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awstools
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feat(client-sagemaker): Amazon Sagemaker Autopilot now supports Text Generation jobs.
1 parent 0bc9a39 commit fd8ca90

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+851
-551
lines changed

‎clients/client-sagemaker/src/commands/CreateAutoMLJobCommand.ts

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@@ -43,7 +43,8 @@ export interface CreateAutoMLJobCommandOutput extends CreateAutoMLJobResponse, _
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* <p>
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* <code>CreateAutoMLJobV2</code> can manage tabular problem types identical to those of
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* its previous version <code>CreateAutoMLJob</code>, as well as time-series forecasting,
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* and non-tabular problem types such as image or text classification.</p>
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* non-tabular problem types such as image or text classification, and text generation
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* (LLMs fine-tuning).</p>
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* <p>Find guidelines about how to migrate a <code>CreateAutoMLJob</code> to
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* <code>CreateAutoMLJobV2</code> in <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-create-experiment-api.html#autopilot-create-experiment-api-migrate-v1-v2">Migrate a CreateAutoMLJob to CreateAutoMLJobV2</a>.</p>
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* </note>

‎clients/client-sagemaker/src/commands/CreateAutoMLJobV2Command.ts

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@@ -45,7 +45,8 @@ export interface CreateAutoMLJobV2CommandOutput extends CreateAutoMLJobV2Respons
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* <p>
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* <code>CreateAutoMLJobV2</code> can manage tabular problem types identical to those of
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* its previous version <code>CreateAutoMLJob</code>, as well as time-series forecasting,
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* and non-tabular problem types such as image or text classification.</p>
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* non-tabular problem types such as image or text classification, and text generation
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* (LLMs fine-tuning).</p>
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* <p>Find guidelines about how to migrate a <code>CreateAutoMLJob</code> to
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* <code>CreateAutoMLJobV2</code> in <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-create-experiment-api.html#autopilot-create-experiment-api-migrate-v1-v2">Migrate a CreateAutoMLJob to CreateAutoMLJobV2</a>.</p>
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* </note>
@@ -152,6 +153,14 @@ export interface CreateAutoMLJobV2CommandOutput extends CreateAutoMLJobV2Respons
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* },
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* ],
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* },
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* TextGenerationJobConfig: { // TextGenerationJobConfig
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* CompletionCriteria: {
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* MaxCandidates: Number("int"),
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* MaxRuntimePerTrainingJobInSeconds: Number("int"),
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* MaxAutoMLJobRuntimeInSeconds: Number("int"),
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* },
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* BaseModelName: "STRING_VALUE",
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* },
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* },
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* RoleArn: "STRING_VALUE", // required
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* Tags: [ // TagList

‎clients/client-sagemaker/src/commands/CreateDataQualityJobDefinitionCommand.ts

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@@ -14,8 +14,7 @@ import {
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SMITHY_CONTEXT_KEY,
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} from "@smithy/types";
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import { CreateDataQualityJobDefinitionRequest } from "../models/models_0";
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import { CreateDataQualityJobDefinitionResponse } from "../models/models_1";
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import { CreateDataQualityJobDefinitionRequest, CreateDataQualityJobDefinitionResponse } from "../models/models_1";
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import {
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de_CreateDataQualityJobDefinitionCommand,
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se_CreateDataQualityJobDefinitionCommand,

‎clients/client-sagemaker/src/commands/DeleteContextCommand.ts

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@@ -14,7 +14,7 @@ import {
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SMITHY_CONTEXT_KEY,
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} from "@smithy/types";
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import { DeleteContextRequest, DeleteContextResponse } from "../models/models_1";
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import { DeleteContextRequest, DeleteContextResponse } from "../models/models_2";
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import { de_DeleteContextCommand, se_DeleteContextCommand } from "../protocols/Aws_json1_1";
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import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient";
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‎clients/client-sagemaker/src/commands/DescribeAutoMLJobCommand.ts

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@@ -163,7 +163,7 @@ export interface DescribeAutoMLJobCommandOutput extends DescribeAutoMLJobRespons
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* // MetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro" || "MAPE" || "MASE" || "WAPE" || "AverageWeightedQuantileLoss",
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* // Value: Number("float"),
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* // Set: "Train" || "Validation" || "Test",
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* // StandardMetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro" || "LogLoss" || "InferenceLatency" || "MAPE" || "MASE" || "WAPE" || "AverageWeightedQuantileLoss",
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* // StandardMetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro" || "LogLoss" || "InferenceLatency" || "MAPE" || "MASE" || "WAPE" || "AverageWeightedQuantileLoss" || "Rouge1" || "Rouge2" || "RougeL" || "RougeLSum" || "Perplexity" || "ValidationLoss" || "TrainingLoss",
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* // },
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* // ],
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* // },

