feat: Add target_model to support multi-model endpoints

Author: keerthanvasist

src/sagemaker/clarify.py

@@ -185,6 +185,7 @@ 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.
 
@@ -218,6 +219,8 @@ def __init__(
                 https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html.
             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
         """
         self.predictor_config = {
             "model_name": model_name,
@@ -261,6 +264,7 @@ 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,
@@ -258,6 +259,7 @@ def test_model_config():
         "content_type": content_type,
         "custom_attributes": custom_attributes,
         "accelerator_type": accelerator_type,
+        "target_model_name": target_model,
     }
     assert expected_config == model_config.get_predictor_config()