Updated API models and rebuilt service gems.

Author: aws-sdk-ruby-automation

apis/qconnect/2020-10-19/api-2.json

@@ -0,0 +1,5 @@
+{
+  "version": 2,
+  "waiters": {
+  }
+}

apis/qconnect/2020-10-19/docs-2.json

@@ -18596,7 +18596,8 @@
         "ModelPackageDescription":{"shape":"EntityDescription"},
         "CreationTime":{"shape":"CreationTime"},
         "ModelPackageStatus":{"shape":"ModelPackageStatus"},
-        "ModelApprovalStatus":{"shape":"ModelApprovalStatus"}
+        "ModelApprovalStatus":{"shape":"ModelApprovalStatus"},
+        "ModelLifeCycle":{"shape":"ModelLifeCycle"}
       }
     },
     "ModelPackageSummaryList":{
@@ -20803,7 +20804,8 @@
       "enum":[
         "al2-ami-sagemaker-inference-gpu-2",
         "al2-ami-sagemaker-inference-gpu-2-1",
-        "al2-ami-sagemaker-inference-gpu-3-1"
+        "al2-ami-sagemaker-inference-gpu-3-1",
+        "al2-ami-sagemaker-inference-neuron-2"
       ]
     },
     "ProductionVariantInstanceType":{

apis/qconnect/2020-10-19/waiters-2.json

@@ -10095,7 +10095,7 @@
     "MaxPendingTimeInSeconds": {
       "base": "Maximum job scheduler pending time in seconds.",
       "refs": {
-        "StoppingCondition$MaxPendingTimeInSeconds": "<p>The maximum length of time, in seconds, that a training or compilation job can be pending before it is stopped.</p>"
+        "StoppingCondition$MaxPendingTimeInSeconds": "<p>The maximum length of time, in seconds, that a training or compilation job can be pending before it is stopped.</p> <note> <p>When working with training jobs that use capacity from <a href=\"https://docs.aws.amazon.com/sagemaker/latest/dg/reserve-capacity-with-training-plans.html\">training plans</a>, not all <code>Pending</code> job states count against the <code>MaxPendingTimeInSeconds</code> limit. The following scenarios do not increment the <code>MaxPendingTimeInSeconds</code> counter:</p> <ul> <li> <p>The plan is in a <code>Scheduled</code> state: Jobs queued (in <code>Pending</code> status) before a plan's start date (waiting for scheduled start time)</p> </li> <li> <p>Between capacity reservations: Jobs temporarily back to <code>Pending</code> status between two capacity reservation periods</p> </li> </ul> <p> <code>MaxPendingTimeInSeconds</code> only increments when jobs are actively waiting for capacity in an <code>Active</code> plan.</p> </note>"
       }
     },
     "MaxPercentageOfInputDatasetLabeled": {
@@ -10781,6 +10781,7 @@
         "CreateModelPackageInput$ModelLifeCycle": "<p> A structure describing the current state of the model in its life cycle. </p>",
         "DescribeModelPackageOutput$ModelLifeCycle": "<p> A structure describing the current state of the model in its life cycle. </p>",
         "ModelPackage$ModelLifeCycle": "<p> A structure describing the current state of the model in its life cycle. </p>",
+        "ModelPackageSummary$ModelLifeCycle": null,
         "UpdateModelPackageInput$ModelLifeCycle": "<p> A structure describing the current state of the model in its life cycle. </p>"
       }
     },
@@ -13286,7 +13287,7 @@
     "ProductionVariantInferenceAmiVersion": {
       "base": null,
       "refs": {
-        "ProductionVariant$InferenceAmiVersion": "<p>Specifies an option from a collection of preconfigured Amazon Machine Image (AMI) images. Each image is configured by Amazon Web Services with a set of software and driver versions. Amazon Web Services optimizes these configurations for different machine learning workloads.</p> <p>By selecting an AMI version, you can ensure that your inference environment is compatible with specific software requirements, such as CUDA driver versions, Linux kernel versions, or Amazon Web Services Neuron driver versions.</p> <p>The AMI version names, and their configurations, are the following:</p> <dl> <dt>al2-ami-sagemaker-inference-gpu-2</dt> <dd> <ul> <li> <p>Accelerator: GPU</p> </li> <li> <p>NVIDIA driver version: 535</p> </li> <li> <p>CUDA version: 12.2</p> </li> </ul> </dd> <dt>al2-ami-sagemaker-inference-gpu-2-1</dt> <dd> <ul> <li> <p>Accelerator: GPU</p> </li> <li> <p>NVIDIA driver version: 535</p> </li> <li> <p>CUDA version: 12.2</p> </li> <li> <p>NVIDIA Container Toolkit with disabled CUDA-compat mounting</p> </li> </ul> </dd> <dt>al2-ami-sagemaker-inference-gpu-3-1</dt> <dd> <ul> <li> <p>Accelerator: GPU</p> </li> <li> <p>NVIDIA driver version: 550</p> </li> <li> <p>CUDA version: 12.4</p> </li> <li> <p>NVIDIA Container Toolkit with disabled CUDA-compat mounting</p> </li> </ul> </dd> </dl>"
+        "ProductionVariant$InferenceAmiVersion": "<p>Specifies an option from a collection of preconfigured Amazon Machine Image (AMI) images. Each image is configured by Amazon Web Services with a set of software and driver versions. Amazon Web Services optimizes these configurations for different machine learning workloads.</p> <p>By selecting an AMI version, you can ensure that your inference environment is compatible with specific software requirements, such as CUDA driver versions, Linux kernel versions, or Amazon Web Services Neuron driver versions.</p> <p>The AMI version names, and their configurations, are the following:</p> <dl> <dt>al2-ami-sagemaker-inference-gpu-2</dt> <dd> <ul> <li> <p>Accelerator: GPU</p> </li> <li> <p>NVIDIA driver version: 535</p> </li> <li> <p>CUDA version: 12.2</p> </li> </ul> </dd> <dt>al2-ami-sagemaker-inference-gpu-2-1</dt> <dd> <ul> <li> <p>Accelerator: GPU</p> </li> <li> <p>NVIDIA driver version: 535</p> </li> <li> <p>CUDA version: 12.2</p> </li> <li> <p>NVIDIA Container Toolkit with disabled CUDA-compat mounting</p> </li> </ul> </dd> <dt>al2-ami-sagemaker-inference-gpu-3-1</dt> <dd> <ul> <li> <p>Accelerator: GPU</p> </li> <li> <p>NVIDIA driver version: 550</p> </li> <li> <p>CUDA version: 12.4</p> </li> <li> <p>NVIDIA Container Toolkit with disabled CUDA-compat mounting</p> </li> </ul> </dd> <dt>al2-ami-sagemaker-inference-neuron-2</dt> <dd> <ul> <li> <p>Accelerator: Inferentia2 and Trainium</p> </li> <li> <p>Neuron driver version: 2.19</p> </li> </ul> </dd> </dl>"
       }
     },
     "ProductionVariantInstanceType": {

