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feat(client-lookoutequipment): This release adds a field exposing mod…
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…el 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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awstools committed Feb 21, 2024
1 parent 200c126 commit b8f8238
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1 change: 1 addition & 0 deletions clients/client-lookoutequipment/src/commands/CreateInferenceSchedulerCommand.ts
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Expand Up @@ -78,6 +78,7 @@ export interface CreateInferenceSchedulerCommandOutput extends CreateInferenceSc
* // InferenceSchedulerArn: "STRING_VALUE",
* // InferenceSchedulerName: "STRING_VALUE",
* // Status: "PENDING" || "RUNNING" || "STOPPING" || "STOPPED",
* // ModelQuality: "QUALITY_THRESHOLD_MET" || "CANNOT_DETERMINE_QUALITY" || "POOR_QUALITY_DETECTED",
* // };
*
* ```
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1 change: 1 addition & 0 deletions clients/client-lookoutequipment/src/commands/DescribeModelCommand.ts
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Expand Up @@ -98,6 +98,7 @@ export interface DescribeModelCommandOutput extends DescribeModelResponse, __Met
* // },
* // KmsKeyId: "STRING_VALUE",
* // },
* // ModelQuality: "QUALITY_THRESHOLD_MET" || "CANNOT_DETERMINE_QUALITY" || "POOR_QUALITY_DETECTED",
* // };
*
* ```
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1 change: 1 addition & 0 deletions clients/client-lookoutequipment/src/commands/DescribeModelVersionCommand.ts
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Expand Up @@ -93,6 +93,7 @@ export interface DescribeModelVersionCommandOutput extends DescribeModelVersionR
* // Bucket: "STRING_VALUE", // required
* // Key: "STRING_VALUE", // required
* // },
* // ModelQuality: "QUALITY_THRESHOLD_MET" || "CANNOT_DETERMINE_QUALITY" || "POOR_QUALITY_DETECTED",
* // };
*
* ```
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1 change: 1 addition & 0 deletions clients/client-lookoutequipment/src/commands/ListModelVersionsCommand.ts
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Expand Up @@ -61,6 +61,7 @@ export interface ListModelVersionsCommandOutput extends ListModelVersionsRespons
* // CreatedAt: new Date("TIMESTAMP"),
* // Status: "IN_PROGRESS" || "SUCCESS" || "FAILED" || "IMPORT_IN_PROGRESS" || "CANCELED",
* // SourceType: "TRAINING" || "RETRAINING" || "IMPORT",
* // ModelQuality: "QUALITY_THRESHOLD_MET" || "CANNOT_DETERMINE_QUALITY" || "POOR_QUALITY_DETECTED",
* // },
* // ],
* // };
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1 change: 1 addition & 0 deletions clients/client-lookoutequipment/src/commands/ListModelsCommand.ts
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Expand Up @@ -69,6 +69,7 @@ export interface ListModelsCommandOutput extends ListModelsResponse, __MetadataB
* // },
* // KmsKeyId: "STRING_VALUE",
* // },
* // ModelQuality: "QUALITY_THRESHOLD_MET" || "CANNOT_DETERMINE_QUALITY" || "POOR_QUALITY_DETECTED",
* // },
* // ],
* // };
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95 changes: 95 additions & 0 deletions clients/client-lookoutequipment/src/models/models_0.ts
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Expand Up @@ -473,6 +473,21 @@ export interface CreateInferenceSchedulerRequest {
Tags?: Tag[];
}

/**
* @public
* @enum
*/
export const ModelQuality = {
CANNOT_DETERMINE_QUALITY: "CANNOT_DETERMINE_QUALITY",
POOR_QUALITY_DETECTED: "POOR_QUALITY_DETECTED",
QUALITY_THRESHOLD_MET: "QUALITY_THRESHOLD_MET",
} as const;

/**
* @public
*/
export type ModelQuality = (typeof ModelQuality)[keyof typeof ModelQuality];

/**
* @public
* @enum
Expand Down Expand Up @@ -510,6 +525,23 @@ export interface CreateInferenceSchedulerResponse {
* <p>Indicates the status of the <code>CreateInferenceScheduler</code> operation. </p>
*/
Status?: InferenceSchedulerStatus;

/**
* @public
* <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>
*/
ModelQuality?: ModelQuality;
}

/**
Expand Down Expand Up @@ -2217,6 +2249,22 @@ export interface DescribeModelResponse {
* <p>Configuration information for the model's pointwise model diagnostics.</p>
*/
ModelDiagnosticsOutputConfiguration?: ModelDiagnosticsOutputConfiguration;

/**
* @public
* <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>
*/
ModelQuality?: ModelQuality;
}

/**
Expand Down Expand Up @@ -2493,6 +2541,22 @@ export interface DescribeModelVersionResponse {
* <p>The Amazon S3 output prefix for where Lookout for Equipment saves the pointwise model diagnostics for the model version.</p>
*/
ModelDiagnosticsResultsObject?: S3Object;

/**
* @public
* <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>
*/
ModelQuality?: ModelQuality;
}

/**
Expand Down Expand Up @@ -3717,6 +3781,22 @@ export interface ModelSummary {
* <p>Output configuration information for the pointwise model diagnostics for an Amazon Lookout for Equipment model.</p>
