AWS sagemaker documentation change
Summary
Updated documentation links for SageMakerClarifyProcessor and Processor APIs to point to the sagemaker_core.html documentation page instead of training/processing.html. Also updated ModelConfig class references.
Security assessment
The changes only update URLs and references to documentation pages without modifying security configurations, VPC settings, or access controls. No security vulnerabilities or security features are mentioned in the diff.
Diff
diff --git a/sagemaker/latest/dg/clarify-vpc.md b/sagemaker/latest/dg/clarify-vpc.md index 052248f8c..b655befa1 100644 --- a//sagemaker/latest/dg/clarify-vpc.md +++ b//sagemaker/latest/dg/clarify-vpc.md @@ -58 +58 @@ Subnets and security groups in your private Amazon VPC can be assigned to a Sage - * **SageMaker Python SDK** : Use the `NetworkConfig` parameter of the [`SageMakerClarifyProcessor`](https://sagemaker.readthedocs.io/en/stable/api/training/processing.html?highlight=Processor#sagemaker.clarify.SageMakerClarifyProcessor) API or [`Processor`](https://sagemaker.readthedocs.io/en/stable/api/training/processing.html?highlight=Processor#sagemaker.processing.Processor) API, as shown in the following example: + * **SageMaker Python SDK** : Use the `NetworkConfig` parameter of the [`SageMakerClarifyProcessor`](https://sagemaker.readthedocs.io/en/stable/api/sagemaker_core.html) API or [`Processor`](https://sagemaker.readthedocs.io/en/stable/api/sagemaker_core.html) API, as shown in the following example: @@ -83 +83 @@ The network isolation option of the SageMaker Clarify job must be turned off (by -In order to compute post-training bias metrics and explainability, the SageMaker Clarify job needs to get inferences from the SageMaker AI model that is specified by the `model_name` parameter of the [analysis configuration](https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-configure-processing-jobs.html#clarify-processing-job-configure-analysis) for the SageMaker Clarify processing job. Alternatively, if you use the `SageMakerClarifyProcessor` API in the SageMaker AI Python SDK, the job needs to get the `model_name` specified by the [ModelConfig](https://sagemaker.readthedocs.io/en/stable/api/training/processing.html?highlight=Processor#sagemaker.clarify.ModelConfig) class. To accomplish this, the SageMaker Clarify job creates an ephemeral endpoint with the model, known as a _shadow endpoint_ , and then applies the Amazon VPC configuration of the model to the shadow endpoint. +In order to compute post-training bias metrics and explainability, the SageMaker Clarify job needs to get inferences from the SageMaker AI model that is specified by the `model_name` parameter of the [analysis configuration](https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-configure-processing-jobs.html#clarify-processing-job-configure-analysis) for the SageMaker Clarify processing job. Alternatively, if you use the `SageMakerClarifyProcessor` API in the SageMaker AI Python SDK, the job needs to get the `model_name` specified by the [ModelConfig](https://sagemaker.readthedocs.io/en/stable/api/sagemaker_core.html) class. To accomplish this, the SageMaker Clarify job creates an ephemeral endpoint with the model, known as a _shadow endpoint_ , and then applies the Amazon VPC configuration of the model to the shadow endpoint. @@ -99 +99 @@ To specify subnets and security groups in your private Amazon VPC to the SageMak -You can specify the number of instances of the shadow endpoint to launch with the `initial_instance_count` parameter of the [analysis configuration](https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-configure-processing-jobs.html#clarify-processing-job-configure-analysis) for the SageMaker Clarify processing job. Alternatively, if you use the `SageMakerClarifyProcessor` API in the SageMaker AI Python SDK, the job needs to get the `instance_count` specified by the [ModelConfig](https://sagemaker.readthedocs.io/en/stable/api/training/processing.html?highlight=Processor#sagemaker.clarify.ModelConfig) class. +You can specify the number of instances of the shadow endpoint to launch with the `initial_instance_count` parameter of the [analysis configuration](https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-configure-processing-jobs.html#clarify-processing-job-configure-analysis) for the SageMaker Clarify processing job. Alternatively, if you use the `SageMakerClarifyProcessor` API in the SageMaker AI Python SDK, the job needs to get the `instance_count` specified by the [ModelConfig](https://sagemaker.readthedocs.io/en/stable/api/sagemaker_core.html) class. @@ -103 +103 @@ You can specify the number of instances of the shadow endpoint to launch with th -Even if you only request one instance when creating the shadow endpoint, you need at least two subnets in the model's [ModelConfig](https://sagemaker.readthedocs.io/en/stable/api/training/processing.html?highlight=Processor#sagemaker.clarify.ModelConfig) in distinct availability zones. Otherwise the shadow endpoint creation fails with the following error: +Even if you only request one instance when creating the shadow endpoint, you need at least two subnets in the model's [ModelConfig](https://sagemaker.readthedocs.io/en/stable/api/sagemaker_core.html) in distinct availability zones. Otherwise the shadow endpoint creation fails with the following error: @@ -141 +141 @@ SageMaker Clarify jobs support distributed processing when two or more processin - * **SageMaker Python SDK** : The `instance_count` is specified when using the [SageMakerClarifyProcessor](https://sagemaker.readthedocs.io/en/stable/api/training/processing.html?highlight=Processor#sagemaker.clarify.SageMakerClarifyProcessor) API or the [Processor](https://sagemaker.readthedocs.io/en/stable/api/training/processing.html?highlight=Processor#sagemaker.processing.Processor) API. + * **SageMaker Python SDK** : The `instance_count` is specified when using the [SageMakerClarifyProcessor](https://sagemaker.readthedocs.io/en/stable/api/sagemaker_core.html) API or the [Processor](https://sagemaker.readthedocs.io/en/stable/api/sagemaker_core.html) API.