drop tagging functionality for now

Author: gwang111

src/sagemaker/inference_recommender/inference_recommender_mixin.py

@@ -30,10 +30,6 @@
 
 LOGGER = logging.getLogger("sagemaker")
 
-DEPLOYMENT_RECOMMENDATION_TAG = "PythonSDK-DeploymentRecommendation"
-
-RIGHT_SIZE_TAG = "PythonSDK-RightSize"
-
 
 class Phase:
     """Used to store phases of a traffic pattern to perform endpoint load testing.
@@ -222,7 +218,6 @@ def _update_params(
         explainer_config = kwargs["explainer_config"]
         inference_recommendation_id = kwargs["inference_recommendation_id"]
         inference_recommender_job_results = kwargs["inference_recommender_job_results"]
-        tags = kwargs["tags"]
         if inference_recommendation_id is not None:
             inference_recommendation = self._update_params_for_recommendation_id(
                 instance_type=instance_type,
@@ -243,10 +238,11 @@ def _update_params(
                 explainer_config,
             )
 
-        if inference_recommendation:
-            tags = self._add_client_type_tag(tags, inference_recommendation[2])
-            return (inference_recommendation[0], inference_recommendation[1], tags)
-        return (instance_type, initial_instance_count, tags)
+        return (
+            inference_recommendation
+            if inference_recommendation
+            else (instance_type, initial_instance_count)
+        )
 
     def _update_params_for_right_size(
         self,
@@ -310,7 +306,7 @@ def _update_params_for_right_size(
         initial_instance_count = self.inference_recommendations[0]["EndpointConfiguration"][
             "InitialInstanceCount"
         ]
-        return (instance_type, initial_instance_count, RIGHT_SIZE_TAG)
+        return (instance_type, initial_instance_count)
 
     def _update_params_for_recommendation_id(
         self,
@@ -410,7 +406,7 @@ def _update_params_for_recommendation_id(
                 raise ValueError("Must specify model recommendation id and instance count.")
             self.env.update(model_recommendation["Environment"])
             instance_type = model_recommendation["InstanceType"]
-            return (instance_type, initial_instance_count, DEPLOYMENT_RECOMMENDATION_TAG)
+            return (instance_type, initial_instance_count)
 
         # Update params based on default inference recommendation
         if bool(instance_type) != bool(initial_instance_count):
@@ -474,7 +470,7 @@ def _update_params_for_recommendation_id(
             "InitialInstanceCount"
         ]
 
-        return (instance_type, initial_instance_count, RIGHT_SIZE_TAG)
+        return (instance_type, initial_instance_count)
 
     def _convert_to_endpoint_configurations_json(
         self, hyperparameter_ranges: List[Dict[str, CategoricalParameter]]
@@ -614,9 +610,3 @@ def _search_recommendation(self, recommendation_list, inference_recommendation_i
             ),
             None,
         )
-
-    def _add_client_type_tag(self, tags, client_type):
-        """Tagging for Inference Recommender and Deployment Recommendations"""
-        client_type_tag = {"Key": "ClientType", "Value": client_type}
-        tags = tags.append(client_type_tag) if tags else [client_type_tag]
-        return tags

src/sagemaker/model.py

@@ -1234,7 +1234,7 @@ def deploy(
             inference_recommendation_id is not None
             or self.inference_recommender_job_results is not None
         ):
-            instance_type, initial_instance_count, tags = self._update_params(
+            instance_type, initial_instance_count = self._update_params(
                 instance_type=instance_type,
                 initial_instance_count=initial_instance_count,
                 accelerator_type=accelerator_type,
@@ -1243,7 +1243,6 @@ def deploy(
                 explainer_config=explainer_config,
                 inference_recommendation_id=inference_recommendation_id,
                 inference_recommender_job_results=self.inference_recommender_job_results,
-                tags=tags,
             )
 
         is_async = async_inference_config is not None
@@ -1738,10 +1737,10 @@ def _create_sagemaker_model(self, *args, **kwargs):  # pylint: disable=unused-ar
 
         Args:
             args: Positional arguments coming from the caller. This class does not require
-                any but will look for tags in the 3rd parameter.
+                any so they are ignored.
 
             kwargs: Keyword arguments coming from the caller. This class does not require
-                any but will search for tags if not in args.
+                any so they are ignored.
         """
         if self.algorithm_arn:
             # When ModelPackage is created using an algorithm_arn we need to first
@@ -1763,17 +1762,12 @@ def _create_sagemaker_model(self, *args, **kwargs):  # pylint: disable=unused-ar
         self._ensure_base_name_if_needed(model_package_name.split("/")[-1])
         self._set_model_name_if_needed()
 
-        # If tags are in args, it must be the 3rd param
-        # If not, then check kwargs and set to either tags or None
-        tags = args[2] if len(args) >= 3 else kwargs.get("tags")
-
         self.sagemaker_session.create_model(
             self.name,
             self.role,
             container_def,
             vpc_config=self.vpc_config,
             enable_network_isolation=self.enable_network_isolation(),
-            tags=tags,
         )
 
     def _ensure_base_name_if_needed(self, base_name):

tests/unit/sagemaker/inference_recommender/test_inference_recommender_mixin.py

@@ -181,13 +181,6 @@
     "ModelPackageName": MODEL_PACKAGE_ARN,
 }
 
-IR_TAGS = [
-    {
-        "Key": "ClientType",
-        "Value": "PythonSDK-RightSize",
-    }
-]
-
 
