/*
 * 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.rekognition.model;

import java.io.Serializable;
import javax.annotation.Generated;

import com.amazonaws.AmazonWebServiceRequest;

@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class StartProjectVersionRequest extends com.amazonaws.AmazonWebServiceRequest implements Serializable, Cloneable {

    /**
     * <p>
     * The Amazon Resource Name(ARN) of the model version that you want to start.
     * </p>
     */
    private String projectVersionArn;
    /**
     * <p>
     * The minimum number of inference units to use. A single inference unit represents 1 hour of processing.
     * </p>
     * <p>
     * For information about the number of transactions per second (TPS) that an inference unit can support, see
     * <i>Running a trained Amazon Rekognition Custom Labels model</i> in the Amazon Rekognition Custom Labels Guide.
     * </p>
     * <p>
     * Use a higher number to increase the TPS throughput of your model. You are charged for the number of inference
     * units that you use.
     * </p>
     */
    private Integer minInferenceUnits;
    /**
     * <p>
     * The maximum number of inference units to use for auto-scaling the model. If you don't specify a value, Amazon
     * Rekognition Custom Labels doesn't auto-scale the model.
     * </p>
     */
    private Integer maxInferenceUnits;

    /**
     * <p>
     * The Amazon Resource Name(ARN) of the model version that you want to start.
     * </p>
     * 
     * @param projectVersionArn
     *        The Amazon Resource Name(ARN) of the model version that you want to start.
     */

    public void setProjectVersionArn(String projectVersionArn) {
        this.projectVersionArn = projectVersionArn;
    }

    /**
     * <p>
     * The Amazon Resource Name(ARN) of the model version that you want to start.
     * </p>
     * 
     * @return The Amazon Resource Name(ARN) of the model version that you want to start.
     */

    public String getProjectVersionArn() {
        return this.projectVersionArn;
    }

    /**
     * <p>
     * The Amazon Resource Name(ARN) of the model version that you want to start.
     * </p>
     * 
     * @param projectVersionArn
     *        The Amazon Resource Name(ARN) of the model version that you want to start.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public StartProjectVersionRequest withProjectVersionArn(String projectVersionArn) {
        setProjectVersionArn(projectVersionArn);
        return this;
    }

    /**
     * <p>
     * The minimum number of inference units to use. A single inference unit represents 1 hour of processing.
     * </p>
     * <p>
     * For information about the number of transactions per second (TPS) that an inference unit can support, see
     * <i>Running a trained Amazon Rekognition Custom Labels model</i> in the Amazon Rekognition Custom Labels Guide.
     * </p>
     * <p>
     * Use a higher number to increase the TPS throughput of your model. You are charged for the number of inference
     * units that you use.
     * </p>
     * 
     * @param minInferenceUnits
     *        The minimum number of inference units to use. A single inference unit represents 1 hour of processing.
     *        </p>
     *        <p>
     *        For information about the number of transactions per second (TPS) that an inference unit can support, see
     *        <i>Running a trained Amazon Rekognition Custom Labels model</i> in the Amazon Rekognition Custom Labels
     *        Guide.
     *        </p>
     *        <p>
     *        Use a higher number to increase the TPS throughput of your model. You are charged for the number of
     *        inference units that you use.
     */

    public void setMinInferenceUnits(Integer minInferenceUnits) {
        this.minInferenceUnits = minInferenceUnits;
    }

    /**
     * <p>
     * The minimum number of inference units to use. A single inference unit represents 1 hour of processing.
     * </p>
     * <p>
     * For information about the number of transactions per second (TPS) that an inference unit can support, see
     * <i>Running a trained Amazon Rekognition Custom Labels model</i> in the Amazon Rekognition Custom Labels Guide.
     * </p>
     * <p>
     * Use a higher number to increase the TPS throughput of your model. You are charged for the number of inference
     * units that you use.
     * </p>
     * 
     * @return The minimum number of inference units to use. A single inference unit represents 1 hour of processing.
     *         </p>
     *         <p>
     *         For information about the number of transactions per second (TPS) that an inference unit can support, see
     *         <i>Running a trained Amazon Rekognition Custom Labels model</i> in the Amazon Rekognition Custom Labels
     *         Guide.
     *         </p>
     *         <p>
     *         Use a higher number to increase the TPS throughput of your model. You are charged for the number of
     *         inference units that you use.
     */

    public Integer getMinInferenceUnits() {
        return this.minInferenceUnits;
    }

