Amazon SageMaker Service Update: SageMaker Inference Recommender now provides SupportedResponseMIMETypes from DescribeInferenceRecommendationsJob response

Author: AWS

.changes/next-release/feature-AmazonSageMakerService-d4b6302.json

@@ -0,0 +1,6 @@
+{
+    "type": "feature",
+    "category": "Amazon SageMaker Service",
+    "contributor": "",
+    "description": "SageMaker Inference Recommender now provides SupportedResponseMIMETypes from DescribeInferenceRecommendationsJob response"
+}

services/sagemaker/src/main/resources/codegen-resources/service-2.json

@@ -279,7 +279,7 @@
       "errors":[
         {"shape":"ResourceLimitExceeded"}
       ],
-      "documentation":"<p>Creates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html\">CreateEndpointConfig</a> API. </p> <p> Use this API to deploy models using SageMaker hosting services. </p> <p>For an example that calls this method when deploying a model to SageMaker hosting services, see the <a href=\"https://github.com/aws/amazon-sagemaker-examples/blob/master/sagemaker-fundamentals/create-endpoint/create_endpoint.ipynb\">Create Endpoint example notebook.</a> </p> <note> <p> You must not delete an <code>EndpointConfig</code> that is in use by an endpoint that is live or while the <code>UpdateEndpoint</code> or <code>CreateEndpoint</code> operations are being performed on the endpoint. To update an endpoint, you must create a new <code>EndpointConfig</code>.</p> </note> <p>The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account. </p> <p>When it receives the request, SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them. </p> <note> <p>When you call <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html\">CreateEndpoint</a>, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting <a href=\"https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html\"> <code>Eventually Consistent Reads</code> </a>, the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeEndpointConfig.html\">DescribeEndpointConfig</a> before calling <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html\">CreateEndpoint</a> to minimize the potential impact of a DynamoDB eventually consistent read.</p> </note> <p>When SageMaker receives the request, it sets the endpoint status to <code>Creating</code>. After it creates the endpoint, it sets the status to <code>InService</code>. SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeEndpoint.html\">DescribeEndpoint</a> API.</p> <p>If any of the models hosted at this endpoint get model data from an Amazon S3 location, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see <a href=\"https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html\">Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region</a> in the <i>Amazon Web Services Identity and Access Management User Guide</i>.</p> <note> <p> To add the IAM role policies for using this API operation, go to the <a href=\"https://console.aws.amazon.com/iam/\">IAM console</a>, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html\">CreateEndpoint</a> and <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html\">CreateEndpointConfig</a> API operations, add the following policies to the role. </p> <ul> <li> <p>Option 1: For a full SageMaker access, search and attach the <code>AmazonSageMakerFullAccess</code> policy.</p> </li> <li> <p>Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role: </p> <p> <code>\"Action\": [\"sagemaker:CreateEndpoint\", \"sagemaker:CreateEndpointConfig\"]</code> </p> <p> <code>\"Resource\": [</code> </p> <p> <code>\"arn:aws:sagemaker:region:account-id:endpoint/endpointName\"</code> </p> <p> <code>\"arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName\"</code> </p> <p> <code>]</code> </p> <p>For more information, see <a href=\"https://docs.aws.amazon.com/sagemaker/latest/dg/api-permissions-reference.html\">SageMaker API Permissions: Actions, Permissions, and Resources Reference</a>.</p> </li> </ul> </note>"
+      "documentation":"<p>Creates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html\">CreateEndpointConfig</a> API. </p> <p> Use this API to deploy models using SageMaker hosting services. </p> <note> <p> You must not delete an <code>EndpointConfig</code> that is in use by an endpoint that is live or while the <code>UpdateEndpoint</code> or <code>CreateEndpoint</code> operations are being performed on the endpoint. To update an endpoint, you must create a new <code>EndpointConfig</code>.