apis/sagemaker/2017-07-24/api-2.json

@@ -791,6 +791,12 @@
       ]
     },
     "QuotaContextScopeType":{"type":"string"},
+    "QuotaDescription":{
+      "type":"string",
+      "max":350,
+      "min":0,
+      "pattern":"^.{0,350}$"
+    },
     "QuotaExceededException":{
       "type":"structure",
       "members":{
@@ -831,7 +837,8 @@
         "ServiceCode":{"shape":"ServiceCode"},
         "QuotaCode":{"shape":"QuotaCode"},
         "DesiredValue":{"shape":"QuotaValue"},
-        "ContextId":{"shape":"QuotaContextId"}
+        "ContextId":{"shape":"QuotaContextId"},
+        "SupportCaseAllowed":{"shape":"SupportCaseAllowed"}
       }
     },
     "RequestServiceQuotaIncreaseResponse":{
@@ -927,7 +934,8 @@
         "Period":{"shape":"QuotaPeriod"},
         "ErrorReason":{"shape":"ErrorReason"},
         "QuotaAppliedAtLevel":{"shape":"AppliedLevelEnum"},
-        "QuotaContext":{"shape":"QuotaContextInfo"}
+        "QuotaContext":{"shape":"QuotaContextInfo"},
+        "Description":{"shape":"QuotaDescription"}
       }
     },
     "ServiceQuotaIncreaseRequestInTemplate":{
@@ -971,6 +979,7 @@
       "min":1,
       "pattern":"(Sum|Maximum)"
     },
+    "SupportCaseAllowed":{"type":"boolean"},
     "Tag":{
       "type":"structure",
       "required":[