use jumpstart deployment config image as default optimization image

src/sagemaker/serve/builder/jumpstart_builder.py

@@ -829,7 +829,13 @@ def _optimize_for_jumpstart(
             self.pysdk_model._enable_network_isolation = False
 
         if quantization_config or sharding_config or is_compilation:
-            return create_optimization_job_args
+            # only apply default image for vLLM usecases.
+            # vLLM does not support compilation for now so skip on compilation
+            return (
+                create_optimization_job_args
+                if is_compilation
+                else self._set_optimization_image_default(create_optimization_job_args)
+            )
         return None
 
     def _is_gated_model(self, model=None) -> bool:
@@ -986,3 +992,28 @@ def _get_neuron_model_env_vars(
                     )
                     return job_model.env
         return None
+
+    def _set_optimization_image_default(
+        self, create_optimization_job_args: Dict[str, Any]
+    ) -> Dict[str, Any]:
+        """Defaults the optimization image to the JumpStart deployment config default
+
+        Args:
+            create_optimization_job_args (Dict[str, Any]): create optimization job request
+
+        Returns:
+            Dict[str, Any]: create optimization job request with image uri default
+        """
+
+        for optimization_config in create_optimization_job_args.get("OptimizationConfigs"):
+            if optimization_config.get("ModelQuantizationConfig"):
+                model_quantization_config = optimization_config.get("ModelQuantizationConfig")
+                if not model_quantization_config.get("Image"):
+                    model_quantization_config["Image"] = self.pysdk_model.init_kwargs["image_uri"]
+
+            if optimization_config.get("ModelShardingConfig"):
+                model_sharding_config = optimization_config.get("ModelShardingConfig")
+                if not model_sharding_config.get("Image"):
+                    model_sharding_config["Image"] = self.pysdk_model.init_kwargs["image_uri"]
+
+        return create_optimization_job_args

tests/integ/sagemaker/serve/test_serve_js_deep_unit_tests.py

@@ -32,6 +32,8 @@ def test_js_model_with_optimize_speculative_decoding_config_gated_requests_are_e
         iam_client = sagemaker_session.boto_session.client("iam")
         role_arn = iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"]
 
+        sagemaker_session.sagemaker_client.create_optimization_job = MagicMock()
+
         schema_builder = SchemaBuilder("test", "test")
         model_builder = ModelBuilder(
             model="meta-textgeneration-llama-3-1-8b-instruct",
@@ -50,6 +52,8 @@ def test_js_model_with_optimize_speculative_decoding_config_gated_requests_are_e
             accept_eula=True,
         )
 
+        assert not sagemaker_session.sagemaker_client.create_optimization_job.called
+
         optimized_model.deploy()
 
         mock_create_model.assert_called_once_with(
@@ -126,6 +130,13 @@ def test_js_model_with_optimize_sharding_and_resource_requirements_requests_are_
             accept_eula=True,
         )
 
+        assert (
+            sagemaker_session.sagemaker_client.create_optimization_job.call_args_list[0][1][
+                "OptimizationConfigs"
+            ][0]["ModelShardingConfig"]["Image"]
+            is not None
+        )
+
         optimized_model.deploy(
             resources=ResourceRequirements(requests={"memory": 196608, "num_accelerators": 8})
         )
@@ -206,6 +217,13 @@ def test_js_model_with_optimize_quantization_on_pre_optimized_model_requests_are
             accept_eula=True,
         )
 
+        assert (
+            sagemaker_session.sagemaker_client.create_optimization_job.call_args_list[0][1][
+                "OptimizationConfigs"
+            ][0]["ModelQuantizationConfig"]["Image"]
+            is not None
+        )
+
         optimized_model.deploy()
 
         mock_create_model.assert_called_once_with(

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

@@ -1166,6 +1166,7 @@ def test_optimize_quantize_for_jumpstart(
         mock_pysdk_model.image_uri = mock_tgi_image_uri
         mock_pysdk_model.list_deployment_configs.return_value = DEPLOYMENT_CONFIGS
         mock_pysdk_model.deployment_config = DEPLOYMENT_CONFIGS[0]
+        mock_pysdk_model.init_kwargs = {"image_uri": "mock_js_image"}
 
         sample_input = {
             "inputs": "The diamondback terrapin or simply terrapin is a species "
@@ -1201,6 +1202,9 @@ def test_optimize_quantize_for_jumpstart(
         )
 
         self.assertIsNotNone(out_put)
+        self.assertEqual(
+            out_put["OptimizationConfigs"][0]["ModelQuantizationConfig"]["Image"], "mock_js_image"
+        )
 
     @patch("sagemaker.serve.builder.jumpstart_builder._capture_telemetry", side_effect=None)
     @patch.object(ModelBuilder, "_get_serve_setting", autospec=True)
@@ -1287,6 +1291,7 @@ def test_optimize_quantize_and_compile_for_jumpstart(
         mock_pysdk_model.deployment_config = DEPLOYMENT_CONFIGS[0]
         mock_pysdk_model.config_name = "config_name"
         mock_pysdk_model._metadata_configs = {"config_name": mock_metadata_config}
+        mock_pysdk_model.init_kwargs = {"image_uri": "mock_js_image"}
 
         sample_input = {
             "inputs": "The diamondback terrapin or simply terrapin is a species "
@@ -1319,6 +1324,8 @@ def test_optimize_quantize_and_compile_for_jumpstart(
         )
 
         self.assertIsNotNone(out_put)
+        self.assertIsNone(out_put["OptimizationConfigs"][1]["ModelCompilationConfig"].get("Image"))
+        self.assertIsNone(out_put["OptimizationConfigs"][0]["ModelQuantizationConfig"].get("Image"))
 
     @patch("sagemaker.serve.builder.jumpstart_builder._capture_telemetry", side_effect=None)
     @patch.object(ModelBuilder, "_get_serve_setting", autospec=True)

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

@@ -3733,6 +3733,7 @@ def test_optimize_sharding_with_override_for_js(
         pysdk_model.env = {"key": "val"}
         pysdk_model._enable_network_isolation = True
         pysdk_model.add_tags.side_effect = lambda *arg, **kwargs: None
+        pysdk_model.init_kwargs = {"image_uri": "mock_js_image"}
 
         mock_build_for_jumpstart.side_effect = lambda **kwargs: pysdk_model
         mock_prepare_for_mode.side_effect = lambda *args, **kwargs: (
@@ -3803,8 +3804,9 @@ def test_optimize_sharding_with_override_for_js(
             OptimizationConfigs=[
                 {
                     "ModelShardingConfig": {
-                        "OverrideEnvironment": {"OPTION_TENSOR_PARALLEL_DEGREE": "1"}
-                    }
+                        "Image": "mock_js_image",
+                        "OverrideEnvironment": {"OPTION_TENSOR_PARALLEL_DEGREE": "1"},
+                    },
                 }
             ],
             OutputConfig={