fix: Pop out ModelPackageName from pipeline definition

src/sagemaker/workflow/_utils.py

@@ -13,6 +13,7 @@
 """Scrapper utilities to support repacking of models."""
 from __future__ import absolute_import
 
+import logging
 import os
 import shutil
 import tarfile
@@ -37,6 +38,8 @@
 if TYPE_CHECKING:
     from sagemaker.workflow.step_collections import StepCollection
 
+logger = logging.getLogger(__name__)
+
 FRAMEWORK_VERSION = "0.23-1"
 INSTANCE_TYPE = "ml.m5.large"
 REPACK_SCRIPT = "_repack_model.py"
@@ -479,10 +482,19 @@ def arguments(self) -> RequestType:
 
             request_dict = get_create_model_package_request(**model_package_args)
         # these are not available in the workflow service and will cause rejection
+        warn_msg_template = (
+            "Popping out '%s' from the pipeline definition "
+            "since it will be overridden in pipeline execution time."
+        )
         if "CertifyForMarketplace" in request_dict:
             request_dict.pop("CertifyForMarketplace")
+            logger.warning(warn_msg_template, "CertifyForMarketplace")
         if "Description" in request_dict:
             request_dict.pop("Description")
+            logger.warning(warn_msg_template, "Description")
+        if "ModelPackageName" in request_dict:
+            request_dict.pop("ModelPackageName")
+            logger.warning(warn_msg_template, "ModelPackageName")
 
         return request_dict
 

tests/integ/sagemaker/workflow/test_model_steps.py

@@ -112,6 +112,7 @@ def test_pytorch_training_model_registration_and_creation_without_custom_inferen
         inference_instances=["ml.m5.xlarge"],
         transform_instances=["ml.m5.xlarge"],
         description="test-description",
+        model_package_name="model-pkg-name-will-be-popped-out",
     )
     step_model_regis = ModelStep(
         name="pytorch-register-model",

tests/unit/sagemaker/workflow/conftest.py

@@ -0,0 +1,75 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You
+# may not use this file except in compliance with the License. A copy of
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.
+from __future__ import absolute_import
+
+from unittest.mock import Mock, PropertyMock
+
+import pytest
+
+from sagemaker import Session
+from sagemaker.workflow.pipeline_context import PipelineSession
+
+REGION = "us-west-2"
+BUCKET = "my-bucket"
+ROLE = "DummyRole"
+IMAGE_URI = "fakeimage"
+
+
+@pytest.fixture(scope="module")
+def client():
+    """Mock client.
+
+    Considerations when appropriate:
+
+        * utilize botocore.stub.Stubber
+        * separate runtime client from client
+    """
+    client_mock = Mock()
+    client_mock._client_config.user_agent = (
+        "Boto3/1.14.24 Python/3.8.5 Linux/5.4.0-42-generic Botocore/1.17.24 Resource"
+    )
+    return client_mock
+
+
+@pytest.fixture(scope="module")
+def boto_session(client):
+    role_mock = Mock()
+    type(role_mock).arn = PropertyMock(return_value=ROLE)
+
+    resource_mock = Mock()
+    resource_mock.Role.return_value = role_mock
+
+    session_mock = Mock(region_name=REGION)
+    session_mock.resource.return_value = resource_mock
+    session_mock.client.return_value = client
+
+    return session_mock
+
+
+@pytest.fixture(scope="module")
+def pipeline_session(boto_session, client):
+    return PipelineSession(
+        boto_session=boto_session,
+        sagemaker_client=client,
+        default_bucket=BUCKET,
+    )
+
+
+@pytest.fixture(scope="module")
+def sagemaker_session(boto_session, client):
+    return Session(
+        boto_session=boto_session,
+        sagemaker_client=client,
+        sagemaker_runtime_client=client,
+        default_bucket=BUCKET,
+    )