fix: attach jumpstart estimator for gated model (#4546)

Author: evakravi

src/sagemaker/jumpstart/estimator.py

@@ -37,6 +37,7 @@
 from sagemaker.jumpstart.utils import (
     validate_model_id_and_get_type,
     resolve_model_sagemaker_config_field,
+    verify_model_region_and_return_specs,
 )
 from sagemaker.utils import stringify_object, format_tags, Tags
 from sagemaker.model_monitor.data_capture_config import DataCaptureConfig
@@ -729,11 +730,27 @@ def attach(
 
         model_version = model_version or "*"
 
+        additional_kwargs = {"model_id": model_id, "model_version": model_version}
+
+        model_specs = verify_model_region_and_return_specs(
+            model_id=model_id,
+            version=model_version,
+            region=sagemaker_session.boto_region_name,
+            scope=JumpStartScriptScope.TRAINING,
+            tolerate_deprecated_model=True,  # model is already trained, so tolerate if deprecated
+            tolerate_vulnerable_model=True,  # model is already trained, so tolerate if vulnerable
+            sagemaker_session=sagemaker_session,
+        )
+
+        # eula was already accepted if the model was successfully trained
+        if model_specs.is_gated_model():
+            additional_kwargs.update({"environment": {"accept_eula": "true"}})
+
         return cls._attach(
             training_job_name=training_job_name,
             sagemaker_session=sagemaker_session,
             model_channel_name=model_channel_name,
-            additional_kwargs={"model_id": model_id, "model_version": model_version},
+            additional_kwargs=additional_kwargs,
         )
 
     def deploy(

tests/integ/sagemaker/jumpstart/estimator/test_jumpstart_estimator.py

@@ -160,8 +160,16 @@ def test_gated_model_training_v2(setup):
         }
     )
 
+    # test that we can create a JumpStartEstimator from existing job with `attach`
+    attached_estimator = JumpStartEstimator.attach(
+        training_job_name=estimator.latest_training_job.name,
+        model_id=model_id,
+        model_version=model_version,
+        sagemaker_session=get_sm_session(),
+    )
+
     # uses ml.g5.2xlarge instance
-    predictor = estimator.deploy(
+    predictor = attached_estimator.deploy(
         tags=[{"Key": JUMPSTART_TAG, "Value": os.environ[ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID]}],
         role=get_sm_session().get_caller_identity_arn(),
         sagemaker_session=get_sm_session(),
@@ -172,7 +180,7 @@ def test_gated_model_training_v2(setup):
         "parameters": {"max_new_tokens": 256, "top_p": 0.9, "temperature": 0.6},
     }
 
-    response = predictor.predict(payload, custom_attributes="accept_eula=true")
+    response = predictor.predict(payload)
 
     assert response is not None
 

tests/unit/sagemaker/jumpstart/estimator/test_estimator.py

@@ -979,6 +979,40 @@ def test_jumpstart_estimator_tags(
             [{"Key": "blah", "Value": "blahagain"}] + js_tags,
         )
 
+    @mock.patch("sagemaker.jumpstart.estimator.JumpStartEstimator._attach")
+    @mock.patch("sagemaker.jumpstart.estimator.validate_model_id_and_get_type")
+    @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
+    @mock.patch("sagemaker.jumpstart.factory.estimator.JUMPSTART_DEFAULT_REGION_NAME", region)
+    def test_jumpstart_estimator_attach_eula_model(
+        self,
+        mock_get_model_specs: mock.Mock,
+        mock_validate_model_id_and_get_type: mock.Mock,
+        mock_attach: mock.Mock,
+    ):
+
+        mock_validate_model_id_and_get_type.return_value = JumpStartModelType.OPEN_WEIGHTS
+
+        mock_get_model_specs.side_effect = get_special_model_spec
+
+        mock_session = mock.MagicMock(sagemaker_config={}, boto_region_name="us-west-2")
+
+        JumpStartEstimator.attach(
+            training_job_name="some-training-job-name",
+            model_id="gemma-model",
+            sagemaker_session=mock_session,
+        )
+
+        mock_attach.assert_called_once_with(
+            training_job_name="some-training-job-name",
+            sagemaker_session=mock_session,
+            model_channel_name="model",
+            additional_kwargs={
+                "model_id": "gemma-model",
+                "model_version": "*",
+                "environment": {"accept_eula": "true"},
+            },
+        )
+
     @mock.patch("sagemaker.jumpstart.estimator.JumpStartEstimator._attach")
     @mock.patch("sagemaker.jumpstart.estimator.get_model_id_version_from_training_job")
     @mock.patch("sagemaker.jumpstart.estimator.validate_model_id_and_get_type")