/*
 * Copyright 2020 Google LLC
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     https://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License 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.
 */
// Generated by the protocol buffer compiler.  DO NOT EDIT!
// source: google/cloud/datalabeling/v1beta1/evaluation_job.proto

package com.google.cloud.datalabeling.v1beta1;

/**
 *
 *
 * <pre>
 * Configures specific details of how a continuous evaluation job works. Provide
 * this configuration when you create an EvaluationJob.
 * </pre>
 *
 * Protobuf type {@code google.cloud.datalabeling.v1beta1.EvaluationJobConfig}
 */
public final class EvaluationJobConfig extends com.google.protobuf.GeneratedMessageV3
    implements
    // @@protoc_insertion_point(message_implements:google.cloud.datalabeling.v1beta1.EvaluationJobConfig)
    EvaluationJobConfigOrBuilder {
  private static final long serialVersionUID = 0L;
  // Use EvaluationJobConfig.newBuilder() to construct.
  private EvaluationJobConfig(com.google.protobuf.GeneratedMessageV3.Builder<?> builder) {
    super(builder);
  }

  private EvaluationJobConfig() {}

  @java.lang.Override
  @SuppressWarnings({"unused"})
  protected java.lang.Object newInstance(UnusedPrivateParameter unused) {
    return new EvaluationJobConfig();
  }

  @java.lang.Override
  public final com.google.protobuf.UnknownFieldSet getUnknownFields() {
    return this.unknownFields;
  }

  public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
    return com.google.cloud.datalabeling.v1beta1.EvaluationJobOuterClass
        .internal_static_google_cloud_datalabeling_v1beta1_EvaluationJobConfig_descriptor;
  }

  @SuppressWarnings({"rawtypes"})
  @java.lang.Override
  protected com.google.protobuf.MapField internalGetMapField(int number) {
    switch (number) {
      case 9:
        return internalGetBigqueryImportKeys();
      default:
        throw new RuntimeException("Invalid map field number: " + number);
    }
  }

  @java.lang.Override
  protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
      internalGetFieldAccessorTable() {
    return com.google.cloud.datalabeling.v1beta1.EvaluationJobOuterClass
        .internal_static_google_cloud_datalabeling_v1beta1_EvaluationJobConfig_fieldAccessorTable
        .ensureFieldAccessorsInitialized(
            com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig.class,
            com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig.Builder.class);
  }

  private int humanAnnotationRequestConfigCase_ = 0;
  private java.lang.Object humanAnnotationRequestConfig_;

  public enum HumanAnnotationRequestConfigCase
      implements
          com.google.protobuf.Internal.EnumLite,
          com.google.protobuf.AbstractMessage.InternalOneOfEnum {
    IMAGE_CLASSIFICATION_CONFIG(4),
    BOUNDING_POLY_CONFIG(5),
    TEXT_CLASSIFICATION_CONFIG(8),
    HUMANANNOTATIONREQUESTCONFIG_NOT_SET(0);
    private final int value;

    private HumanAnnotationRequestConfigCase(int value) {
      this.value = value;
    }
    /**
     * @param value The number of the enum to look for.
     * @return The enum associated with the given number.
     * @deprecated Use {@link #forNumber(int)} instead.
     */
    @java.lang.Deprecated
    public static HumanAnnotationRequestConfigCase valueOf(int value) {
      return forNumber(value);
    }

    public static HumanAnnotationRequestConfigCase forNumber(int value) {
      switch (value) {
        case 4:
          return IMAGE_CLASSIFICATION_CONFIG;
        case 5:
          return BOUNDING_POLY_CONFIG;
        case 8:
          return TEXT_CLASSIFICATION_CONFIG;
        case 0:
          return HUMANANNOTATIONREQUESTCONFIG_NOT_SET;
        default:
          return null;
      }
    }

    public int getNumber() {
      return this.value;
    }
  };

  public HumanAnnotationRequestConfigCase getHumanAnnotationRequestConfigCase() {
    return HumanAnnotationRequestConfigCase.forNumber(humanAnnotationRequestConfigCase_);
  }

  public static final int IMAGE_CLASSIFICATION_CONFIG_FIELD_NUMBER = 4;
  /**
   *
   *
   * <pre>
   * Specify this field if your model version performs image classification or
   * general classification.
   * `annotationSpecSet` in this configuration must match
   * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
   * `allowMultiLabel` in this configuration must match
   * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
   * </pre>
   *
   * <code>
   * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
   * </code>
   *
   * @return Whether the imageClassificationConfig field is set.
   */
  @java.lang.Override
  public boolean hasImageClassificationConfig() {
    return humanAnnotationRequestConfigCase_ == 4;
  }
  /**
   *
   *
   * <pre>
   * Specify this field if your model version performs image classification or
   * general classification.
   * `annotationSpecSet` in this configuration must match
   * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
   * `allowMultiLabel` in this configuration must match
   * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
   * </pre>
   *
   * <code>
   * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
   * </code>
   *
   * @return The imageClassificationConfig.
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig
      getImageClassificationConfig() {
    if (humanAnnotationRequestConfigCase_ == 4) {
      return (com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig)
          humanAnnotationRequestConfig_;
    }
    return com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.getDefaultInstance();
  }
  /**
   *
   *
   * <pre>
   * Specify this field if your model version performs image classification or
   * general classification.
   * `annotationSpecSet` in this configuration must match
   * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
   * `allowMultiLabel` in this configuration must match
   * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
   * </pre>
   *
   * <code>
   * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
   * </code>
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.ImageClassificationConfigOrBuilder
      getImageClassificationConfigOrBuilder() {
    if (humanAnnotationRequestConfigCase_ == 4) {
      return (com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig)
          humanAnnotationRequestConfig_;
    }
    return com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.getDefaultInstance();
  }

  public static final int BOUNDING_POLY_CONFIG_FIELD_NUMBER = 5;
  /**
   *
   *
   * <pre>
   * Specify this field if your model version performs image object detection
   * (bounding box detection).
   * `annotationSpecSet` in this configuration must match
   * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
   *
   * @return Whether the boundingPolyConfig field is set.
   */
  @java.lang.Override
  public boolean hasBoundingPolyConfig() {
    return humanAnnotationRequestConfigCase_ == 5;
  }
  /**
   *
   *
   * <pre>
   * Specify this field if your model version performs image object detection
   * (bounding box detection).
   * `annotationSpecSet` in this configuration must match
   * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
   *
   * @return The boundingPolyConfig.
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig getBoundingPolyConfig() {
    if (humanAnnotationRequestConfigCase_ == 5) {
      return (com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig)
          humanAnnotationRequestConfig_;
    }
    return com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.getDefaultInstance();
  }
  /**
   *
   *
   * <pre>
   * Specify this field if your model version performs image object detection
   * (bounding box detection).
   * `annotationSpecSet` in this configuration must match
   * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.BoundingPolyConfigOrBuilder
      getBoundingPolyConfigOrBuilder() {
    if (humanAnnotationRequestConfigCase_ == 5) {
      return (com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig)
          humanAnnotationRequestConfig_;
    }
    return com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.getDefaultInstance();
  }

  public static final int TEXT_CLASSIFICATION_CONFIG_FIELD_NUMBER = 8;
  /**
   *
   *
   * <pre>
   * Specify this field if your model version performs text classification.
   * `annotationSpecSet` in this configuration must match
   * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
   * `allowMultiLabel` in this configuration must match
   * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
   * </pre>
   *
   * <code>
   * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
   * </code>
   *
   * @return Whether the textClassificationConfig field is set.
   */
  @java.lang.Override
  public boolean hasTextClassificationConfig() {
    return humanAnnotationRequestConfigCase_ == 8;
  }
  /**
   *
   *
   * <pre>
   * Specify this field if your model version performs text classification.
   * `annotationSpecSet` in this configuration must match
   * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
   * `allowMultiLabel` in this configuration must match
   * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
   * </pre>
   *
   * <code>
   * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
   * </code>
   *
   * @return The textClassificationConfig.
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.TextClassificationConfig
      getTextClassificationConfig() {
    if (humanAnnotationRequestConfigCase_ == 8) {
      return (com.google.cloud.datalabeling.v1beta1.TextClassificationConfig)
          humanAnnotationRequestConfig_;
    }
    return com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.getDefaultInstance();
  }
  /**
   *
   *
   * <pre>
   * Specify this field if your model version performs text classification.
   * `annotationSpecSet` in this configuration must match
   * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
   * `allowMultiLabel` in this configuration must match
   * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
   * </pre>
   *
   * <code>
   * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
   * </code>
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.TextClassificationConfigOrBuilder
      getTextClassificationConfigOrBuilder() {
    if (humanAnnotationRequestConfigCase_ == 8) {
      return (com.google.cloud.datalabeling.v1beta1.TextClassificationConfig)
          humanAnnotationRequestConfig_;
    }
    return com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.getDefaultInstance();
  }

  public static final int INPUT_CONFIG_FIELD_NUMBER = 1;
  private com.google.cloud.datalabeling.v1beta1.InputConfig inputConfig_;
  /**
   *
   *
   * <pre>
   * Rquired. Details for the sampled prediction input. Within this
   * configuration, there are requirements for several fields:
   * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
   * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
   *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
   *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
   * * If your machine learning model performs classification, you must specify
   *   `classificationMetadata.isMultiLabel`.
   * * You must specify `bigquerySource` (not `gcsSource`).
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
   *
   * @return Whether the inputConfig field is set.
   */
  @java.lang.Override
  public boolean hasInputConfig() {
    return inputConfig_ != null;
  }
  /**
   *
   *
   * <pre>
   * Rquired. Details for the sampled prediction input. Within this
   * configuration, there are requirements for several fields:
   * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
   * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
   *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
   *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
   * * If your machine learning model performs classification, you must specify
   *   `classificationMetadata.isMultiLabel`.
   * * You must specify `bigquerySource` (not `gcsSource`).
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
   *
   * @return The inputConfig.
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.InputConfig getInputConfig() {
    return inputConfig_ == null
        ? com.google.cloud.datalabeling.v1beta1.InputConfig.getDefaultInstance()
        : inputConfig_;
  }
  /**
   *
   *
   * <pre>
   * Rquired. Details for the sampled prediction input. Within this
   * configuration, there are requirements for several fields:
   * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
   * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
   *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
   *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
   * * If your machine learning model performs classification, you must specify
   *   `classificationMetadata.isMultiLabel`.
   * * You must specify `bigquerySource` (not `gcsSource`).
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.InputConfigOrBuilder getInputConfigOrBuilder() {
    return inputConfig_ == null
        ? com.google.cloud.datalabeling.v1beta1.InputConfig.getDefaultInstance()
        : inputConfig_;
  }

