feat: Add target_model to support multi-model endpoints (aws#3215)

Author: keerthanvasist

src/sagemaker/clarify.py

@@ -200,6 +200,7 @@ def __init__(
         custom_attributes=None,
         accelerator_type=None,
         endpoint_name_prefix=None,
+        target_model=None,
     ):
         r"""Initializes a configuration of a model and the endpoint to be created for it.
 
@@ -234,6 +235,9 @@ def __init__(
                 for making inferences to the model.
             endpoint_name_prefix (str): The endpoint name prefix of a new endpoint. Must follow
                 pattern ``^[a-zA-Z0-9](-\*[a-zA-Z0-9]``.
+            target_model (str): Sets the target model name when using a multi-model endpoint. For
+                more information about multi-model endpoints, see
+                https://docs.aws.amazon.com/sagemaker/latest/dg/multi-model-endpoints.html
 
         Raises:
             ValueError: when the ``endpoint_name_prefix`` is invalid, ``accept_type`` is invalid,
@@ -281,6 +285,7 @@ def __init__(
             self.predictor_config["content_template"] = content_template
         _set(custom_attributes, "custom_attributes", self.predictor_config)
         _set(accelerator_type, "accelerator_type", self.predictor_config)
+        _set(target_model, "target_model", self.predictor_config)
 
     def get_predictor_config(self):
         """Returns part of the predictor dictionary of the analysis config."""

tests/unit/test_clarify.py

@@ -240,6 +240,7 @@ def test_model_config():
     accept_type = "text/csv"
     content_type = "application/jsonlines"
     custom_attributes = "c000b4f9-df62-4c85-a0bf-7c525f9104a4"
+    target_model = "target_model_name"
     accelerator_type = "ml.eia1.medium"
     model_config = ModelConfig(
         model_name=model_name,
@@ -249,6 +250,7 @@ def test_model_config():
         content_type=content_type,
         custom_attributes=custom_attributes,
         accelerator_type=accelerator_type,
+        target_model=target_model,
     )
     expected_config = {
         "model_name": model_name,
@@ -258,6 +260,7 @@ def test_model_config():
         "content_type": content_type,
         "custom_attributes": custom_attributes,
         "accelerator_type": accelerator_type,
+        "target_model": target_model,
     }
     assert expected_config == model_config.get_predictor_config()