</p> </note> <p>The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account. </p> <p>When it receives the request, SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them. </p> <note> <p>When you call <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html\">CreateEndpoint</a>, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting <a href=\"https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html\"> <code>Eventually Consistent Reads</code> </a>, the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeEndpointConfig.html\">DescribeEndpointConfig</a> before calling <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html\">CreateEndpoint</a> to minimize the potential impact of a DynamoDB eventually consistent read.</p> </note> <p>When SageMaker receives the request, it sets the endpoint status to <code>Creating</code>. After it creates the endpoint, it sets the status to <code>InService</code>. SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeEndpoint.html\">DescribeEndpoint</a> API.</p> <p>If any of the models hosted at this endpoint get model data from an Amazon S3 location, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see <a href=\"https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html\">Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region</a> in the <i>Amazon Web Services Identity and Access Management User Guide</i>.</p> <note> <p> To add the IAM role policies for using this API operation, go to the <a href=\"https://console.aws.amazon.com/iam/\">IAM console</a>, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html\">CreateEndpoint</a> and <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html\">CreateEndpointConfig</a> API operations, add the following policies to the role. </p> <ul> <li> <p>Option 1: For a full SageMaker access, search and attach the <code>AmazonSageMakerFullAccess</code> policy.</p> </li> <li> <p>Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role: </p> <p> <code>\"Action\": [\"sagemaker:CreateEndpoint\", \"sagemaker:CreateEndpointConfig\"]</code> </p> <p> <code>\"Resource\": [</code> </p> <p> <code>\"arn:aws:sagemaker:region:account-id:endpoint/endpointName\"</code> </p> <p> <code>\"arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName\"</code> </p> <p> <code>]</code> </p> <p>For more information, see <a href=\"https://docs.aws.amazon.com/sagemaker/latest/dg/api-permissions-reference.html\">SageMaker API Permissions: Actions, Permissions, and Resources Reference</a>.</p> </li> </ul> </note>"
     },
     "CreateEndpointConfig":{
       "name":"CreateEndpointConfig",
@@ -8672,7 +8672,7 @@
         },
         "Tags":{
           "shape":"TagList",
-          "documentation":"<p>A list of key value pairs associated with the model. For more information, see <a href=\"https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html\">Tagging Amazon Web Services resources</a> in the <i>Amazon Web Services General Reference Guide</i>.</p>"
+          "documentation":"<p>A list of key value pairs associated with the model. For more information, see <a href=\"https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html\">Tagging Amazon Web Services resources</a> in the <i>Amazon Web Services General Reference Guide</i>.</p> <p>If you supply <code>ModelPackageGroupName</code>, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply a <code>tag</code> argument. </p>"
         },
         "ModelApprovalStatus":{
           "shape":"ModelApprovalStatus",
@@ -29167,6 +29167,10 @@
         "SupportedEndpointType":{
           "shape":"RecommendationJobSupportedEndpointType",
           "documentation":"<p>The endpoint type to receive recommendations for. By default this is null, and the results of the inference recommendation job return a combined list of both real-time and serverless benchmarks. By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.</p>"
+        },
+        "SupportedResponseMIMETypes":{
+          "shape":"RecommendationJobSupportedResponseMIMETypes",
+          "documentation":"<p>The supported MIME types for the output data.</p>"
         }
       },
       "documentation":"<p>Specifies mandatory fields for running an Inference Recommender job directly in the <a href=\"https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateInferenceRecommendationsJob.html\">CreateInferenceRecommendationsJob</a> API. The fields specified in <code>ContainerConfig</code> override the corresponding fields in the model package. Use <code>ContainerConfig</code> if you want to specify these fields for the recommendation job but don't want to edit them in your model package.</p>"
@@ -29342,6 +29346,15 @@
       "type":"list",
       "member":{"shape":"String"}
     },
+    "RecommendationJobSupportedResponseMIMEType":{
+      "type":"string",
+      "max":1024,
+      "pattern":"^[-\\w]+\\/.+$"
+    },
+    "RecommendationJobSupportedResponseMIMETypes":{
+      "type":"list",
+      "member":{"shape":"RecommendationJobSupportedResponseMIMEType"}
+    },
     "RecommendationJobType":{
       "type":"string",
       "enum":[