 @pytest.fixture()
 def sagemaker_session():
@@ -592,7 +585,6 @@ def test_deploy_right_size_with_model_package_succeeds(
         IR_MODEL_PACKAGE_CONTAINER_DEF,
         vpc_config=None,
         enable_network_isolation=False,
-        tags=IR_TAGS,
     )
 
     sagemaker_session.endpoint_from_production_variants.assert_called_with(
@@ -602,7 +594,7 @@ def test_deploy_right_size_with_model_package_succeeds(
         kms_key=None,
         name="ir-endpoint-test",
         production_variants=IR_PRODUCTION_VARIANTS,
-        tags=IR_TAGS,
+        tags=None,
         wait=True,
     )
 
@@ -623,7 +615,6 @@ def test_deploy_right_size_with_both_overrides_succeeds(
         IR_MODEL_PACKAGE_CONTAINER_DEF,
         vpc_config=None,
         enable_network_isolation=False,
-        tags=None,
     )
 
     sagemaker_session.endpoint_from_production_variants.assert_called_with(
@@ -680,7 +671,6 @@ def test_deploy_right_size_serverless_override(sagemaker_session, default_right_
         IR_MODEL_PACKAGE_CONTAINER_DEF,
         vpc_config=None,
         enable_network_isolation=False,
-        tags=None,
     )
 
     sagemaker_session.endpoint_from_production_variants.assert_called_with(
@@ -713,7 +703,6 @@ def test_deploy_right_size_async_override(sagemaker_session, default_right_sized
         IR_MODEL_PACKAGE_CONTAINER_DEF,
         vpc_config=None,
         enable_network_isolation=False,
-        tags=None,
     )
 
     sagemaker_session.endpoint_from_production_variants.assert_called_with(
@@ -756,7 +745,6 @@ def test_deploy_right_size_explainer_config_override(sagemaker_session, default_
         IR_MODEL_PACKAGE_CONTAINER_DEF,
         vpc_config=None,
         enable_network_isolation=False,
-        tags=None,
     )
 
     sagemaker_session.endpoint_from_production_variants.assert_called_with(

tests/unit/sagemaker/model/test_deploy.py

@@ -45,8 +45,6 @@
     IR_COMPILATION_CONTAINER_DEF,
     IR_MODEL_PACKAGE_CONTAINER_DEF,
     IR_COMPILATION_MODEL_PACKAGE_CONTAINER_DEF,
-    IR_TAGS,
-    DEPLOYMENT_RECOMMENDATION_TAGS,
 )
 from tests.unit.sagemaker.inference_recommender.constructs import (
     create_inference_recommendations_job_default_with_model_name,
@@ -649,7 +647,6 @@ def test_deploy_with_recommendation_id_with_model_pkg_arn(name_from_base, sagema
         IR_MODEL_PACKAGE_CONTAINER_DEF,
         vpc_config=None,
         enable_network_isolation=False,
-        tags=IR_TAGS,
     )
 
     assert model_package.model_package_arn == IR_MODEL_PACKAGE_VERSION_ARN
@@ -682,7 +679,7 @@ def test_deploy_with_recommendation_id_with_model_name(name_from_base, sagemaker
         container_defs=IR_CONTAINER_DEF,
         vpc_config=None,
         enable_network_isolation=False,
-        tags=IR_TAGS,
+        tags=None,
     )
 
     assert model.model_data == IR_MODEL_DATA
@@ -718,7 +715,6 @@ def test_deploy_with_recommendation_id_with_model_pkg_arn_and_compilation(
         IR_COMPILATION_MODEL_PACKAGE_CONTAINER_DEF,
         vpc_config=None,
         enable_network_isolation=False,
-        tags=IR_TAGS,
     )
 
     assert model_package.model_data == IR_COMPILATION_MODEL_DATA
@@ -753,7 +749,7 @@ def mock_describe_compilation_job(CompilationJobName):
         container_defs=IR_COMPILATION_CONTAINER_DEF,
         vpc_config=None,
         enable_network_isolation=False,
-        tags=IR_TAGS,
+        tags=None,
     )
 
     assert model.model_data == IR_COMPILATION_MODEL_DATA
@@ -812,7 +808,7 @@ def test_deploy_with_valid_model_recommendation_id(name_from_base, sagemaker_ses
         container_defs=DEPLOYMENT_RECOMMENDATION_CONTAINER_DEF,
         vpc_config=None,
         enable_network_isolation=False,
-        tags=DEPLOYMENT_RECOMMENDATION_TAGS,
+        tags=None,
     )
 
     assert model.model_data == IR_MODEL_DATA

tests/unit/sagemaker/model/test_model_package.py

@@ -115,7 +115,6 @@ def test_create_sagemaker_model_uses_model_name(name_from_base, sagemaker_sessio
         {"ModelPackageName": model_package_name},
         vpc_config=None,
         enable_network_isolation=False,
-        tags=None,
     )
 
 
@@ -142,7 +141,6 @@ def test_create_sagemaker_model_include_environment_variable(sagemaker_session):
         {"ModelPackageName": model_package_name, "Environment": environment},
         vpc_config=None,
         enable_network_isolation=False,
-        tags=None,
     )