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feat(client-lookoutequipment): 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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‎clients/client-lookoutequipment/src/commands/CreateInferenceSchedulerCommand.ts

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@@ -78,6 +78,7 @@ export interface CreateInferenceSchedulerCommandOutput extends CreateInferenceSc
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* // InferenceSchedulerArn: "STRING_VALUE",
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* // InferenceSchedulerName: "STRING_VALUE",
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* // Status: "PENDING" || "RUNNING" || "STOPPING" || "STOPPED",
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* // ModelQuality: "QUALITY_THRESHOLD_MET" || "CANNOT_DETERMINE_QUALITY" || "POOR_QUALITY_DETECTED",
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* // };
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*
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* ```

‎clients/client-lookoutequipment/src/commands/DescribeModelCommand.ts

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@@ -98,6 +98,7 @@ export interface DescribeModelCommandOutput extends DescribeModelResponse, __Met
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* // },
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* // KmsKeyId: "STRING_VALUE",
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* // },
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* // ModelQuality: "QUALITY_THRESHOLD_MET" || "CANNOT_DETERMINE_QUALITY" || "POOR_QUALITY_DETECTED",
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* // };
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*
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* ```

‎clients/client-lookoutequipment/src/commands/DescribeModelVersionCommand.ts

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@@ -93,6 +93,7 @@ export interface DescribeModelVersionCommandOutput extends DescribeModelVersionR
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* // Bucket: "STRING_VALUE", // required
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* // Key: "STRING_VALUE", // required
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* // },
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* // ModelQuality: "QUALITY_THRESHOLD_MET" || "CANNOT_DETERMINE_QUALITY" || "POOR_QUALITY_DETECTED",
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* // };
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*
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* ```

‎clients/client-lookoutequipment/src/commands/ListModelVersionsCommand.ts

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@@ -61,6 +61,7 @@ export interface ListModelVersionsCommandOutput extends ListModelVersionsRespons
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* // CreatedAt: new Date("TIMESTAMP"),
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* // Status: "IN_PROGRESS" || "SUCCESS" || "FAILED" || "IMPORT_IN_PROGRESS" || "CANCELED",
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* // SourceType: "TRAINING" || "RETRAINING" || "IMPORT",
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* // ModelQuality: "QUALITY_THRESHOLD_MET" || "CANNOT_DETERMINE_QUALITY" || "POOR_QUALITY_DETECTED",
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* // },
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* // ],
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* // };

‎clients/client-lookoutequipment/src/commands/ListModelsCommand.ts

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@@ -69,6 +69,7 @@ export interface ListModelsCommandOutput extends ListModelsResponse, __MetadataB
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* // },
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* // KmsKeyId: "STRING_VALUE",
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* // },
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* // ModelQuality: "QUALITY_THRESHOLD_MET" || "CANNOT_DETERMINE_QUALITY" || "POOR_QUALITY_DETECTED",
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* // },
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* // ],
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* // };