‎clients/client-sagemaker/src/commands/DescribeAutoMLJobV2Command.ts

Lines changed: 14 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -149,6 +149,14 @@ export interface DescribeAutoMLJobV2CommandOutput extends DescribeAutoMLJobV2Res
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* // },
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* // ],
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* // },
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* // TextGenerationJobConfig: { // TextGenerationJobConfig
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* // CompletionCriteria: {
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* // MaxCandidates: Number("int"),
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* // MaxRuntimePerTrainingJobInSeconds: Number("int"),
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* // MaxAutoMLJobRuntimeInSeconds: Number("int"),
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* // },
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* // BaseModelName: "STRING_VALUE",
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* // },
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* // },
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* // CreationTime: new Date("TIMESTAMP"), // required
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* // EndTime: new Date("TIMESTAMP"),
@@ -200,7 +208,7 @@ export interface DescribeAutoMLJobV2CommandOutput extends DescribeAutoMLJobV2Res
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* // MetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro" || "MAPE" || "MASE" || "WAPE" || "AverageWeightedQuantileLoss",
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* // Value: Number("float"),
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* // Set: "Train" || "Validation" || "Test",
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* // StandardMetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro" || "LogLoss" || "InferenceLatency" || "MAPE" || "MASE" || "WAPE" || "AverageWeightedQuantileLoss",
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* // StandardMetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro" || "LogLoss" || "InferenceLatency" || "MAPE" || "MASE" || "WAPE" || "AverageWeightedQuantileLoss" || "Rouge1" || "Rouge2" || "RougeL" || "RougeLSum" || "Perplexity" || "ValidationLoss" || "TrainingLoss",
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* // },
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* // ],
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* // },
@@ -248,18 +256,17 @@ export interface DescribeAutoMLJobV2CommandOutput extends DescribeAutoMLJobV2Res
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* // AutoMLJobObjective: {
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* // MetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro" || "MAPE" || "MASE" || "WAPE" || "AverageWeightedQuantileLoss", // required
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* // },
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* // CompletionCriteria: {
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* // MaxCandidates: Number("int"),
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* // MaxRuntimePerTrainingJobInSeconds: Number("int"),
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* // MaxAutoMLJobRuntimeInSeconds: Number("int"),
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* // },
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* // CompletionCriteria: "<AutoMLJobCompletionCriteria>",
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* // AutoMLProblemTypeResolvedAttributes: { // AutoMLProblemTypeResolvedAttributes Union: only one key present
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* // TabularResolvedAttributes: { // TabularResolvedAttributes
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* // ProblemType: "BinaryClassification" || "MulticlassClassification" || "Regression",
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* // },
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* // TextGenerationResolvedAttributes: { // TextGenerationResolvedAttributes
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* // BaseModelName: "STRING_VALUE",
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* // },
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* // },
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* // },
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* // AutoMLProblemTypeConfigName: "ImageClassification" || "TextClassification" || "Tabular" || "TimeSeriesForecasting",
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* // AutoMLProblemTypeConfigName: "ImageClassification" || "TextClassification" || "Tabular" || "TimeSeriesForecasting" || "TextGeneration",
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* // };
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*
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* ```

‎clients/client-sagemaker/src/commands/ListCandidatesForAutoMLJobCommand.ts

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@@ -98,7 +98,7 @@ export interface ListCandidatesForAutoMLJobCommandOutput extends ListCandidatesF
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* // MetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro" || "MAPE" || "MASE" || "WAPE" || "AverageWeightedQuantileLoss",
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* // Value: Number("float"),
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* // Set: "Train" || "Validation" || "Test",
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* // StandardMetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro" || "LogLoss" || "InferenceLatency" || "MAPE" || "MASE" || "WAPE" || "AverageWeightedQuantileLoss",
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* // StandardMetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro" || "LogLoss" || "InferenceLatency" || "MAPE" || "MASE" || "WAPE" || "AverageWeightedQuantileLoss" || "Rouge1" || "Rouge2" || "RougeL" || "RougeLSum" || "Perplexity" || "ValidationLoss" || "TrainingLoss",
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* // },
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* // ],
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* // },

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