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MediaLive now supports the ability to restart pipelines in a running …
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…channel.

Increase the maximum length of descriptions for Inputs, Detector Models, and Alarm Models
This release adds support for sharing Systems Manager parameters with other AWS accounts.
This release adds a field exposing model quality to read APIs for models. It also adds a model quality field to the API response when creating an inference scheduler.
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aws-sdk-cpp-automation committed Feb 21, 2024
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2 changes: 1 addition & 1 deletion VERSION
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1.11.269
1.11.270
186 changes: 93 additions & 93 deletions generated/src/aws-cpp-sdk-iotevents/source/IoTEventsEndpointRules.cpp
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89 changes: 89 additions & 0 deletions ...-sdk-lookoutequipment/include/aws/lookoutequipment/model/CreateInferenceSchedulerResult.h
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#include <aws/lookoutequipment/LookoutEquipment_EXPORTS.h>
#include <aws/core/utils/memory/stl/AWSString.h>
#include <aws/lookoutequipment/model/InferenceSchedulerStatus.h>
#include <aws/lookoutequipment/model/ModelQuality.h>
#include <utility>

namespace Aws
Expand Down Expand Up @@ -136,6 +137,92 @@ namespace Model
inline CreateInferenceSchedulerResult& WithStatus(InferenceSchedulerStatus&& value) { SetStatus(std::move(value)); return *this;}


/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>. </p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline const ModelQuality& GetModelQuality() const{ return m_modelQuality; }

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>. </p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline void SetModelQuality(const ModelQuality& value) { m_modelQuality = value; }

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>. </p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline void SetModelQuality(ModelQuality&& value) { m_modelQuality = std::move(value); }

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>. </p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline CreateInferenceSchedulerResult& WithModelQuality(const ModelQuality& value) { SetModelQuality(value); return *this;}

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>. </p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline CreateInferenceSchedulerResult& WithModelQuality(ModelQuality&& value) { SetModelQuality(std::move(value)); return *this;}



inline const Aws::String& GetRequestId() const{ return m_requestId; }

Expand Down Expand Up @@ -165,6 +252,8 @@ namespace Model

InferenceSchedulerStatus m_status;

ModelQuality m_modelQuality;

Aws::String m_requestId;
};

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89 changes: 89 additions & 0 deletions ...src/aws-cpp-sdk-lookoutequipment/include/aws/lookoutequipment/model/DescribeModelResult.h
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Expand Up @@ -13,6 +13,7 @@
#include <aws/lookoutequipment/model/ModelVersionStatus.h>
#include <aws/lookoutequipment/model/RetrainingSchedulerStatus.h>
#include <aws/lookoutequipment/model/ModelDiagnosticsOutputConfiguration.h>
#include <aws/lookoutequipment/model/ModelQuality.h>
#include <utility>

namespace Aws
Expand Down Expand Up @@ -1468,6 +1469,92 @@ namespace Model
inline DescribeModelResult& WithModelDiagnosticsOutputConfiguration(ModelDiagnosticsOutputConfiguration&& value) { SetModelDiagnosticsOutputConfiguration(std::move(value)); return *this;}


/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>.</p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline const ModelQuality& GetModelQuality() const{ return m_modelQuality; }

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>.</p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline void SetModelQuality(const ModelQuality& value) { m_modelQuality = value; }

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>.</p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline void SetModelQuality(ModelQuality&& value) { m_modelQuality = std::move(value); }

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>.</p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline DescribeModelResult& WithModelQuality(const ModelQuality& value) { SetModelQuality(value); return *this;}

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>.</p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline DescribeModelResult& WithModelQuality(ModelQuality&& value) { SetModelQuality(std::move(value)); return *this;}



inline const Aws::String& GetRequestId() const{ return m_requestId; }

Expand Down Expand Up @@ -1573,6 +1660,8 @@ namespace Model

ModelDiagnosticsOutputConfiguration m_modelDiagnosticsOutputConfiguration;

ModelQuality m_modelQuality;

Aws::String m_requestId;
};

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89 changes: 89 additions & 0 deletions ...-cpp-sdk-lookoutequipment/include/aws/lookoutequipment/model/DescribeModelVersionResult.h
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Expand Up @@ -14,6 +14,7 @@
#include <aws/lookoutequipment/model/AutoPromotionResult.h>
#include <aws/lookoutequipment/model/ModelDiagnosticsOutputConfiguration.h>
#include <aws/lookoutequipment/model/S3Object.h>
#include <aws/lookoutequipment/model/ModelQuality.h>
#include <utility>

namespace Aws
Expand Down Expand Up @@ -1219,6 +1220,92 @@ namespace Model
inline DescribeModelVersionResult& WithModelDiagnosticsResultsObject(S3Object&& value) { SetModelDiagnosticsResultsObject(std::move(value)); return *this;}


/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>.</p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline const ModelQuality& GetModelQuality() const{ return m_modelQuality; }

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>.</p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline void SetModelQuality(const ModelQuality& value) { m_modelQuality = value; }

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>.</p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline void SetModelQuality(ModelQuality&& value) { m_modelQuality = std::move(value); }

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>.</p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline DescribeModelVersionResult& WithModelQuality(const ModelQuality& value) { SetModelQuality(value); return *this;}

/**
* <p>Provides a quality assessment for a model that uses labels. If Lookout for
* Equipment determines that the model quality is poor based on training metrics,
* the value is <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
* <code>QUALITY_THRESHOLD_MET</code>.</p> <p>If the model is unlabeled, the model
* quality can't be assessed and the value of <code>ModelQuality</code> is
* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model
* quality assessment by adding labels to the input dataset and retraining the
* model.</p> <p>For information about using labels with your models, see <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html">Understanding
* labeling</a>.</p> <p>For information about improving the quality of a model, see
* <a
* href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best
* practices with Amazon Lookout for Equipment</a>.</p>
*/
inline DescribeModelVersionResult& WithModelQuality(ModelQuality&& value) { SetModelQuality(std::move(value)); return *this;}



inline const Aws::String& GetRequestId() const{ return m_requestId; }

Expand Down Expand Up @@ -1310,6 +1397,8 @@ namespace Model

S3Object m_modelDiagnosticsResultsObject;

ModelQuality m_modelQuality;

Aws::String m_requestId;
};

Expand Down
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