@@ -150,6 +150,40 @@ def test_inference_pipeline_model_deploy(sagemaker_session, cpu_instance_type):
150150 assert "Could not find model" in str (exception .value )
151151
152152
153+ @pytest .mark .release
154+ def test_inference_pipeline_model_register (sagemaker_session ):
155+ sparkml_data_path = os .path .join (DATA_DIR , "sparkml_model" )
156+ endpoint_name = unique_name_from_base ("test-inference-pipeline-deploy" )
157+ sparkml_model_data = sagemaker_session .upload_data (
158+ path = os .path .join (sparkml_data_path , "mleap_model.tar.gz" ),
159+ key_prefix = "integ-test-data/sparkml/model" ,
160+ )
161+
162+ sparkml_model = SparkMLModel (
163+ model_data = sparkml_model_data ,
164+ env = {"SAGEMAKER_SPARKML_SCHEMA" : SCHEMA },
165+ sagemaker_session = sagemaker_session ,
166+ )
167+
168+ model = PipelineModel (
169+ models = [sparkml_model ],
170+ role = "SageMakerRole" ,
171+ sagemaker_session = sagemaker_session ,
172+ name = endpoint_name ,
173+ )
174+ model_package_group_name = unique_name_from_base ("pipeline-model-package" )
175+ model_package = model .register (model_package_group_name = model_package_group_name )
176+ assert model_package .model_package_arn is not None
177+
178+ sagemaker_session .sagemaker_client .delete_model_package (
179+ ModelPackageName = model_package .model_package_arn
180+ )
181+
182+ sagemaker_session .sagemaker_client .delete_model_package_group (
183+ ModelPackageGroupName = model_package_group_name
184+ )
185+
186+
153187@pytest .mark .slow_test
154188@pytest .mark .flaky (reruns = 5 , reruns_delay = 2 )
155189def test_inference_pipeline_model_deploy_and_update_endpoint (
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