  public static final int EVALUATION_CONFIG_FIELD_NUMBER = 2;
  private com.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluationConfig_;
  /**
   *
   *
   * <pre>
   * Required. Details for calculating evaluation metrics and creating
   * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
   * detection, you must specify the `boundingBoxEvaluationOptions` field within
   * this configuration. Otherwise, provide an empty object for this
   * configuration.
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
   *
   * @return Whether the evaluationConfig field is set.
   */
  @java.lang.Override
  public boolean hasEvaluationConfig() {
    return evaluationConfig_ != null;
  }
  /**
   *
   *
   * <pre>
   * Required. Details for calculating evaluation metrics and creating
   * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
   * detection, you must specify the `boundingBoxEvaluationOptions` field within
   * this configuration. Otherwise, provide an empty object for this
   * configuration.
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
   *
   * @return The evaluationConfig.
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.EvaluationConfig getEvaluationConfig() {
    return evaluationConfig_ == null
        ? com.google.cloud.datalabeling.v1beta1.EvaluationConfig.getDefaultInstance()
        : evaluationConfig_;
  }
  /**
   *
   *
   * <pre>
   * Required. Details for calculating evaluation metrics and creating
   * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
   * detection, you must specify the `boundingBoxEvaluationOptions` field within
   * this configuration. Otherwise, provide an empty object for this
   * configuration.
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.EvaluationConfigOrBuilder
      getEvaluationConfigOrBuilder() {
    return evaluationConfig_ == null
        ? com.google.cloud.datalabeling.v1beta1.EvaluationConfig.getDefaultInstance()
        : evaluationConfig_;
  }

  public static final int HUMAN_ANNOTATION_CONFIG_FIELD_NUMBER = 3;
  private com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig humanAnnotationConfig_;
  /**
   *
   *
   * <pre>
   * Optional. Details for human annotation of your data. If you set
   * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
   * `true` for this evaluation job, then you must specify this field. If you
   * plan to provide your own ground truth labels, then omit this field.
   * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
   * specify this field. Provide the name of the instruction resource in the
   * `instruction` field within this configuration.
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
   * </code>
   *
   * @return Whether the humanAnnotationConfig field is set.
   */
  @java.lang.Override
  public boolean hasHumanAnnotationConfig() {
    return humanAnnotationConfig_ != null;
  }
  /**
   *
   *
   * <pre>
   * Optional. Details for human annotation of your data. If you set
   * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
   * `true` for this evaluation job, then you must specify this field. If you
   * plan to provide your own ground truth labels, then omit this field.
   * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
   * specify this field. Provide the name of the instruction resource in the
   * `instruction` field within this configuration.
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
   * </code>
   *
   * @return The humanAnnotationConfig.
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig getHumanAnnotationConfig() {
    return humanAnnotationConfig_ == null
        ? com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig.getDefaultInstance()
        : humanAnnotationConfig_;
  }
  /**
   *
   *
   * <pre>
   * Optional. Details for human annotation of your data. If you set
   * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
   * `true` for this evaluation job, then you must specify this field. If you
   * plan to provide your own ground truth labels, then omit this field.
   * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
   * specify this field. Provide the name of the instruction resource in the
   * `instruction` field within this configuration.
   * </pre>
   *
   * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
   * </code>
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfigOrBuilder
      getHumanAnnotationConfigOrBuilder() {
    return humanAnnotationConfig_ == null
        ? com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig.getDefaultInstance()
        : humanAnnotationConfig_;
  }

  public static final int BIGQUERY_IMPORT_KEYS_FIELD_NUMBER = 9;

  private static final class BigqueryImportKeysDefaultEntryHolder {
    static final com.google.protobuf.MapEntry<java.lang.String, java.lang.String> defaultEntry =
        com.google.protobuf.MapEntry.<java.lang.String, java.lang.String>newDefaultInstance(
            com.google.cloud.datalabeling.v1beta1.EvaluationJobOuterClass
                .internal_static_google_cloud_datalabeling_v1beta1_EvaluationJobConfig_BigqueryImportKeysEntry_descriptor,
            com.google.protobuf.WireFormat.FieldType.STRING,
            "",
            com.google.protobuf.WireFormat.FieldType.STRING,
            "");
  }

  @SuppressWarnings("serial")
  private com.google.protobuf.MapField<java.lang.String, java.lang.String> bigqueryImportKeys_;

  private com.google.protobuf.MapField<java.lang.String, java.lang.String>
      internalGetBigqueryImportKeys() {
    if (bigqueryImportKeys_ == null) {
      return com.google.protobuf.MapField.emptyMapField(
          BigqueryImportKeysDefaultEntryHolder.defaultEntry);
    }
    return bigqueryImportKeys_;
  }

  public int getBigqueryImportKeysCount() {
    return internalGetBigqueryImportKeys().getMap().size();
  }
  /**
   *
   *
   * <pre>
   * Required. Prediction keys that tell Data Labeling Service where to find the
   * data for evaluation in your BigQuery table. When the service samples
   * prediction input and output from your model version and saves it to
   * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
   * keys tell Data Labeling Service how to parse the JSON.
   * You can provide the following entries in this field:
   * * `data_json_key`: the data key for prediction input. You must provide
   *   either this key or `reference_json_key`.
   * * `reference_json_key`: the data reference key for prediction input. You
   *   must provide either this key or `data_json_key`.
   * * `label_json_key`: the label key for prediction output. Required.
   * * `label_score_json_key`: the score key for prediction output. Required.
   * * `bounding_box_json_key`: the bounding box key for prediction output.
   *   Required if your model version perform image object detection.
   * Learn [how to configure prediction
   * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
   * </pre>
   *
   * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
   */
  @java.lang.Override
  public boolean containsBigqueryImportKeys(java.lang.String key) {
    if (key == null) {
      throw new NullPointerException("map key");
    }
    return internalGetBigqueryImportKeys().getMap().containsKey(key);
  }
  /** Use {@link #getBigqueryImportKeysMap()} instead. */
  @java.lang.Override
  @java.lang.Deprecated
  public java.util.Map<java.lang.String, java.lang.String> getBigqueryImportKeys() {
    return getBigqueryImportKeysMap();
  }
  /**
   *
   *
   * <pre>
   * Required. Prediction keys that tell Data Labeling Service where to find the
   * data for evaluation in your BigQuery table. When the service samples
   * prediction input and output from your model version and saves it to
   * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
   * keys tell Data Labeling Service how to parse the JSON.
   * You can provide the following entries in this field:
   * * `data_json_key`: the data key for prediction input. You must provide
   *   either this key or `reference_json_key`.
   * * `reference_json_key`: the data reference key for prediction input. You
   *   must provide either this key or `data_json_key`.
   * * `label_json_key`: the label key for prediction output. Required.
   * * `label_score_json_key`: the score key for prediction output. Required.
   * * `bounding_box_json_key`: the bounding box key for prediction output.
   *   Required if your model version perform image object detection.
   * Learn [how to configure prediction
   * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
   * </pre>
   *
   * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
   */
  @java.lang.Override
  public java.util.Map<java.lang.String, java.lang.String> getBigqueryImportKeysMap() {
    return internalGetBigqueryImportKeys().getMap();
  }
  /**
   *
   *
   * <pre>
   * Required. Prediction keys that tell Data Labeling Service where to find the
   * data for evaluation in your BigQuery table. When the service samples
   * prediction input and output from your model version and saves it to
   * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
   * keys tell Data Labeling Service how to parse the JSON.
   * You can provide the following entries in this field:
   * * `data_json_key`: the data key for prediction input. You must provide
   *   either this key or `reference_json_key`.
   * * `reference_json_key`: the data reference key for prediction input. You
   *   must provide either this key or `data_json_key`.
   * * `label_json_key`: the label key for prediction output. Required.
   * * `label_score_json_key`: the score key for prediction output. Required.
   * * `bounding_box_json_key`: the bounding box key for prediction output.
   *   Required if your model version perform image object detection.
   * Learn [how to configure prediction
   * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
   * </pre>
   *
   * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
   */
  @java.lang.Override
  public /* nullable */ java.lang.String getBigqueryImportKeysOrDefault(
      java.lang.String key,
      /* nullable */
      java.lang.String defaultValue) {
    if (key == null) {
      throw new NullPointerException("map key");
    }
    java.util.Map<java.lang.String, java.lang.String> map =
        internalGetBigqueryImportKeys().getMap();
    return map.containsKey(key) ? map.get(key) : defaultValue;
  }
  /**
   *
   *
   * <pre>
   * Required. Prediction keys that tell Data Labeling Service where to find the
   * data for evaluation in your BigQuery table. When the service samples
   * prediction input and output from your model version and saves it to
   * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
   * keys tell Data Labeling Service how to parse the JSON.
   * You can provide the following entries in this field:
   * * `data_json_key`: the data key for prediction input. You must provide
   *   either this key or `reference_json_key`.
   * * `reference_json_key`: the data reference key for prediction input. You
   *   must provide either this key or `data_json_key`.
   * * `label_json_key`: the label key for prediction output. Required.
   * * `label_score_json_key`: the score key for prediction output. Required.
   * * `bounding_box_json_key`: the bounding box key for prediction output.
   *   Required if your model version perform image object detection.
   * Learn [how to configure prediction
   * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
   * </pre>
   *
   * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
   */
  @java.lang.Override
  public java.lang.String getBigqueryImportKeysOrThrow(java.lang.String key) {
    if (key == null) {
      throw new NullPointerException("map key");
    }
    java.util.Map<java.lang.String, java.lang.String> map =
        internalGetBigqueryImportKeys().getMap();
    if (!map.containsKey(key)) {
      throw new java.lang.IllegalArgumentException();
    }
    return map.get(key);
  }