    /**
     * <p>
     * The minimum number of inference units to use. A single inference unit represents 1 hour of processing.
     * </p>
     * <p>
     * For information about the number of transactions per second (TPS) that an inference unit can support, see
     * <i>Running a trained Amazon Rekognition Custom Labels model</i> in the Amazon Rekognition Custom Labels Guide.
     * </p>
     * <p>
     * Use a higher number to increase the TPS throughput of your model. You are charged for the number of inference
     * units that you use.
     * </p>
     * 
     * @param minInferenceUnits
     *        The minimum number of inference units to use. A single inference unit represents 1 hour of processing.
     *        </p>
     *        <p>
     *        For information about the number of transactions per second (TPS) that an inference unit can support, see
     *        <i>Running a trained Amazon Rekognition Custom Labels model</i> in the Amazon Rekognition Custom Labels
     *        Guide.
     *        </p>
     *        <p>
     *        Use a higher number to increase the TPS throughput of your model. You are charged for the number of
     *        inference units that you use.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public StartProjectVersionRequest withMinInferenceUnits(Integer minInferenceUnits) {
        setMinInferenceUnits(minInferenceUnits);
        return this;
    }

    /**
     * <p>
     * The maximum number of inference units to use for auto-scaling the model. If you don't specify a value, Amazon
     * Rekognition Custom Labels doesn't auto-scale the model.
     * </p>
     * 
     * @param maxInferenceUnits
     *        The maximum number of inference units to use for auto-scaling the model. If you don't specify a value,
     *        Amazon Rekognition Custom Labels doesn't auto-scale the model.
     */

    public void setMaxInferenceUnits(Integer maxInferenceUnits) {
        this.maxInferenceUnits = maxInferenceUnits;
    }

    /**
     * <p>
     * The maximum number of inference units to use for auto-scaling the model. If you don't specify a value, Amazon
     * Rekognition Custom Labels doesn't auto-scale the model.
     * </p>
     * 
     * @return The maximum number of inference units to use for auto-scaling the model. If you don't specify a value,
     *         Amazon Rekognition Custom Labels doesn't auto-scale the model.
     */

    public Integer getMaxInferenceUnits() {
        return this.maxInferenceUnits;
    }

    /**
     * <p>
     * The maximum number of inference units to use for auto-scaling the model. If you don't specify a value, Amazon
     * Rekognition Custom Labels doesn't auto-scale the model.
     * </p>
     * 
     * @param maxInferenceUnits
     *        The maximum number of inference units to use for auto-scaling the model. If you don't specify a value,
     *        Amazon Rekognition Custom Labels doesn't auto-scale the model.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public StartProjectVersionRequest withMaxInferenceUnits(Integer maxInferenceUnits) {
        setMaxInferenceUnits(maxInferenceUnits);
        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 (getProjectVersionArn() != null)
            sb.append("ProjectVersionArn: ").append(getProjectVersionArn()).append(",");
        if (getMinInferenceUnits() != null)
            sb.append("MinInferenceUnits: ").append(getMinInferenceUnits()).append(",");
        if (getMaxInferenceUnits() != null)
            sb.append("MaxInferenceUnits: ").append(getMaxInferenceUnits());
        sb.append("}");
        return sb.toString();
    }

    @Override
    public boolean equals(Object obj) {
        if (this == obj)
            return true;
        if (obj == null)
            return false;

        if (obj instanceof StartProjectVersionRequest == false)
            return false;
        StartProjectVersionRequest other = (StartProjectVersionRequest) obj;
        if (other.getProjectVersionArn() == null ^ this.getProjectVersionArn() == null)
            return false;
        if (other.getProjectVersionArn() != null && other.getProjectVersionArn().equals(this.getProjectVersionArn()) == false)
            return false;
        if (other.getMinInferenceUnits() == null ^ this.getMinInferenceUnits() == null)
            return false;
        if (other.getMinInferenceUnits() != null && other.getMinInferenceUnits().equals(this.getMinInferenceUnits()) == false)
            return false;
        if (other.getMaxInferenceUnits() == null ^ this.getMaxInferenceUnits() == null)
            return false;
        if (other.getMaxInferenceUnits() != null && other.getMaxInferenceUnits().equals(this.getMaxInferenceUnits()) == false)
            return false;
        return true;
    }

    @Override
    public int hashCode() {
        final int prime = 31;
        int hashCode = 1;

        hashCode = prime * hashCode + ((getProjectVersionArn() == null) ? 0 : getProjectVersionArn().hashCode());
        hashCode = prime * hashCode + ((getMinInferenceUnits() == null) ? 0 : getMinInferenceUnits().hashCode());
        hashCode = prime * hashCode + ((getMaxInferenceUnits() == null) ? 0 : getMaxInferenceUnits().hashCode());
        return hashCode;
    }

    @Override
    public StartProjectVersionRequest clone() {
        return (StartProjectVersionRequest) super.clone();
    }

}