code: def test_describe_endpoint_response_contains_expected_attributes(
      sagemaker_client,
  ):
      model_name = "sample-model"
      create_sagemaker_model(
          sagemaker_client=sagemaker_client, model_name=model_name
      )
  
      endpoint_config_name = "sample-config"
      production_variants = [
          {
              "VariantName": "sample-variant",
              "ModelName": model_name,
              "InitialInstanceCount": 1,
              "InstanceType": "ml.m4.xlarge",
              "InitialVariantWeight": 1.0,
          },
      ]
      sagemaker_client.create_endpoint_config(
          EndpointConfigName=endpoint_config_name,
          ProductionVariants=production_variants,
      )
  
      endpoint_name = "sample-endpoint"
      sagemaker_client.create_endpoint(
          EndpointName=endpoint_name,
          EndpointConfigName=endpoint_config_name,
      )
  
      describe_endpoint_response = sagemaker_client.describe_endpoint(
          EndpointName=endpoint_name
      )
      assert "CreationTime" in describe_endpoint_response
      assert "LastModifiedTime" in describe_endpoint_response
      assert "EndpointArn" in describe_endpoint_response
      assert "EndpointStatus" in describe_endpoint_response
      assert "ProductionVariants" in describe_endpoint_response
  
imports: import boto3
  import pytest
  from tests.helper_functions import set_boto_credentials
  from tests.sagemaker.mock import mock_sagemaker
label_desc: Use image node_id 22 for calling a global function with example usage: test_describe_endpoint_response_contains_expected_attributes(sagemaker_client) without return types