  public static final int EXAMPLE_COUNT_FIELD_NUMBER = 10;
  private int exampleCount_ = 0;
  /**
   *
   *
   * <pre>
   * Required. The maximum number of predictions to sample and save to BigQuery
   * during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. This limit
   * overrides `example_sample_percentage`: even if the service has not sampled
   * enough predictions to fulfill `example_sample_perecentage` during an
   * interval, it stops sampling predictions when it meets this limit.
   * </pre>
   *
   * <code>int32 example_count = 10;</code>
   *
   * @return The exampleCount.
   */
  @java.lang.Override
  public int getExampleCount() {
    return exampleCount_;
  }

  public static final int EXAMPLE_SAMPLE_PERCENTAGE_FIELD_NUMBER = 11;
  private double exampleSamplePercentage_ = 0D;
  /**
   *
   *
   * <pre>
   * Required. Fraction of predictions to sample and save to BigQuery during
   * each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means
   * 10% of predictions served by your model version get saved to BigQuery.
   * </pre>
   *
   * <code>double example_sample_percentage = 11;</code>
   *
   * @return The exampleSamplePercentage.
   */
  @java.lang.Override
  public double getExampleSamplePercentage() {
    return exampleSamplePercentage_;
  }

  public static final int EVALUATION_JOB_ALERT_CONFIG_FIELD_NUMBER = 13;
  private com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluationJobAlertConfig_;
  /**
   *
   *
   * <pre>
   * Optional. Configuration details for evaluation job alerts. Specify this
   * field if you want to receive email alerts if the evaluation job finds that
   * your predictions have low mean average precision during a run.
   * </pre>
   *
   * <code>
   * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
   * </code>
   *
   * @return Whether the evaluationJobAlertConfig field is set.
   */
  @java.lang.Override
  public boolean hasEvaluationJobAlertConfig() {
    return evaluationJobAlertConfig_ != null;
  }
  /**
   *
   *
   * <pre>
   * Optional. Configuration details for evaluation job alerts. Specify this
   * field if you want to receive email alerts if the evaluation job finds that
   * your predictions have low mean average precision during a run.
   * </pre>
   *
   * <code>
   * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
   * </code>
   *
   * @return The evaluationJobAlertConfig.
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig
      getEvaluationJobAlertConfig() {
    return evaluationJobAlertConfig_ == null
        ? com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig.getDefaultInstance()
        : evaluationJobAlertConfig_;
  }
  /**
   *
   *
   * <pre>
   * Optional. Configuration details for evaluation job alerts. Specify this
   * field if you want to receive email alerts if the evaluation job finds that
   * your predictions have low mean average precision during a run.
   * </pre>
   *
   * <code>
   * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
   * </code>
   */
  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfigOrBuilder
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    return evaluationJobAlertConfig_ == null
        ? com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig.getDefaultInstance()
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  }

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    }
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    if (hasHumanAnnotationConfig() != other.hasHumanAnnotationConfig()) return false;
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      if (!getHumanAnnotationConfig().equals(other.getHumanAnnotationConfig())) return false;
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    if (hasEvaluationJobAlertConfig()) {
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        break;
      case 8:
        if (!getTextClassificationConfig().equals(other.getTextClassificationConfig()))
          return false;
        break;
      case 0:
      default:
    }
    if (!getUnknownFields().equals(other.getUnknownFields())) return false;
    return true;
  }

  @java.lang.Override
  public int hashCode() {
    if (memoizedHashCode != 0) {
      return memoizedHashCode;
    }
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      case 0:
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    memoizedHashCode = hash;
    return hash;
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  public static com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig parseFrom(
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  public static com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig parseFrom(
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      throws com.google.protobuf.InvalidProtocolBufferException {
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  public static com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig parseFrom(
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  public static com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig parseFrom(
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      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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  public static com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig parseFrom(
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  public static Builder newBuilder() {
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  public static Builder newBuilder(
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  /**
   *
   *
   * <pre>
   * Configures specific details of how a continuous evaluation job works. Provide
   * this configuration when you create an EvaluationJob.
   * </pre>
   *
   * Protobuf type {@code google.cloud.datalabeling.v1beta1.EvaluationJobConfig}
   */
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      // @@protoc_insertion_point(builder_implements:google.cloud.datalabeling.v1beta1.EvaluationJobConfig)
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    @java.lang.Override
    public Builder setField(
        com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) {
      return super.setField(field, value);
    }

    @java.lang.Override
    public Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field) {
      return super.clearField(field);
    }

    @java.lang.Override
    public Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) {
      return super.clearOneof(oneof);
    }

    @java.lang.Override
    public Builder setRepeatedField(
        com.google.protobuf.Descriptors.FieldDescriptor field, int index, java.lang.Object value) {
      return super.setRepeatedField(field, index, value);
    }

    @java.lang.Override
    public Builder addRepeatedField(
        com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) {
      return super.addRepeatedField(field, value);
    }

    @java.lang.Override
    public Builder mergeFrom(com.google.protobuf.Message other) {
      if (other instanceof com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig) {
        return mergeFrom((com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig) other);
      } else {
        super.mergeFrom(other);
        return this;
      }
    }

    public Builder mergeFrom(com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig other) {
      if (other == com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig.getDefaultInstance())
        return this;
      if (other.hasInputConfig()) {
        mergeInputConfig(other.getInputConfig());
      }
      if (other.hasEvaluationConfig()) {
        mergeEvaluationConfig(other.getEvaluationConfig());
      }
      if (other.hasHumanAnnotationConfig()) {
        mergeHumanAnnotationConfig(other.getHumanAnnotationConfig());
      }
      internalGetMutableBigqueryImportKeys().mergeFrom(other.internalGetBigqueryImportKeys());
      bitField0_ |= 0x00000040;
      if (other.getExampleCount() != 0) {
        setExampleCount(other.getExampleCount());
      }
      if (other.getExampleSamplePercentage() != 0D) {
        setExampleSamplePercentage(other.getExampleSamplePercentage());
      }
      if (other.hasEvaluationJobAlertConfig()) {
        mergeEvaluationJobAlertConfig(other.getEvaluationJobAlertConfig());
      }
      switch (other.getHumanAnnotationRequestConfigCase()) {
        case IMAGE_CLASSIFICATION_CONFIG:
          {
            mergeImageClassificationConfig(other.getImageClassificationConfig());
            break;
          }
        case BOUNDING_POLY_CONFIG:
          {
            mergeBoundingPolyConfig(other.getBoundingPolyConfig());
            break;
          }
        case TEXT_CLASSIFICATION_CONFIG:
          {
            mergeTextClassificationConfig(other.getTextClassificationConfig());
            break;
          }
        case HUMANANNOTATIONREQUESTCONFIG_NOT_SET:
          {
            break;
          }
      }
      this.mergeUnknownFields(other.getUnknownFields());
      onChanged();
      return this;
    }

    @java.lang.Override
    public final boolean isInitialized() {
      return true;
    }

    @java.lang.Override
    public Builder mergeFrom(
        com.google.protobuf.CodedInputStream input,
        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
        throws java.io.IOException {
      if (extensionRegistry == null) {
        throw new java.lang.NullPointerException();
      }
      try {
        boolean done = false;
        while (!done) {
          int tag = input.readTag();
          switch (tag) {
            case 0:
              done = true;
              break;
            case 10:
              {
                input.readMessage(getInputConfigFieldBuilder().getBuilder(), extensionRegistry);
                bitField0_ |= 0x00000008;
                break;
              } // case 10
            case 18:
              {
                input.readMessage(
                    getEvaluationConfigFieldBuilder().getBuilder(), extensionRegistry);
                bitField0_ |= 0x00000010;
                break;
              } // case 18
            case 26:
              {
                input.readMessage(
                    getHumanAnnotationConfigFieldBuilder().getBuilder(), extensionRegistry);
                bitField0_ |= 0x00000020;
                break;
              } // case 26
            case 34:
              {
                input.readMessage(
                    getImageClassificationConfigFieldBuilder().getBuilder(), extensionRegistry);
                humanAnnotationRequestConfigCase_ = 4;
                break;
              } // case 34
            case 42:
              {
                input.readMessage(
                    getBoundingPolyConfigFieldBuilder().getBuilder(), extensionRegistry);
                humanAnnotationRequestConfigCase_ = 5;
                break;
              } // case 42
            case 66:
              {
                input.readMessage(
                    getTextClassificationConfigFieldBuilder().getBuilder(), extensionRegistry);
                humanAnnotationRequestConfigCase_ = 8;
                break;
              } // case 66
            case 74:
              {
                com.google.protobuf.MapEntry<java.lang.String, java.lang.String>
                    bigqueryImportKeys__ =
                        input.readMessage(
                            BigqueryImportKeysDefaultEntryHolder.defaultEntry.getParserForType(),
                            extensionRegistry);
                internalGetMutableBigqueryImportKeys()
                    .getMutableMap()
                    .put(bigqueryImportKeys__.getKey(), bigqueryImportKeys__.getValue());
                bitField0_ |= 0x00000040;
                break;
              } // case 74
            case 80:
              {
                exampleCount_ = input.readInt32();
                bitField0_ |= 0x00000080;
                break;
              } // case 80
            case 89:
              {
                exampleSamplePercentage_ = input.readDouble();
                bitField0_ |= 0x00000100;
                break;
              } // case 89
            case 106:
              {
                input.readMessage(
                    getEvaluationJobAlertConfigFieldBuilder().getBuilder(), extensionRegistry);
                bitField0_ |= 0x00000200;
                break;
              } // case 106
            default:
              {
                if (!super.parseUnknownField(input, extensionRegistry, tag)) {
                  done = true; // was an endgroup tag
                }
                break;
              } // default:
          } // switch (tag)
        } // while (!done)
      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
        throw e.unwrapIOException();
      } finally {
        onChanged();
      } // finally
      return this;
    }

    private int humanAnnotationRequestConfigCase_ = 0;
    private java.lang.Object humanAnnotationRequestConfig_;

    public HumanAnnotationRequestConfigCase getHumanAnnotationRequestConfigCase() {
      return HumanAnnotationRequestConfigCase.forNumber(humanAnnotationRequestConfigCase_);
    }

    public Builder clearHumanAnnotationRequestConfig() {
      humanAnnotationRequestConfigCase_ = 0;
      humanAnnotationRequestConfig_ = null;
      onChanged();
      return this;
    }

    private int bitField0_;

