaker.deserializers import CSVDeserializer, PandasDeserializer
  from sagemaker.enums import EndpointType
  from sagemaker.model_monitor.model_monitoring import DEFAULT_REPOSITORY_NAME
  from sagemaker.predictor import Predictor
  from sagemaker.serializers import JSONSerializer, CSVSerializer
  from sagemaker.compute_resource_requirements.resource_requirements import ResourceRequirements
label_desc: Use image node_id 15 for calling a global function with example usage: test_update_endpoint_no_one_default_model_name_with_instance_type_and_count() without return types