AWS sagemaker documentation change
Summary
Updated SageMaker SDK imports and parameter names (volume_size → volume_size_in_gb), and replaced role/session initialization methods
Security assessment
Changes reflect SDK updates without security implications. Parameter renaming (volume_size_in_gb) improves clarity but doesn't address security vulnerabilities.
Diff
diff --git a/sagemaker/latest/dg/large-model-inference-tutorials-torchserve.md b/sagemaker/latest/dg/large-model-inference-tutorials-torchserve.md index 07a944199..522541ac6 100644 --- a//sagemaker/latest/dg/large-model-inference-tutorials-torchserve.md +++ b//sagemaker/latest/dg/large-model-inference-tutorials-torchserve.md @@ -216 +216,3 @@ To deploy your model, complete the following steps: - from sagemaker import Model, image_uris, serializers, deserializers + from sagemaker.core.resources import Model + from sagemaker.core import image_uris + from sagemaker.core.helper.session_helper import get_execution_role, Session @@ -221,2 +223,2 @@ To deploy your model, complete the following steps: - role = sagemaker.get_execution_role() # execution role for the endpoint - sess= sagemaker.session.Session(boto3_session, sagemaker_client=sm, sagemaker_runtime_client=smr) # SageMaker AI session for interacting with different AWS APIs + role = get_execution_role() # execution role for the endpoint + sess= Session(boto3_session, sagemaker_client=sm, sagemaker_runtime_client=smr) # SageMaker AI session for interacting with different AWS APIs @@ -263 +265 @@ To deploy your model, complete the following steps: - volume_size=512, # increase the size to store large model + volume_size_in_gb=512, # increase the size to store large model