    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig,
            com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.ImageClassificationConfigOrBuilder>
        imageClassificationConfigBuilder_;
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image classification or
     * general classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
     * </code>
     *
     * @return Whether the imageClassificationConfig field is set.
     */
    @java.lang.Override
    public boolean hasImageClassificationConfig() {
      return humanAnnotationRequestConfigCase_ == 4;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image classification or
     * general classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
     * </code>
     *
     * @return The imageClassificationConfig.
     */
    @java.lang.Override
    public com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig
        getImageClassificationConfig() {
      if (imageClassificationConfigBuilder_ == null) {
        if (humanAnnotationRequestConfigCase_ == 4) {
          return (com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig)
              humanAnnotationRequestConfig_;
        }
        return com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.getDefaultInstance();
      } else {
        if (humanAnnotationRequestConfigCase_ == 4) {
          return imageClassificationConfigBuilder_.getMessage();
        }
        return com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.getDefaultInstance();
      }
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image classification or
     * general classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
     * </code>
     */
    public Builder setImageClassificationConfig(
        com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig value) {
      if (imageClassificationConfigBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        humanAnnotationRequestConfig_ = value;
        onChanged();
      } else {
        imageClassificationConfigBuilder_.setMessage(value);
      }
      humanAnnotationRequestConfigCase_ = 4;
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image classification or
     * general classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
     * </code>
     */
    public Builder setImageClassificationConfig(
        com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.Builder builderForValue) {
      if (imageClassificationConfigBuilder_ == null) {
        humanAnnotationRequestConfig_ = builderForValue.build();
        onChanged();
      } else {
        imageClassificationConfigBuilder_.setMessage(builderForValue.build());
      }
      humanAnnotationRequestConfigCase_ = 4;
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image classification or
     * general classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
     * </code>
     */
    public Builder mergeImageClassificationConfig(
        com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig value) {
      if (imageClassificationConfigBuilder_ == null) {
        if (humanAnnotationRequestConfigCase_ == 4
            && humanAnnotationRequestConfig_
                != com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig
                    .getDefaultInstance()) {
          humanAnnotationRequestConfig_ =
              com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.newBuilder(
                      (com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig)
                          humanAnnotationRequestConfig_)
                  .mergeFrom(value)
                  .buildPartial();
        } else {
          humanAnnotationRequestConfig_ = value;
        }
        onChanged();
      } else {
        if (humanAnnotationRequestConfigCase_ == 4) {
          imageClassificationConfigBuilder_.mergeFrom(value);
        } else {
          imageClassificationConfigBuilder_.setMessage(value);
        }
      }
      humanAnnotationRequestConfigCase_ = 4;
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image classification or
     * general classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
     * </code>
     */
    public Builder clearImageClassificationConfig() {
      if (imageClassificationConfigBuilder_ == null) {
        if (humanAnnotationRequestConfigCase_ == 4) {
          humanAnnotationRequestConfigCase_ = 0;
          humanAnnotationRequestConfig_ = null;
          onChanged();
        }
      } else {
        if (humanAnnotationRequestConfigCase_ == 4) {
          humanAnnotationRequestConfigCase_ = 0;
          humanAnnotationRequestConfig_ = null;
        }
        imageClassificationConfigBuilder_.clear();
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image classification or
     * general classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
     * </code>
     */
    public com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.Builder
        getImageClassificationConfigBuilder() {
      return getImageClassificationConfigFieldBuilder().getBuilder();
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image classification or
     * general classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
     * </code>
     */
    @java.lang.Override
    public com.google.cloud.datalabeling.v1beta1.ImageClassificationConfigOrBuilder
        getImageClassificationConfigOrBuilder() {
      if ((humanAnnotationRequestConfigCase_ == 4) && (imageClassificationConfigBuilder_ != null)) {
        return imageClassificationConfigBuilder_.getMessageOrBuilder();
      } else {
        if (humanAnnotationRequestConfigCase_ == 4) {
          return (com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig)
              humanAnnotationRequestConfig_;
        }
        return com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.getDefaultInstance();
      }
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image classification or
     * general classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
     * </code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig,
            com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.ImageClassificationConfigOrBuilder>
        getImageClassificationConfigFieldBuilder() {
      if (imageClassificationConfigBuilder_ == null) {
        if (!(humanAnnotationRequestConfigCase_ == 4)) {
          humanAnnotationRequestConfig_ =
              com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.getDefaultInstance();
        }
        imageClassificationConfigBuilder_ =
            new com.google.protobuf.SingleFieldBuilderV3<
                com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig,
                com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig.Builder,
                com.google.cloud.datalabeling.v1beta1.ImageClassificationConfigOrBuilder>(
                (com.google.cloud.datalabeling.v1beta1.ImageClassificationConfig)
                    humanAnnotationRequestConfig_,
                getParentForChildren(),
                isClean());
        humanAnnotationRequestConfig_ = null;
      }
      humanAnnotationRequestConfigCase_ = 4;
      onChanged();
      return imageClassificationConfigBuilder_;
    }

    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig,
            com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.BoundingPolyConfigOrBuilder>
        boundingPolyConfigBuilder_;
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image object detection
     * (bounding box detection).
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
     *
     * @return Whether the boundingPolyConfig field is set.
     */
    @java.lang.Override
    public boolean hasBoundingPolyConfig() {
      return humanAnnotationRequestConfigCase_ == 5;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image object detection
     * (bounding box detection).
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
     *
     * @return The boundingPolyConfig.
     */
    @java.lang.Override
    public com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig getBoundingPolyConfig() {
      if (boundingPolyConfigBuilder_ == null) {
        if (humanAnnotationRequestConfigCase_ == 5) {
          return (com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig)
              humanAnnotationRequestConfig_;
        }
        return com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.getDefaultInstance();
      } else {
        if (humanAnnotationRequestConfigCase_ == 5) {
          return boundingPolyConfigBuilder_.getMessage();
        }
        return com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.getDefaultInstance();
      }
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image object detection
     * (bounding box detection).
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
     */
    public Builder setBoundingPolyConfig(
        com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig value) {
      if (boundingPolyConfigBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        humanAnnotationRequestConfig_ = value;
        onChanged();
      } else {
        boundingPolyConfigBuilder_.setMessage(value);
      }
      humanAnnotationRequestConfigCase_ = 5;
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image object detection
     * (bounding box detection).
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
     */
    public Builder setBoundingPolyConfig(
        com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.Builder builderForValue) {
      if (boundingPolyConfigBuilder_ == null) {
        humanAnnotationRequestConfig_ = builderForValue.build();
        onChanged();
      } else {
        boundingPolyConfigBuilder_.setMessage(builderForValue.build());
      }
      humanAnnotationRequestConfigCase_ = 5;
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image object detection
     * (bounding box detection).
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
     */
    public Builder mergeBoundingPolyConfig(
        com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig value) {
      if (boundingPolyConfigBuilder_ == null) {
        if (humanAnnotationRequestConfigCase_ == 5
            && humanAnnotationRequestConfig_
                != com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.getDefaultInstance()) {
          humanAnnotationRequestConfig_ =
              com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.newBuilder(
                      (com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig)
                          humanAnnotationRequestConfig_)
                  .mergeFrom(value)
                  .buildPartial();
        } else {
          humanAnnotationRequestConfig_ = value;
        }
        onChanged();
      } else {
        if (humanAnnotationRequestConfigCase_ == 5) {
          boundingPolyConfigBuilder_.mergeFrom(value);
        } else {
          boundingPolyConfigBuilder_.setMessage(value);
        }
      }
      humanAnnotationRequestConfigCase_ = 5;
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image object detection
     * (bounding box detection).
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
     */
    public Builder clearBoundingPolyConfig() {
      if (boundingPolyConfigBuilder_ == null) {
        if (humanAnnotationRequestConfigCase_ == 5) {
          humanAnnotationRequestConfigCase_ = 0;
          humanAnnotationRequestConfig_ = null;
          onChanged();
        }
      } else {
        if (humanAnnotationRequestConfigCase_ == 5) {
          humanAnnotationRequestConfigCase_ = 0;
          humanAnnotationRequestConfig_ = null;
        }
        boundingPolyConfigBuilder_.clear();
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image object detection
     * (bounding box detection).
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
     */
    public com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.Builder
        getBoundingPolyConfigBuilder() {
      return getBoundingPolyConfigFieldBuilder().getBuilder();
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image object detection
     * (bounding box detection).
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
     */
    @java.lang.Override
    public com.google.cloud.datalabeling.v1beta1.BoundingPolyConfigOrBuilder
        getBoundingPolyConfigOrBuilder() {
      if ((humanAnnotationRequestConfigCase_ == 5) && (boundingPolyConfigBuilder_ != null)) {
        return boundingPolyConfigBuilder_.getMessageOrBuilder();
      } else {
        if (humanAnnotationRequestConfigCase_ == 5) {
          return (com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig)
              humanAnnotationRequestConfig_;
        }
        return com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.getDefaultInstance();
      }
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs image object detection
     * (bounding box detection).
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;</code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig,
            com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.BoundingPolyConfigOrBuilder>
        getBoundingPolyConfigFieldBuilder() {
      if (boundingPolyConfigBuilder_ == null) {
        if (!(humanAnnotationRequestConfigCase_ == 5)) {
          humanAnnotationRequestConfig_ =
              com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.getDefaultInstance();
        }
        boundingPolyConfigBuilder_ =
            new com.google.protobuf.SingleFieldBuilderV3<
                com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig,
                com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig.Builder,
                com.google.cloud.datalabeling.v1beta1.BoundingPolyConfigOrBuilder>(
                (com.google.cloud.datalabeling.v1beta1.BoundingPolyConfig)
                    humanAnnotationRequestConfig_,
                getParentForChildren(),
                isClean());
        humanAnnotationRequestConfig_ = null;
      }
      humanAnnotationRequestConfigCase_ = 5;
      onChanged();
      return boundingPolyConfigBuilder_;
    }

