lint

Author: bencrabtree

src/sagemaker/jumpstart/utils.py

@@ -1641,7 +1641,11 @@ def remove_env_var_from_estimator_kwargs_if_model_access_config_present(
         init_kwargs (dict): Dictionary of kwargs when Estimator is instantiated.
         accept_eula (Optional[bool]): Whether or not the EULA was accepted, optionally passed in to Estimator.fit().
     """
-    if model_access_config is not None and init_kwargs.get("environment") is not None and init_kwargs.get("model_uri") is not None:
+    if (
+        model_access_config is not None
+        and init_kwargs.get("environment") is not None
+        and init_kwargs.get("model_uri") is not None
+    ):
         if (
             constants.SAGEMAKER_GATED_MODEL_S3_URI_TRAINING_ENV_VAR_KEY
             in init_kwargs["environment"]

src/test.py

@@ -0,0 +1,36 @@
+from sagemaker.jumpstart.hub.hub import Hub
+from sagemaker import hyperparameters
+from sagemaker.session import Session
+from sagemaker.jumpstart.estimator import JumpStartEstimator
+
+
+hub = Hub(hub_name="temp-bencrab-hub", sagemaker_session=Session())
+
+# hub.create(description="hello haha")
+
+model_id = "meta-vlm-llama-3-2-11b-vision"
+model_version = "*"
+hub_arn = hub.hub_name
+
+my_hyperparameters = hyperparameters.retrieve_default(
+    model_id=model_id, model_version=model_version, hub_arn=hub_arn
+)
+print(my_hyperparameters)
+hyperparameters.validate(
+    model_id=model_id,
+    model_version=model_version,
+    hyperparameters=my_hyperparameters,
+    hub_arn=hub_arn,
+)
+estimator = JumpStartEstimator(
+    model_id=model_id,
+    hub_name=hub_arn,
+    model_version=model_version,
+    environment={"accept_eula": "true"},  # Please change {"accept_eula": "true"}
+    disable_output_compression=True,
+    instance_type="ml.p4d.24xlarge",
+    hyperparameters=my_hyperparameters,
+)
+estimator.fit(
+    {"training": "s3://jumpstart-cache-prod-us-west-2/training-datasets/docVQA-small-3000ex/"}
+)