JumpStart Gated Model Support in ModelBuilder Local Modes

src/sagemaker/serve/builder/jumpstart_builder.py

@@ -443,6 +443,11 @@ def _build_for_jumpstart(self):
 
         logger.info("JumpStart ID %s is packaged with Image URI: %s", self.model, image_uri)
 
+        if self._is_gated_model(pysdk_model) and self.mode != Mode.SAGEMAKER_ENDPOINT:
+            raise ValueError(
+                "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
+            )
+
         if "djl-inference" in image_uri:
             logger.info("Building for DJL JumpStart Model ID...")
             self.model_server = ModelServer.DJL_SERVING
@@ -469,3 +474,19 @@ def _build_for_jumpstart(self):
             )
 
         return self.pysdk_model
+
+    def _is_gated_model(self, model) -> bool:
+        """Determine if ``this`` Model is Gated
+
+        Args:
+            model (Model): Jumpstart Model
+        Returns:
+            bool: ``True`` if ``this`` Model is Gated
+        """
+        s3_uri = model.model_data
+        if isinstance(s3_uri, dict):
+            s3_uri = s3_uri.get("S3DataSource").get("S3Uri")
+
+        if s3_uri is None:
+            return False
+        return "private" in s3_uri

tests/integ/sagemaker/serve/test_serve_js_happy.py

@@ -31,15 +31,15 @@
 SAMPLE_RESPONSE = [
     {"generated_text": "Hello, I'm a language model, and I'm here to help you with your English."}
 ]
-JS_MODEL_ID = "huggingface-textgeneration1-gpt-neo-125m-fp16"
+JS_GATED_MODEL_ID = "meta-textgeneration-llama-2-7b-f"
 ROLE_NAME = "SageMakerRole"
 
 
 @pytest.fixture
 def happy_model_builder(sagemaker_session):
     iam_client = sagemaker_session.boto_session.client("iam")
     return ModelBuilder(
-        model=JS_MODEL_ID,
+        model=JS_GATED_MODEL_ID,
         schema_builder=SchemaBuilder(SAMPLE_PROMPT, SAMPLE_RESPONSE),
         role_arn=iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"],
         sagemaker_session=sagemaker_session,
@@ -59,7 +59,9 @@ def test_happy_tgi_sagemaker_endpoint(happy_model_builder, gpu_instance_type):
     with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
         try:
             logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
-            predictor = model.deploy(instance_type=gpu_instance_type, endpoint_logging=False)
+            predictor = model.deploy(
+                instance_type=gpu_instance_type, endpoint_logging=False, accept_eula=True
+            )
             logger.info("Endpoint successfully deployed.")
 
             updated_sample_input = happy_model_builder.schema_builder.sample_input

tests/unit/sagemaker/serve/builder/test_js_builder.py

@@ -67,6 +67,19 @@
     "123456789712.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.24.0-neuronx-sdk2.14.1"
 )
 
+mock_model_data = {
+    "S3DataSource": {
+        "S3Uri": "s3://jumpstart-private-cache-prod-us-west-2/huggingface-llm/huggingface-llm-zephyr-7b-gemma"
+        "/artifacts/inference-prepack/v1.0.0/",
+        "S3DataType": "S3Prefix",
+        "CompressionType": "None",
+    }
+}
+mock_model_data_str = (
+    "s3://jumpstart-private-cache-prod-us-west-2/huggingface-llm/huggingface-llm-zephyr-7b-gemma"
+    "/artifacts/inference-prepack/v1.0.0/"
+)
+
 
 class TestJumpStartBuilder(unittest.TestCase):
     @patch("sagemaker.serve.builder.jumpstart_builder._capture_telemetry", side_effect=None)
@@ -527,3 +540,101 @@ def test_tune_for_djl_js_endpoint_mode_ex(
 
         tuned_model = model.tune()
         assert tuned_model == model
+
+    @patch("sagemaker.serve.builder.jumpstart_builder._capture_telemetry", side_effect=None)
+    @patch(
+        "sagemaker.serve.builder.jumpstart_builder.JumpStart._is_jumpstart_model_id",
+        return_value=True,
+    )
+    @patch(
+        "sagemaker.serve.builder.jumpstart_builder.JumpStart._create_pre_trained_js_model",
+        return_value=MagicMock(),
+    )
+    @patch(
+        "sagemaker.serve.builder.jumpstart_builder.prepare_tgi_js_resources",
+        return_value=({"model_type": "t5", "n_head": 71}, True),
+    )
+    @patch("sagemaker.serve.builder.jumpstart_builder._get_ram_usage_mb", return_value=1024)
+    @patch(
+        "sagemaker.serve.builder.jumpstart_builder._get_nb_instance", return_value="ml.g5.24xlarge"
+    )
+    def test_js_gated_model_in_endpoint_mode(
+        self,
+        mock_get_nb_instance,
+        mock_get_ram_usage_mb,
+        mock_prepare_for_tgi,
+        mock_pre_trained_model,
+        mock_is_jumpstart_model,
+        mock_telemetry,
+    ):
+        builder = ModelBuilder(
+            model="facebook/galactica-mock-model-id",
+            schema_builder=mock_schema_builder,
+            mode=Mode.SAGEMAKER_ENDPOINT,
+        )
+
+        mock_pre_trained_model.return_value.image_uri = mock_tgi_image_uri
+        mock_pre_trained_model.return_value.model_data = mock_model_data
+
+        model = builder.build()
+
+        assert model is not None
+
+    @patch("sagemaker.serve.builder.jumpstart_builder._capture_telemetry", side_effect=None)
+    @patch(
+        "sagemaker.serve.builder.jumpstart_builder.JumpStart._is_jumpstart_model_id",
+        return_value=True,
+    )
+    @patch(
+        "sagemaker.serve.builder.jumpstart_builder.JumpStart._create_pre_trained_js_model",
+        return_value=MagicMock(),
+    )
+    def test_js_gated_model_in_local_mode(
+        self,
+        mock_pre_trained_model,
+        mock_is_jumpstart_model,
+        mock_telemetry,
+    ):
+        builder = ModelBuilder(
+            model="huggingface-llm-zephyr-7b-gemma",
+            schema_builder=mock_schema_builder,
+            mode=Mode.LOCAL_CONTAINER,
+        )
+
+        mock_pre_trained_model.return_value.image_uri = mock_tgi_image_uri
+        mock_pre_trained_model.return_value.model_data = mock_model_data_str
+
+        self.assertRaisesRegex(
+            ValueError,
+            "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode.",
+            lambda: builder.build(),
+        )
+
+    @patch("sagemaker.serve.builder.jumpstart_builder._capture_telemetry", side_effect=None)
+    @patch(
+        "sagemaker.serve.builder.jumpstart_builder.JumpStart._is_jumpstart_model_id",
+        return_value=True,
+    )
+    @patch(
+        "sagemaker.serve.builder.jumpstart_builder.JumpStart._create_pre_trained_js_model",
+        return_value=MagicMock(),
+    )
+    def test_js_gated_model_ex(
+        self,
+        mock_pre_trained_model,
+        mock_is_jumpstart_model,
+        mock_telemetry,
+    ):
+        builder = ModelBuilder(
+            model="huggingface-llm-zephyr-7b-gemma",
+            schema_builder=mock_schema_builder,
+            mode=Mode.LOCAL_CONTAINER,
+        )
+
+        mock_pre_trained_model.return_value.image_uri = mock_tgi_image_uri
+        mock_pre_trained_model.return_value.model_data = None
+
+        self.assertRaises(
+            ValueError,
+            lambda: builder.build(),
+        )