    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.TextClassificationConfig,
            com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.TextClassificationConfigOrBuilder>
        textClassificationConfigBuilder_;
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs text classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
     * </code>
     *
     * @return Whether the textClassificationConfig field is set.
     */
    @java.lang.Override
    public boolean hasTextClassificationConfig() {
      return humanAnnotationRequestConfigCase_ == 8;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs text classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
     * </code>
     *
     * @return The textClassificationConfig.
     */
    @java.lang.Override
    public com.google.cloud.datalabeling.v1beta1.TextClassificationConfig
        getTextClassificationConfig() {
      if (textClassificationConfigBuilder_ == null) {
        if (humanAnnotationRequestConfigCase_ == 8) {
          return (com.google.cloud.datalabeling.v1beta1.TextClassificationConfig)
              humanAnnotationRequestConfig_;
        }
        return com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.getDefaultInstance();
      } else {
        if (humanAnnotationRequestConfigCase_ == 8) {
          return textClassificationConfigBuilder_.getMessage();
        }
        return com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.getDefaultInstance();
      }
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs text classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
     * </code>
     */
    public Builder setTextClassificationConfig(
        com.google.cloud.datalabeling.v1beta1.TextClassificationConfig value) {
      if (textClassificationConfigBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        humanAnnotationRequestConfig_ = value;
        onChanged();
      } else {
        textClassificationConfigBuilder_.setMessage(value);
      }
      humanAnnotationRequestConfigCase_ = 8;
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs text classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
     * </code>
     */
    public Builder setTextClassificationConfig(
        com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.Builder builderForValue) {
      if (textClassificationConfigBuilder_ == null) {
        humanAnnotationRequestConfig_ = builderForValue.build();
        onChanged();
      } else {
        textClassificationConfigBuilder_.setMessage(builderForValue.build());
      }
      humanAnnotationRequestConfigCase_ = 8;
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs text classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
     * </code>
     */
    public Builder mergeTextClassificationConfig(
        com.google.cloud.datalabeling.v1beta1.TextClassificationConfig value) {
      if (textClassificationConfigBuilder_ == null) {
        if (humanAnnotationRequestConfigCase_ == 8
            && humanAnnotationRequestConfig_
                != com.google.cloud.datalabeling.v1beta1.TextClassificationConfig
                    .getDefaultInstance()) {
          humanAnnotationRequestConfig_ =
              com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.newBuilder(
                      (com.google.cloud.datalabeling.v1beta1.TextClassificationConfig)
                          humanAnnotationRequestConfig_)
                  .mergeFrom(value)
                  .buildPartial();
        } else {
          humanAnnotationRequestConfig_ = value;
        }
        onChanged();
      } else {
        if (humanAnnotationRequestConfigCase_ == 8) {
          textClassificationConfigBuilder_.mergeFrom(value);
        } else {
          textClassificationConfigBuilder_.setMessage(value);
        }
      }
      humanAnnotationRequestConfigCase_ = 8;
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs text classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
     * </code>
     */
    public Builder clearTextClassificationConfig() {
      if (textClassificationConfigBuilder_ == null) {
        if (humanAnnotationRequestConfigCase_ == 8) {
          humanAnnotationRequestConfigCase_ = 0;
          humanAnnotationRequestConfig_ = null;
          onChanged();
        }
      } else {
        if (humanAnnotationRequestConfigCase_ == 8) {
          humanAnnotationRequestConfigCase_ = 0;
          humanAnnotationRequestConfig_ = null;
        }
        textClassificationConfigBuilder_.clear();
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs text classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
     * </code>
     */
    public com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.Builder
        getTextClassificationConfigBuilder() {
      return getTextClassificationConfigFieldBuilder().getBuilder();
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs text classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
     * </code>
     */
    @java.lang.Override
    public com.google.cloud.datalabeling.v1beta1.TextClassificationConfigOrBuilder
        getTextClassificationConfigOrBuilder() {
      if ((humanAnnotationRequestConfigCase_ == 8) && (textClassificationConfigBuilder_ != null)) {
        return textClassificationConfigBuilder_.getMessageOrBuilder();
      } else {
        if (humanAnnotationRequestConfigCase_ == 8) {
          return (com.google.cloud.datalabeling.v1beta1.TextClassificationConfig)
              humanAnnotationRequestConfig_;
        }
        return com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.getDefaultInstance();
      }
    }
    /**
     *
     *
     * <pre>
     * Specify this field if your model version performs text classification.
     * `annotationSpecSet` in this configuration must match
     * [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
     * `allowMultiLabel` in this configuration must match
     * `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
     * </code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.TextClassificationConfig,
            com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.TextClassificationConfigOrBuilder>
        getTextClassificationConfigFieldBuilder() {
      if (textClassificationConfigBuilder_ == null) {
        if (!(humanAnnotationRequestConfigCase_ == 8)) {
          humanAnnotationRequestConfig_ =
              com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.getDefaultInstance();
        }
        textClassificationConfigBuilder_ =
            new com.google.protobuf.SingleFieldBuilderV3<
                com.google.cloud.datalabeling.v1beta1.TextClassificationConfig,
                com.google.cloud.datalabeling.v1beta1.TextClassificationConfig.Builder,
                com.google.cloud.datalabeling.v1beta1.TextClassificationConfigOrBuilder>(
                (com.google.cloud.datalabeling.v1beta1.TextClassificationConfig)
                    humanAnnotationRequestConfig_,
                getParentForChildren(),
                isClean());
        humanAnnotationRequestConfig_ = null;
      }
      humanAnnotationRequestConfigCase_ = 8;
      onChanged();
      return textClassificationConfigBuilder_;
    }