‎clients/client-lookoutequipment/src/models/models_0.ts

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@@ -473,6 +473,21 @@ export interface CreateInferenceSchedulerRequest {
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Tags?: Tag[];
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}
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/**
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* @public
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* @enum
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*/
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export const ModelQuality = {
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CANNOT_DETERMINE_QUALITY: "CANNOT_DETERMINE_QUALITY",
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POOR_QUALITY_DETECTED: "POOR_QUALITY_DETECTED",
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QUALITY_THRESHOLD_MET: "QUALITY_THRESHOLD_MET",
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} as const;
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/**
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* @public
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*/
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export type ModelQuality = (typeof ModelQuality)[keyof typeof ModelQuality];
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/**
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* @public
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* @enum
@@ -510,6 +525,23 @@ export interface CreateInferenceSchedulerResponse {
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* <p>Indicates the status of the <code>CreateInferenceScheduler</code> operation. </p>
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*/
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Status?: InferenceSchedulerStatus;
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/**
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* @public
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* <p>Provides a quality assessment for a model that uses labels.
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* If Lookout for Equipment determines that the
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* model quality is poor based on training metrics, the value is
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* <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
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* <code>QUALITY_THRESHOLD_MET</code>. </p>
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* <p>If the model is unlabeled, the model quality can't
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* be assessed and the value of <code>ModelQuality</code> is
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* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality
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* assessment by adding labels to the input dataset and retraining the model.</p>
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* <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>
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* <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
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* Amazon Lookout for Equipment</a>.</p>
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*/
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ModelQuality?: ModelQuality;
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}
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/**
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* <p>Configuration information for the model's pointwise model diagnostics.</p>
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*/
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ModelDiagnosticsOutputConfiguration?: ModelDiagnosticsOutputConfiguration;
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/**
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* @public
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* <p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the
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* model quality is poor based on training metrics, the value is
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* <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
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* <code>QUALITY_THRESHOLD_MET</code>.</p>
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* <p>If the model is unlabeled, the model quality can't
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* be assessed and the value of <code>ModelQuality</code> is
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* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality
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* assessment by adding labels to the input dataset and retraining the model.</p>
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* <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>
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* <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
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* Amazon Lookout for Equipment</a>.</p>
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*/
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ModelQuality?: ModelQuality;
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}
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/**
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* <p>The Amazon S3 output prefix for where Lookout for Equipment saves the pointwise model diagnostics for the model version.</p>
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*/
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ModelDiagnosticsResultsObject?: S3Object;
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/**
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* @public
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* <p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the
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* model quality is poor based on training metrics, the value is
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* <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
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* <code>QUALITY_THRESHOLD_MET</code>.</p>
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* <p>If the model is unlabeled, the model quality can't
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* be assessed and the value of <code>ModelQuality</code> is
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* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality
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* assessment by adding labels to the input dataset and retraining the model.</p>
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* <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>
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* <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
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* Amazon Lookout for Equipment</a>.</p>
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*/
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ModelQuality?: ModelQuality;
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}
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/**
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* <p>Output configuration information for the pointwise model diagnostics for an Amazon Lookout for Equipment model.</p>
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*/
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ModelDiagnosticsOutputConfiguration?: ModelDiagnosticsOutputConfiguration;
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/**
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* @public
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* <p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the
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* model quality is poor based on training metrics, the value is
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* <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
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* <code>QUALITY_THRESHOLD_MET</code>.</p>
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* <p>If the model is unlabeled, the model quality can't
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* be assessed and the value of <code>ModelQuality</code> is
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* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality
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* assessment by adding labels to the input dataset and retraining the model.</p>
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* <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>
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* <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
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* Amazon Lookout for Equipment</a>.</p>
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*/
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ModelQuality?: ModelQuality;
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}
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/**
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* <p>Indicates how this model version was generated.</p>
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*/
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SourceType?: ModelVersionSourceType;
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/**
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* @public
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* <p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the
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* model quality is poor based on training metrics, the value is
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* <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is
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* <code>QUALITY_THRESHOLD_MET</code>. </p>
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* <p>If the model is unlabeled, the model quality can't
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* be assessed and the value of <code>ModelQuality</code> is
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* <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality
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* assessment by adding labels to the input dataset and retraining the model.</p>
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* <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
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* Amazon Lookout for Equipment</a>.</p>
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*/
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ModelQuality?: ModelQuality;
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}
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/**

‎clients/client-lookoutequipment/src/protocols/Aws_json1_0.ts

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@@ -2501,6 +2501,7 @@ const de_DescribeModelResponse = (output: any, context: __SerdeContext): Describ
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ModelDiagnosticsOutputConfiguration: _json,
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ModelMetrics: (_: any) => new __LazyJsonString(_),
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ModelName: __expectString,
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ModelQuality: __expectString,
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ModelVersionActivatedAt: (_: any) => __expectNonNull(__parseEpochTimestamp(__expectNumber(_))),
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NextScheduledRetrainingStartDate: (_: any) => __expectNonNull(__parseEpochTimestamp(__expectNumber(_))),
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OffCondition: __expectString,
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ModelDiagnosticsResultsObject: _json,
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ModelMetrics: __expectString,
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ModelName: __expectString,
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ModelQuality: __expectString,
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ModelVersion: __expectLong,
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ModelVersionArn: __expectString,
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OffCondition: __expectString,
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ModelArn: __expectString,
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ModelDiagnosticsOutputConfiguration: _json,
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ModelName: __expectString,
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ModelQuality: __expectString,
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NextScheduledRetrainingStartDate: (_: any) => __expectNonNull(__parseEpochTimestamp(__expectNumber(_))),
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RetrainingSchedulerStatus: __expectString,
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Status: __expectString,
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CreatedAt: (_: any) => __expectNonNull(__parseEpochTimestamp(__expectNumber(_))),
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ModelArn: __expectString,
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ModelName: __expectString,
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ModelQuality: __expectString,
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ModelVersion: __expectLong,
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ModelVersionArn: __expectString,
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SourceType: __expectString,

