AWS sagemaker documentation change
Summary
Removed legacy SageMaker Python SDK v2 code examples and references
Security assessment
Change removes outdated code samples without security context. No evidence of security vulnerability remediation or security feature addition.
Diff
diff --git a/sagemaker/latest/dg/model-optimize-create-job.md b/sagemaker/latest/dg/model-optimize-create-job.md index 9dabd2823..fa7d2b445 100644 --- a//sagemaker/latest/dg/model-optimize-create-job.md +++ b//sagemaker/latest/dg/model-optimize-create-job.md @@ -209,3 +208,0 @@ For more information about the classes and methods used in the following example -SageMaker Python SDK v3 - - @@ -218,9 +214,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - import boto3 - from sagemaker.serve.builder.model_builder import ModelBuilder - from sagemaker.serve.builder.schema_builder import SchemaBuilder - from sagemaker.session import Session - from pathlib import Path - @@ -293,3 +280,0 @@ The `optimize()` method returns a `Model` object, which you can use to deploy yo -SageMaker Python SDK v3 - - @@ -301,8 +285,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - predictor = optimized_model.deploy( - instance_type="instance-type", - accept_eula=True, - ) - @@ -340,3 +316,0 @@ The `optimize()` method returns a `Model` object, which you can use to deploy yo -SageMaker Python SDK v3 - - @@ -345,5 +318,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - predictor = optimized_model.deploy(accept_eula=True) - @@ -404,3 +372,0 @@ The `optimize()` method returns a `Model` object, which you can use to deploy yo -SageMaker Python SDK v3 - - @@ -409,5 +374,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - predictor = optimized_model.deploy(accept_eula=True) - @@ -443,3 +403,0 @@ In this example, set ``instance-type`` to an ML instance type with accelerated h -SageMaker Python SDK v3 - - @@ -448,5 +405,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - predictor = optimized_model.deploy(accept_eula=True) - @@ -462,3 +414,0 @@ The `deploy()` method returns an `Endpoint` object, which you can use to send in -SageMaker Python SDK v3 - - @@ -470,5 +419,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - predictor.predict(sample_input) -