    private com.google.cloud.datalabeling.v1beta1.InputConfig inputConfig_;
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.InputConfig,
            com.google.cloud.datalabeling.v1beta1.InputConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.InputConfigOrBuilder>
        inputConfigBuilder_;
    /**
     *
     *
     * <pre>
     * Rquired. Details for the sampled prediction input. Within this
     * configuration, there are requirements for several fields:
     * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
     * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
     *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
     *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
     * * If your machine learning model performs classification, you must specify
     *   `classificationMetadata.isMultiLabel`.
     * * You must specify `bigquerySource` (not `gcsSource`).
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
     *
     * @return Whether the inputConfig field is set.
     */
    public boolean hasInputConfig() {
      return ((bitField0_ & 0x00000008) != 0);
    }
    /**
     *
     *
     * <pre>
     * Rquired. Details for the sampled prediction input. Within this
     * configuration, there are requirements for several fields:
     * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
     * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
     *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
     *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
     * * If your machine learning model performs classification, you must specify
     *   `classificationMetadata.isMultiLabel`.
     * * You must specify `bigquerySource` (not `gcsSource`).
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
     *
     * @return The inputConfig.
     */
    public com.google.cloud.datalabeling.v1beta1.InputConfig getInputConfig() {
      if (inputConfigBuilder_ == null) {
        return inputConfig_ == null
            ? com.google.cloud.datalabeling.v1beta1.InputConfig.getDefaultInstance()
            : inputConfig_;
      } else {
        return inputConfigBuilder_.getMessage();
      }
    }
    /**
     *
     *
     * <pre>
     * Rquired. Details for the sampled prediction input. Within this
     * configuration, there are requirements for several fields:
     * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
     * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
     *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
     *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
     * * If your machine learning model performs classification, you must specify
     *   `classificationMetadata.isMultiLabel`.
     * * You must specify `bigquerySource` (not `gcsSource`).
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
     */
    public Builder setInputConfig(com.google.cloud.datalabeling.v1beta1.InputConfig value) {
      if (inputConfigBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        inputConfig_ = value;
      } else {
        inputConfigBuilder_.setMessage(value);
      }
      bitField0_ |= 0x00000008;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Rquired. Details for the sampled prediction input. Within this
     * configuration, there are requirements for several fields:
     * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
     * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
     *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
     *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
     * * If your machine learning model performs classification, you must specify
     *   `classificationMetadata.isMultiLabel`.
     * * You must specify `bigquerySource` (not `gcsSource`).
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
     */
    public Builder setInputConfig(
        com.google.cloud.datalabeling.v1beta1.InputConfig.Builder builderForValue) {
      if (inputConfigBuilder_ == null) {
        inputConfig_ = builderForValue.build();
      } else {
        inputConfigBuilder_.setMessage(builderForValue.build());
      }
      bitField0_ |= 0x00000008;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Rquired. Details for the sampled prediction input. Within this
     * configuration, there are requirements for several fields:
     * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
     * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
     *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
     *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
     * * If your machine learning model performs classification, you must specify
     *   `classificationMetadata.isMultiLabel`.
     * * You must specify `bigquerySource` (not `gcsSource`).
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
     */
    public Builder mergeInputConfig(com.google.cloud.datalabeling.v1beta1.InputConfig value) {
      if (inputConfigBuilder_ == null) {
        if (((bitField0_ & 0x00000008) != 0)
            && inputConfig_ != null
            && inputConfig_
                != com.google.cloud.datalabeling.v1beta1.InputConfig.getDefaultInstance()) {
          getInputConfigBuilder().mergeFrom(value);
        } else {
          inputConfig_ = value;
        }
      } else {
        inputConfigBuilder_.mergeFrom(value);
      }
      bitField0_ |= 0x00000008;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Rquired. Details for the sampled prediction input. Within this
     * configuration, there are requirements for several fields:
     * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
     * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
     *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
     *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
     * * If your machine learning model performs classification, you must specify
     *   `classificationMetadata.isMultiLabel`.
     * * You must specify `bigquerySource` (not `gcsSource`).
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
     */
    public Builder clearInputConfig() {
      bitField0_ = (bitField0_ & ~0x00000008);
      inputConfig_ = null;
      if (inputConfigBuilder_ != null) {
        inputConfigBuilder_.dispose();
        inputConfigBuilder_ = null;
      }
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Rquired. Details for the sampled prediction input. Within this
     * configuration, there are requirements for several fields:
     * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
     * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
     *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
     *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
     * * If your machine learning model performs classification, you must specify
     *   `classificationMetadata.isMultiLabel`.
     * * You must specify `bigquerySource` (not `gcsSource`).
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
     */
    public com.google.cloud.datalabeling.v1beta1.InputConfig.Builder getInputConfigBuilder() {
      bitField0_ |= 0x00000008;
      onChanged();
      return getInputConfigFieldBuilder().getBuilder();
    }
    /**
     *
     *
     * <pre>
     * Rquired. Details for the sampled prediction input. Within this
     * configuration, there are requirements for several fields:
     * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
     * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
     *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
     *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
     * * If your machine learning model performs classification, you must specify
     *   `classificationMetadata.isMultiLabel`.
     * * You must specify `bigquerySource` (not `gcsSource`).
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
     */
    public com.google.cloud.datalabeling.v1beta1.InputConfigOrBuilder getInputConfigOrBuilder() {
      if (inputConfigBuilder_ != null) {
        return inputConfigBuilder_.getMessageOrBuilder();
      } else {
        return inputConfig_ == null
            ? com.google.cloud.datalabeling.v1beta1.InputConfig.getDefaultInstance()
            : inputConfig_;
      }
    }
    /**
     *
     *
     * <pre>
     * Rquired. Details for the sampled prediction input. Within this
     * configuration, there are requirements for several fields:
     * * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`.
     * * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`,
     *   `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`,
     *   or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection).
     * * If your machine learning model performs classification, you must specify
     *   `classificationMetadata.isMultiLabel`.
     * * You must specify `bigquerySource` (not `gcsSource`).
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;</code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.InputConfig,
            com.google.cloud.datalabeling.v1beta1.InputConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.InputConfigOrBuilder>
        getInputConfigFieldBuilder() {
      if (inputConfigBuilder_ == null) {
        inputConfigBuilder_ =
            new com.google.protobuf.SingleFieldBuilderV3<
                com.google.cloud.datalabeling.v1beta1.InputConfig,
                com.google.cloud.datalabeling.v1beta1.InputConfig.Builder,
                com.google.cloud.datalabeling.v1beta1.InputConfigOrBuilder>(
                getInputConfig(), getParentForChildren(), isClean());
        inputConfig_ = null;
      }
      return inputConfigBuilder_;
    }

    private com.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluationConfig_;
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.EvaluationConfig,
            com.google.cloud.datalabeling.v1beta1.EvaluationConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.EvaluationConfigOrBuilder>
        evaluationConfigBuilder_;
    /**
     *
     *
     * <pre>
     * Required. Details for calculating evaluation metrics and creating
     * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
     * detection, you must specify the `boundingBoxEvaluationOptions` field within
     * this configuration. Otherwise, provide an empty object for this
     * configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
     *
     * @return Whether the evaluationConfig field is set.
     */
    public boolean hasEvaluationConfig() {
      return ((bitField0_ & 0x00000010) != 0);
    }
    /**
     *
     *
     * <pre>
     * Required. Details for calculating evaluation metrics and creating
     * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
     * detection, you must specify the `boundingBoxEvaluationOptions` field within
     * this configuration. Otherwise, provide an empty object for this
     * configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
     *
     * @return The evaluationConfig.
     */
    public com.google.cloud.datalabeling.v1beta1.EvaluationConfig getEvaluationConfig() {
      if (evaluationConfigBuilder_ == null) {
        return evaluationConfig_ == null
            ? com.google.cloud.datalabeling.v1beta1.EvaluationConfig.getDefaultInstance()
            : evaluationConfig_;
      } else {
        return evaluationConfigBuilder_.getMessage();
      }
    }
    /**
     *
     *
     * <pre>
     * Required. Details for calculating evaluation metrics and creating
     * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
     * detection, you must specify the `boundingBoxEvaluationOptions` field within
     * this configuration. Otherwise, provide an empty object for this
     * configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
     */
    public Builder setEvaluationConfig(
        com.google.cloud.datalabeling.v1beta1.EvaluationConfig value) {
      if (evaluationConfigBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        evaluationConfig_ = value;
      } else {
        evaluationConfigBuilder_.setMessage(value);
      }
      bitField0_ |= 0x00000010;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. Details for calculating evaluation metrics and creating
     * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
     * detection, you must specify the `boundingBoxEvaluationOptions` field within
     * this configuration. Otherwise, provide an empty object for this
     * configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
     */
    public Builder setEvaluationConfig(
        com.google.cloud.datalabeling.v1beta1.EvaluationConfig.Builder builderForValue) {
      if (evaluationConfigBuilder_ == null) {
        evaluationConfig_ = builderForValue.build();
      } else {
        evaluationConfigBuilder_.setMessage(builderForValue.build());
      }
      bitField0_ |= 0x00000010;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. Details for calculating evaluation metrics and creating
     * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
     * detection, you must specify the `boundingBoxEvaluationOptions` field within
     * this configuration. Otherwise, provide an empty object for this
     * configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
     */
    public Builder mergeEvaluationConfig(
        com.google.cloud.datalabeling.v1beta1.EvaluationConfig value) {
      if (evaluationConfigBuilder_ == null) {
        if (((bitField0_ & 0x00000010) != 0)
            && evaluationConfig_ != null
            && evaluationConfig_
                != com.google.cloud.datalabeling.v1beta1.EvaluationConfig.getDefaultInstance()) {
          getEvaluationConfigBuilder().mergeFrom(value);
        } else {
          evaluationConfig_ = value;
        }
      } else {
        evaluationConfigBuilder_.mergeFrom(value);
      }
      bitField0_ |= 0x00000010;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. Details for calculating evaluation metrics and creating
     * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
     * detection, you must specify the `boundingBoxEvaluationOptions` field within
     * this configuration. Otherwise, provide an empty object for this
     * configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
     */
    public Builder clearEvaluationConfig() {
      bitField0_ = (bitField0_ & ~0x00000010);
      evaluationConfig_ = null;
      if (evaluationConfigBuilder_ != null) {
        evaluationConfigBuilder_.dispose();
        evaluationConfigBuilder_ = null;
      }
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. Details for calculating evaluation metrics and creating
     * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
     * detection, you must specify the `boundingBoxEvaluationOptions` field within
     * this configuration. Otherwise, provide an empty object for this
     * configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
     */
    public com.google.cloud.datalabeling.v1beta1.EvaluationConfig.Builder
        getEvaluationConfigBuilder() {
      bitField0_ |= 0x00000010;
      onChanged();
      return getEvaluationConfigFieldBuilder().getBuilder();
    }
    /**
     *
     *
     * <pre>
     * Required. Details for calculating evaluation metrics and creating
     * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
     * detection, you must specify the `boundingBoxEvaluationOptions` field within
     * this configuration. Otherwise, provide an empty object for this
     * configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
     */
    public com.google.cloud.datalabeling.v1beta1.EvaluationConfigOrBuilder
        getEvaluationConfigOrBuilder() {
      if (evaluationConfigBuilder_ != null) {
        return evaluationConfigBuilder_.getMessageOrBuilder();
      } else {
        return evaluationConfig_ == null
            ? com.google.cloud.datalabeling.v1beta1.EvaluationConfig.getDefaultInstance()
            : evaluationConfig_;
      }
    }
    /**
     *
     *
     * <pre>
     * Required. Details for calculating evaluation metrics and creating
     * [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object
     * detection, you must specify the `boundingBoxEvaluationOptions` field within
     * this configuration. Otherwise, provide an empty object for this
     * configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;</code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.EvaluationConfig,
            com.google.cloud.datalabeling.v1beta1.EvaluationConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.EvaluationConfigOrBuilder>
        getEvaluationConfigFieldBuilder() {
      if (evaluationConfigBuilder_ == null) {
        evaluationConfigBuilder_ =
            new com.google.protobuf.SingleFieldBuilderV3<
                com.google.cloud.datalabeling.v1beta1.EvaluationConfig,
                com.google.cloud.datalabeling.v1beta1.EvaluationConfig.Builder,
                com.google.cloud.datalabeling.v1beta1.EvaluationConfigOrBuilder>(
                getEvaluationConfig(), getParentForChildren(), isClean());
        evaluationConfig_ = null;
      }
      return evaluationConfigBuilder_;
    }