‎codegen/sdk-codegen/aws-models/lookoutequipment.json

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@@ -1256,6 +1256,12 @@
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"traits": {
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"smithy.api#documentation": "<p>Indicates the status of the <code>CreateInferenceScheduler</code> operation. </p>"
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}
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},
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"ModelQuality": {
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"target": "com.amazonaws.lookoutequipment#ModelQuality",
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"traits": {
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"smithy.api#documentation": "<p>Provides a quality assessment for a model that uses labels. \n If Lookout for Equipment determines that the\n model quality is poor based on training metrics, the value is\n <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is\n <code>QUALITY_THRESHOLD_MET</code>. </p>\n <p>If the model is unlabeled, the model quality can't\n be assessed and the value of <code>ModelQuality</code> is\n <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality\n assessment by adding labels to the input dataset and retraining the model.</p>\n <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>\n <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\n Amazon Lookout for Equipment</a>.</p>"
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}
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}
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},
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"traits": {
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"traits": {
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"smithy.api#documentation": "<p>Configuration information for the model's pointwise model diagnostics.</p>"
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}
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},
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"ModelQuality": {
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"target": "com.amazonaws.lookoutequipment#ModelQuality",
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"traits": {
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"smithy.api#documentation": "<p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the\n model quality is poor based on training metrics, the value is\n <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is\n <code>QUALITY_THRESHOLD_MET</code>.</p>\n <p>If the model is unlabeled, the model quality can't\n be assessed and the value of <code>ModelQuality</code> is\n <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality\n assessment by adding labels to the input dataset and retraining the model.</p>\n <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>\n <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\n Amazon Lookout for Equipment</a>.</p>"
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}
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}
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},
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"traits": {
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"traits": {
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"smithy.api#documentation": "<p>The Amazon S3 output prefix for where Lookout for Equipment saves the pointwise model diagnostics for the model version.</p>"
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}
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},
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"ModelQuality": {
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"target": "com.amazonaws.lookoutequipment#ModelQuality",
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"traits": {
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"smithy.api#documentation": "<p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the\n model quality is poor based on training metrics, the value is\n <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is\n <code>QUALITY_THRESHOLD_MET</code>.</p>\n <p>If the model is unlabeled, the model quality can't\n be assessed and the value of <code>ModelQuality</code> is\n <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality\n assessment by adding labels to the input dataset and retraining the model.</p>\n <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>\n <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\n Amazon Lookout for Equipment</a>.</p>"
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}
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}
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},
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"traits": {
@@ -6173,6 +6191,29 @@
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}
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}
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},
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"com.amazonaws.lookoutequipment#ModelQuality": {
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"type": "enum",
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"members": {
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"QUALITY_THRESHOLD_MET": {
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"target": "smithy.api#Unit",
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"traits": {
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"smithy.api#enumValue": "QUALITY_THRESHOLD_MET"
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}
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},
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"CANNOT_DETERMINE_QUALITY": {
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"target": "smithy.api#Unit",
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"traits": {
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"smithy.api#enumValue": "CANNOT_DETERMINE_QUALITY"
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}
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},
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"POOR_QUALITY_DETECTED": {
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"target": "smithy.api#Unit",
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"traits": {
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"smithy.api#enumValue": "POOR_QUALITY_DETECTED"
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}
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}
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}
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},
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"com.amazonaws.lookoutequipment#ModelStatus": {
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"type": "enum",
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"members": {
@@ -6291,6 +6332,12 @@
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},
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"ModelDiagnosticsOutputConfiguration": {
62936334
"target": "com.amazonaws.lookoutequipment#ModelDiagnosticsOutputConfiguration"
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},
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"ModelQuality": {
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"target": "com.amazonaws.lookoutequipment#ModelQuality",
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"traits": {
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"smithy.api#documentation": "<p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the\n model quality is poor based on training metrics, the value is\n <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is\n <code>QUALITY_THRESHOLD_MET</code>.</p>\n <p>If the model is unlabeled, the model quality can't\n be assessed and the value of <code>ModelQuality</code> is\n <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality\n assessment by adding labels to the input dataset and retraining the model.</p>\n <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>\n <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\n Amazon Lookout for Equipment</a>.</p>"
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}
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}
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},
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"traits": {
@@ -6423,6 +6470,12 @@
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"traits": {
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"smithy.api#documentation": "<p>Indicates how this model version was generated.</p>"
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}
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},
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"ModelQuality": {
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"target": "com.amazonaws.lookoutequipment#ModelQuality",
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"traits": {
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"smithy.api#documentation": "<p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the\n model quality is poor based on training metrics, the value is\n <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is\n <code>QUALITY_THRESHOLD_MET</code>. </p>\n <p>If the model is unlabeled, the model quality can't\n be assessed and the value of <code>ModelQuality</code> is\n <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality\n assessment by adding labels to the input dataset and retraining the model.</p>\n <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\n Amazon Lookout for Equipment</a>.</p>"
6478+
}
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}
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},
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"traits": {

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