*/
ModelDiagnosticsOutputConfiguration?: ModelDiagnosticsOutputConfiguration;

/**
* @public
* <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>
*/
ModelQuality?: ModelQuality;
}

/**
Expand Down Expand Up @@ -3848,6 +3928,21 @@ export interface ModelVersionSummary {
* <p>Indicates how this model version was generated.</p>
*/
SourceType?: ModelVersionSourceType;

/**
* @public
* <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 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>
*/
ModelQuality?: ModelQuality;
}

/**
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4 changes: 4 additions & 0 deletions clients/client-lookoutequipment/src/protocols/Aws_json1_0.ts
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Expand Up @@ -2501,6 +2501,7 @@ const de_DescribeModelResponse = (output: any, context: __SerdeContext): Describ
ModelDiagnosticsOutputConfiguration: _json,
ModelMetrics: (_: any) => new __LazyJsonString(_),
ModelName: __expectString,
ModelQuality: __expectString,
ModelVersionActivatedAt: (_: any) => __expectNonNull(__parseEpochTimestamp(__expectNumber(_))),
NextScheduledRetrainingStartDate: (_: any) => __expectNonNull(__parseEpochTimestamp(__expectNumber(_))),
OffCondition: __expectString,
Expand Down Expand Up @@ -2545,6 +2546,7 @@ const de_DescribeModelVersionResponse = (output: any, context: __SerdeContext):
ModelDiagnosticsResultsObject: _json,
ModelMetrics: __expectString,
ModelName: __expectString,
ModelQuality: __expectString,
ModelVersion: __expectLong,
ModelVersionArn: __expectString,
OffCondition: __expectString,
Expand Down Expand Up @@ -2885,6 +2887,7 @@ const de_ModelSummary = (output: any, context: __SerdeContext): ModelSummary =>
ModelArn: __expectString,
ModelDiagnosticsOutputConfiguration: _json,
ModelName: __expectString,
ModelQuality: __expectString,
NextScheduledRetrainingStartDate: (_: any) => __expectNonNull(__parseEpochTimestamp(__expectNumber(_))),
RetrainingSchedulerStatus: __expectString,
Status: __expectString,
Expand All @@ -2911,6 +2914,7 @@ const de_ModelVersionSummary = (output: any, context: __SerdeContext): ModelVers
CreatedAt: (_: any) => __expectNonNull(__parseEpochTimestamp(__expectNumber(_))),
ModelArn: __expectString,
ModelName: __expectString,
ModelQuality: __expectString,
ModelVersion: __expectLong,
ModelVersionArn: __expectString,
SourceType: __expectString,
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53 changes: 53 additions & 0 deletions codegen/sdk-codegen/aws-models/lookoutequipment.json
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Expand Up @@ -1256,6 +1256,12 @@
"traits": {
"smithy.api#documentation": "<p>Indicates the status of the <code>CreateInferenceScheduler</code> operation. </p>"
}
},
"ModelQuality": {
"target": "com.amazonaws.lookoutequipment#ModelQuality",
"traits": {
"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>"
}
}
},
"traits": {
Expand Down Expand Up @@ -3265,6 +3271,12 @@
"traits": {
"smithy.api#documentation": "<p>Configuration information for the model's pointwise model diagnostics.</p>"
}
},
"ModelQuality": {
"target": "com.amazonaws.lookoutequipment#ModelQuality",
"traits": {
"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>"
}
}
},
"traits": {
Expand Down Expand Up @@ -3522,6 +3534,12 @@
"traits": {
"smithy.api#documentation": "<p>The Amazon S3 output prefix for where Lookout for Equipment saves the pointwise model diagnostics for the model version.</p>"
}
},
"ModelQuality": {
"target": "com.amazonaws.lookoutequipment#ModelQuality",
"traits": {
"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>"
}
}
},
"traits": {
Expand Down Expand Up @@ -6173,6 +6191,29 @@
}
}
},
"com.amazonaws.lookoutequipment#ModelQuality": {
"type": "enum",
"members": {
"QUALITY_THRESHOLD_MET": {
"target": "smithy.api#Unit",
"traits": {
"smithy.api#enumValue": "QUALITY_THRESHOLD_MET"
}
},
"CANNOT_DETERMINE_QUALITY": {
"target": "smithy.api#Unit",
"traits": {
"smithy.api#enumValue": "CANNOT_DETERMINE_QUALITY"
}
},
"POOR_QUALITY_DETECTED": {
"target": "smithy.api#Unit",
"traits": {
"smithy.api#enumValue": "POOR_QUALITY_DETECTED"
}
}
}
},
"com.amazonaws.lookoutequipment#ModelStatus": {
"type": "enum",
"members": {
Expand Down Expand Up @@ -6291,6 +6332,12 @@
},
"ModelDiagnosticsOutputConfiguration": {
"target": "com.amazonaws.lookoutequipment#ModelDiagnosticsOutputConfiguration"
},
"ModelQuality": {
"target": "com.amazonaws.lookoutequipment#ModelQuality",
"traits": {
"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>"
}
}
},
"traits": {
Expand Down Expand Up @@ -6423,6 +6470,12 @@
"traits": {
"smithy.api#documentation": "<p>Indicates how this model version was generated.</p>"
}
},
"ModelQuality": {
"target": "com.amazonaws.lookoutequipment#ModelQuality",
"traits": {
"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>"
}
}
},
"traits": {
Expand Down

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