    private com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig humanAnnotationConfig_;
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig,
            com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfigOrBuilder>
        humanAnnotationConfigBuilder_;
    /**
     *
     *
     * <pre>
     * Optional. Details for human annotation of your data. If you set
     * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
     * `true` for this evaluation job, then you must specify this field. If you
     * plan to provide your own ground truth labels, then omit this field.
     * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
     * specify this field. Provide the name of the instruction resource in the
     * `instruction` field within this configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
     * </code>
     *
     * @return Whether the humanAnnotationConfig field is set.
     */
    public boolean hasHumanAnnotationConfig() {
      return ((bitField0_ & 0x00000020) != 0);
    }
    /**
     *
     *
     * <pre>
     * Optional. Details for human annotation of your data. If you set
     * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
     * `true` for this evaluation job, then you must specify this field. If you
     * plan to provide your own ground truth labels, then omit this field.
     * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
     * specify this field. Provide the name of the instruction resource in the
     * `instruction` field within this configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
     * </code>
     *
     * @return The humanAnnotationConfig.
     */
    public com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig getHumanAnnotationConfig() {
      if (humanAnnotationConfigBuilder_ == null) {
        return humanAnnotationConfig_ == null
            ? com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig.getDefaultInstance()
            : humanAnnotationConfig_;
      } else {
        return humanAnnotationConfigBuilder_.getMessage();
      }
    }
    /**
     *
     *
     * <pre>
     * Optional. Details for human annotation of your data. If you set
     * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
     * `true` for this evaluation job, then you must specify this field. If you
     * plan to provide your own ground truth labels, then omit this field.
     * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
     * specify this field. Provide the name of the instruction resource in the
     * `instruction` field within this configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
     * </code>
     */
    public Builder setHumanAnnotationConfig(
        com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig value) {
      if (humanAnnotationConfigBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        humanAnnotationConfig_ = value;
      } else {
        humanAnnotationConfigBuilder_.setMessage(value);
      }
      bitField0_ |= 0x00000020;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Optional. Details for human annotation of your data. If you set
     * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
     * `true` for this evaluation job, then you must specify this field. If you
     * plan to provide your own ground truth labels, then omit this field.
     * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
     * specify this field. Provide the name of the instruction resource in the
     * `instruction` field within this configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
     * </code>
     */
    public Builder setHumanAnnotationConfig(
        com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig.Builder builderForValue) {
      if (humanAnnotationConfigBuilder_ == null) {
        humanAnnotationConfig_ = builderForValue.build();
      } else {
        humanAnnotationConfigBuilder_.setMessage(builderForValue.build());
      }
      bitField0_ |= 0x00000020;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Optional. Details for human annotation of your data. If you set
     * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
     * `true` for this evaluation job, then you must specify this field. If you
     * plan to provide your own ground truth labels, then omit this field.
     * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
     * specify this field. Provide the name of the instruction resource in the
     * `instruction` field within this configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
     * </code>
     */
    public Builder mergeHumanAnnotationConfig(
        com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig value) {
      if (humanAnnotationConfigBuilder_ == null) {
        if (((bitField0_ & 0x00000020) != 0)
            && humanAnnotationConfig_ != null
            && humanAnnotationConfig_
                != com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig
                    .getDefaultInstance()) {
          getHumanAnnotationConfigBuilder().mergeFrom(value);
        } else {
          humanAnnotationConfig_ = value;
        }
      } else {
        humanAnnotationConfigBuilder_.mergeFrom(value);
      }
      bitField0_ |= 0x00000020;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Optional. Details for human annotation of your data. If you set
     * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
     * `true` for this evaluation job, then you must specify this field. If you
     * plan to provide your own ground truth labels, then omit this field.
     * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
     * specify this field. Provide the name of the instruction resource in the
     * `instruction` field within this configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
     * </code>
     */
    public Builder clearHumanAnnotationConfig() {
      bitField0_ = (bitField0_ & ~0x00000020);
      humanAnnotationConfig_ = null;
      if (humanAnnotationConfigBuilder_ != null) {
        humanAnnotationConfigBuilder_.dispose();
        humanAnnotationConfigBuilder_ = null;
      }
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Optional. Details for human annotation of your data. If you set
     * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
     * `true` for this evaluation job, then you must specify this field. If you
     * plan to provide your own ground truth labels, then omit this field.
     * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
     * specify this field. Provide the name of the instruction resource in the
     * `instruction` field within this configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
     * </code>
     */
    public com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig.Builder
        getHumanAnnotationConfigBuilder() {
      bitField0_ |= 0x00000020;
      onChanged();
      return getHumanAnnotationConfigFieldBuilder().getBuilder();
    }
    /**
     *
     *
     * <pre>
     * Optional. Details for human annotation of your data. If you set
     * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
     * `true` for this evaluation job, then you must specify this field. If you
     * plan to provide your own ground truth labels, then omit this field.
     * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
     * specify this field. Provide the name of the instruction resource in the
     * `instruction` field within this configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
     * </code>
     */
    public com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfigOrBuilder
        getHumanAnnotationConfigOrBuilder() {
      if (humanAnnotationConfigBuilder_ != null) {
        return humanAnnotationConfigBuilder_.getMessageOrBuilder();
      } else {
        return humanAnnotationConfig_ == null
            ? com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig.getDefaultInstance()
            : humanAnnotationConfig_;
      }
    }
    /**
     *
     *
     * <pre>
     * Optional. Details for human annotation of your data. If you set
     * [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to
     * `true` for this evaluation job, then you must specify this field. If you
     * plan to provide your own ground truth labels, then omit this field.
     * Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
     * specify this field. Provide the name of the instruction resource in the
     * `instruction` field within this configuration.
     * </pre>
     *
     * <code>.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
     * </code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig,
            com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfigOrBuilder>
        getHumanAnnotationConfigFieldBuilder() {
      if (humanAnnotationConfigBuilder_ == null) {
        humanAnnotationConfigBuilder_ =
            new com.google.protobuf.SingleFieldBuilderV3<
                com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig,
                com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig.Builder,
                com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfigOrBuilder>(
                getHumanAnnotationConfig(), getParentForChildren(), isClean());
        humanAnnotationConfig_ = null;
      }
      return humanAnnotationConfigBuilder_;
    }

    private com.google.protobuf.MapField<java.lang.String, java.lang.String> bigqueryImportKeys_;

    private com.google.protobuf.MapField<java.lang.String, java.lang.String>
        internalGetBigqueryImportKeys() {
      if (bigqueryImportKeys_ == null) {
        return com.google.protobuf.MapField.emptyMapField(
            BigqueryImportKeysDefaultEntryHolder.defaultEntry);
      }
      return bigqueryImportKeys_;
    }

    private com.google.protobuf.MapField<java.lang.String, java.lang.String>
        internalGetMutableBigqueryImportKeys() {
      if (bigqueryImportKeys_ == null) {
        bigqueryImportKeys_ =
            com.google.protobuf.MapField.newMapField(
                BigqueryImportKeysDefaultEntryHolder.defaultEntry);
      }
      if (!bigqueryImportKeys_.isMutable()) {
        bigqueryImportKeys_ = bigqueryImportKeys_.copy();
      }
      bitField0_ |= 0x00000040;
      onChanged();
      return bigqueryImportKeys_;
    }

    public int getBigqueryImportKeysCount() {
      return internalGetBigqueryImportKeys().getMap().size();
    }
    /**
     *
     *
     * <pre>
     * Required. Prediction keys that tell Data Labeling Service where to find the
     * data for evaluation in your BigQuery table. When the service samples
     * prediction input and output from your model version and saves it to
     * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
     * keys tell Data Labeling Service how to parse the JSON.
     * You can provide the following entries in this field:
     * * `data_json_key`: the data key for prediction input. You must provide
     *   either this key or `reference_json_key`.
     * * `reference_json_key`: the data reference key for prediction input. You
     *   must provide either this key or `data_json_key`.
     * * `label_json_key`: the label key for prediction output. Required.
     * * `label_score_json_key`: the score key for prediction output. Required.
     * * `bounding_box_json_key`: the bounding box key for prediction output.
     *   Required if your model version perform image object detection.
     * Learn [how to configure prediction
     * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
     * </pre>
     *
     * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
     */
    @java.lang.Override
    public boolean containsBigqueryImportKeys(java.lang.String key) {
      if (key == null) {
        throw new NullPointerException("map key");
      }
      return internalGetBigqueryImportKeys().getMap().containsKey(key);
    }
    /** Use {@link #getBigqueryImportKeysMap()} instead. */
    @java.lang.Override
    @java.lang.Deprecated
    public java.util.Map<java.lang.String, java.lang.String> getBigqueryImportKeys() {
      return getBigqueryImportKeysMap();
    }
    /**
     *
     *
     * <pre>
     * Required. Prediction keys that tell Data Labeling Service where to find the
     * data for evaluation in your BigQuery table. When the service samples
     * prediction input and output from your model version and saves it to
     * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
     * keys tell Data Labeling Service how to parse the JSON.
     * You can provide the following entries in this field:
     * * `data_json_key`: the data key for prediction input. You must provide
     *   either this key or `reference_json_key`.
     * * `reference_json_key`: the data reference key for prediction input. You
     *   must provide either this key or `data_json_key`.
     * * `label_json_key`: the label key for prediction output. Required.
     * * `label_score_json_key`: the score key for prediction output. Required.
     * * `bounding_box_json_key`: the bounding box key for prediction output.
     *   Required if your model version perform image object detection.
     * Learn [how to configure prediction
     * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
     * </pre>
     *
     * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
     */
    @java.lang.Override
    public java.util.Map<java.lang.String, java.lang.String> getBigqueryImportKeysMap() {
      return internalGetBigqueryImportKeys().getMap();
    }
    /**
     *
     *
     * <pre>
     * Required. Prediction keys that tell Data Labeling Service where to find the
     * data for evaluation in your BigQuery table. When the service samples
     * prediction input and output from your model version and saves it to
     * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
     * keys tell Data Labeling Service how to parse the JSON.
     * You can provide the following entries in this field:
     * * `data_json_key`: the data key for prediction input. You must provide
     *   either this key or `reference_json_key`.
     * * `reference_json_key`: the data reference key for prediction input. You
     *   must provide either this key or `data_json_key`.
     * * `label_json_key`: the label key for prediction output. Required.
     * * `label_score_json_key`: the score key for prediction output. Required.
     * * `bounding_box_json_key`: the bounding box key for prediction output.
     *   Required if your model version perform image object detection.
     * Learn [how to configure prediction
     * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
     * </pre>
     *
     * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
     */
    @java.lang.Override
    public /* nullable */ java.lang.String getBigqueryImportKeysOrDefault(
        java.lang.String key,
        /* nullable */
        java.lang.String defaultValue) {
      if (key == null) {
        throw new NullPointerException("map key");
      }
      java.util.Map<java.lang.String, java.lang.String> map =
          internalGetBigqueryImportKeys().getMap();
      return map.containsKey(key) ? map.get(key) : defaultValue;
    }
    /**
     *
     *
     * <pre>
     * Required. Prediction keys that tell Data Labeling Service where to find the
     * data for evaluation in your BigQuery table. When the service samples
     * prediction input and output from your model version and saves it to
     * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
     * keys tell Data Labeling Service how to parse the JSON.
     * You can provide the following entries in this field:
     * * `data_json_key`: the data key for prediction input. You must provide
     *   either this key or `reference_json_key`.
     * * `reference_json_key`: the data reference key for prediction input. You
     *   must provide either this key or `data_json_key`.
     * * `label_json_key`: the label key for prediction output. Required.
     * * `label_score_json_key`: the score key for prediction output. Required.
     * * `bounding_box_json_key`: the bounding box key for prediction output.
     *   Required if your model version perform image object detection.
     * Learn [how to configure prediction
     * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
     * </pre>
     *
     * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
     */
    @java.lang.Override
    public java.lang.String getBigqueryImportKeysOrThrow(java.lang.String key) {
      if (key == null) {
        throw new NullPointerException("map key");
      }
      java.util.Map<java.lang.String, java.lang.String> map =
          internalGetBigqueryImportKeys().getMap();
      if (!map.containsKey(key)) {
        throw new java.lang.IllegalArgumentException();
      }
      return map.get(key);
    }

