/* * Copyright 2018-2023 Amazon.com, Inc. or its affiliates. All Rights Reserved. * * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with * the License. A copy of the License is located at * * http://aws.amazon.com/apache2.0 * * or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR * CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions * and limitations under the License. */ package com.amazonaws.services.sagemaker.model; import java.io.Serializable; import javax.annotation.Generated; import com.amazonaws.protocol.StructuredPojo; import com.amazonaws.protocol.ProtocolMarshaller; /** *

* Defines under what conditions SageMaker creates a human loop. Used within CreateFlowDefinition. See HumanLoopActivationConditionsConfig for the required format of activation conditions. *

* * @see AWS API Documentation */ @Generated("com.amazonaws:aws-java-sdk-code-generator") public class HumanLoopActivationConditionsConfig implements Serializable, Cloneable, StructuredPojo { /** *

* JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are created * against the configured work team. The set of conditions is different for Rekognition and Textract. For more * information about how to structure the JSON, see JSON Schema * for Human Loop Activation Conditions in Amazon Augmented AI in the Amazon SageMaker Developer Guide. *

*/ private String humanLoopActivationConditions; /** *

* This field's value must be valid JSON according to RFC 7159, including the opening and closing braces. For * example: '{"key": "value"}'. *

* The AWS SDK for Java performs a Base64 encoding on this field before sending this request to the AWS service. * Users of the SDK should not perform Base64 encoding on this field. *

* This field's value will be valid JSON according to RFC 7159, including the opening and closing braces. For * example: '{"key": "value"}'. *

* * @return JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are * created against the configured work team. The set of conditions is different for Rekognition and * Textract. For more information about how to structure the JSON, see JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI in the Amazon SageMaker * Developer Guide. */ public String getHumanLoopActivationConditions() { return this.humanLoopActivationConditions; } /** *

* This field's value must be valid JSON according to RFC 7159, including the opening and closing braces. For * example: '{"key": "value"}'. *

* The AWS SDK for Java performs a Base64 encoding on this field before sending this request to the AWS service. * Users of the SDK should not perform Base64 encoding on this field. *

* * @param humanLoopActivationConditions * JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are * created against the configured work team. The set of conditions is different for Rekognition and Textract. * For more information about how to structure the JSON, see JSON * Schema for Human Loop Activation Conditions in Amazon Augmented AI in the Amazon SageMaker * Developer Guide. * @return Returns a reference to this object so that method calls can be chained together. */ public HumanLoopActivationConditionsConfig withHumanLoopActivationConditions(String humanLoopActivationConditions) { setHumanLoopActivationConditions(humanLoopActivationConditions); return this; } /** * Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be * redacted from this string using a placeholder value. * * @return A string representation of this object. * * @see java.lang.Object#toString() */ @Override public String toString() { StringBuilder sb = new StringBuilder(); sb.append("{"); if (getHumanLoopActivationConditions() != null) sb.append("HumanLoopActivationConditions: ").append(getHumanLoopActivationConditions()); sb.append("}"); return sb.toString(); } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (obj instanceof HumanLoopActivationConditionsConfig == false) return false; HumanLoopActivationConditionsConfig other = (HumanLoopActivationConditionsConfig) obj; if (other.getHumanLoopActivationConditions() == null ^ this.getHumanLoopActivationConditions() == null) return false; if (other.getHumanLoopActivationConditions() != null && other.getHumanLoopActivationConditions().equals(this.getHumanLoopActivationConditions()) == false) return false; return true; } @Override public int hashCode() { final int prime = 31; int hashCode = 1; hashCode = prime * hashCode + ((getHumanLoopActivationConditions() == null) ? 0 : getHumanLoopActivationConditions().hashCode()); return hashCode; } @Override public HumanLoopActivationConditionsConfig clone() { try { return (HumanLoopActivationConditionsConfig) super.clone(); } catch (CloneNotSupportedException e) { throw new IllegalStateException("Got a CloneNotSupportedException from Object.clone() " + "even though we're Cloneable!", e); } } @com.amazonaws.annotation.SdkInternalApi @Override public void marshall(ProtocolMarshaller protocolMarshaller) { com.amazonaws.services.sagemaker.model.transform.HumanLoopActivationConditionsConfigMarshaller.getInstance().marshall(this, protocolMarshaller); } }