    public Builder clearBigqueryImportKeys() {
      bitField0_ = (bitField0_ & ~0x00000040);
      internalGetMutableBigqueryImportKeys().getMutableMap().clear();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. Prediction keys that tell Data Labeling Service where to find the
     * data for evaluation in your BigQuery table. When the service samples
     * prediction input and output from your model version and saves it to
     * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
     * keys tell Data Labeling Service how to parse the JSON.
     * You can provide the following entries in this field:
     * * `data_json_key`: the data key for prediction input. You must provide
     *   either this key or `reference_json_key`.
     * * `reference_json_key`: the data reference key for prediction input. You
     *   must provide either this key or `data_json_key`.
     * * `label_json_key`: the label key for prediction output. Required.
     * * `label_score_json_key`: the score key for prediction output. Required.
     * * `bounding_box_json_key`: the bounding box key for prediction output.
     *   Required if your model version perform image object detection.
     * Learn [how to configure prediction
     * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
     * </pre>
     *
     * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
     */
    public Builder removeBigqueryImportKeys(java.lang.String key) {
      if (key == null) {
        throw new NullPointerException("map key");
      }
      internalGetMutableBigqueryImportKeys().getMutableMap().remove(key);
      return this;
    }
    /** Use alternate mutation accessors instead. */
    @java.lang.Deprecated
    public java.util.Map<java.lang.String, java.lang.String> getMutableBigqueryImportKeys() {
      bitField0_ |= 0x00000040;
      return internalGetMutableBigqueryImportKeys().getMutableMap();
    }
    /**
     *
     *
     * <pre>
     * Required. Prediction keys that tell Data Labeling Service where to find the
     * data for evaluation in your BigQuery table. When the service samples
     * prediction input and output from your model version and saves it to
     * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
     * keys tell Data Labeling Service how to parse the JSON.
     * You can provide the following entries in this field:
     * * `data_json_key`: the data key for prediction input. You must provide
     *   either this key or `reference_json_key`.
     * * `reference_json_key`: the data reference key for prediction input. You
     *   must provide either this key or `data_json_key`.
     * * `label_json_key`: the label key for prediction output. Required.
     * * `label_score_json_key`: the score key for prediction output. Required.
     * * `bounding_box_json_key`: the bounding box key for prediction output.
     *   Required if your model version perform image object detection.
     * Learn [how to configure prediction
     * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
     * </pre>
     *
     * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
     */
    public Builder putBigqueryImportKeys(java.lang.String key, java.lang.String value) {
      if (key == null) {
        throw new NullPointerException("map key");
      }
      if (value == null) {
        throw new NullPointerException("map value");
      }
      internalGetMutableBigqueryImportKeys().getMutableMap().put(key, value);
      bitField0_ |= 0x00000040;
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. Prediction keys that tell Data Labeling Service where to find the
     * data for evaluation in your BigQuery table. When the service samples
     * prediction input and output from your model version and saves it to
     * BigQuery, the data gets stored as JSON strings in the BigQuery table. These
     * keys tell Data Labeling Service how to parse the JSON.
     * You can provide the following entries in this field:
     * * `data_json_key`: the data key for prediction input. You must provide
     *   either this key or `reference_json_key`.
     * * `reference_json_key`: the data reference key for prediction input. You
     *   must provide either this key or `data_json_key`.
     * * `label_json_key`: the label key for prediction output. Required.
     * * `label_score_json_key`: the score key for prediction output. Required.
     * * `bounding_box_json_key`: the bounding box key for prediction output.
     *   Required if your model version perform image object detection.
     * Learn [how to configure prediction
     * keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
     * </pre>
     *
     * <code>map&lt;string, string&gt; bigquery_import_keys = 9;</code>
     */
    public Builder putAllBigqueryImportKeys(
        java.util.Map<java.lang.String, java.lang.String> values) {
      internalGetMutableBigqueryImportKeys().getMutableMap().putAll(values);
      bitField0_ |= 0x00000040;
      return this;
    }

    private int exampleCount_;
    /**
     *
     *
     * <pre>
     * Required. The maximum number of predictions to sample and save to BigQuery
     * during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. This limit
     * overrides `example_sample_percentage`: even if the service has not sampled
     * enough predictions to fulfill `example_sample_perecentage` during an
     * interval, it stops sampling predictions when it meets this limit.
     * </pre>
     *
     * <code>int32 example_count = 10;</code>
     *
     * @return The exampleCount.
     */
    @java.lang.Override
    public int getExampleCount() {
      return exampleCount_;
    }
    /**
     *
     *
     * <pre>
     * Required. The maximum number of predictions to sample and save to BigQuery
     * during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. This limit
     * overrides `example_sample_percentage`: even if the service has not sampled
     * enough predictions to fulfill `example_sample_perecentage` during an
     * interval, it stops sampling predictions when it meets this limit.
     * </pre>
     *
     * <code>int32 example_count = 10;</code>
     *
     * @param value The exampleCount to set.
     * @return This builder for chaining.
     */
    public Builder setExampleCount(int value) {

      exampleCount_ = value;
      bitField0_ |= 0x00000080;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The maximum number of predictions to sample and save to BigQuery
     * during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. This limit
     * overrides `example_sample_percentage`: even if the service has not sampled
     * enough predictions to fulfill `example_sample_perecentage` during an
     * interval, it stops sampling predictions when it meets this limit.
     * </pre>
     *
     * <code>int32 example_count = 10;</code>
     *
     * @return This builder for chaining.
     */
    public Builder clearExampleCount() {
      bitField0_ = (bitField0_ & ~0x00000080);
      exampleCount_ = 0;
      onChanged();
      return this;
    }

    private double exampleSamplePercentage_;
    /**
     *
     *
     * <pre>
     * Required. Fraction of predictions to sample and save to BigQuery during
     * each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means
     * 10% of predictions served by your model version get saved to BigQuery.
     * </pre>
     *
     * <code>double example_sample_percentage = 11;</code>
     *
     * @return The exampleSamplePercentage.
     */
    @java.lang.Override
    public double getExampleSamplePercentage() {
      return exampleSamplePercentage_;
    }
    /**
     *
     *
     * <pre>
     * Required. Fraction of predictions to sample and save to BigQuery during
     * each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means
     * 10% of predictions served by your model version get saved to BigQuery.
     * </pre>
     *
     * <code>double example_sample_percentage = 11;</code>
     *
     * @param value The exampleSamplePercentage to set.
     * @return This builder for chaining.
     */
    public Builder setExampleSamplePercentage(double value) {

      exampleSamplePercentage_ = value;
      bitField0_ |= 0x00000100;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. Fraction of predictions to sample and save to BigQuery during
     * each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means
     * 10% of predictions served by your model version get saved to BigQuery.
     * </pre>
     *
     * <code>double example_sample_percentage = 11;</code>
     *
     * @return This builder for chaining.
     */
    public Builder clearExampleSamplePercentage() {
      bitField0_ = (bitField0_ & ~0x00000100);
      exampleSamplePercentage_ = 0D;
      onChanged();
      return this;
    }

    private com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig
        evaluationJobAlertConfig_;
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig,
            com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfigOrBuilder>
        evaluationJobAlertConfigBuilder_;
    /**
     *
     *
     * <pre>
     * Optional. Configuration details for evaluation job alerts. Specify this
     * field if you want to receive email alerts if the evaluation job finds that
     * your predictions have low mean average precision during a run.
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
     * </code>
     *
     * @return Whether the evaluationJobAlertConfig field is set.
     */
    public boolean hasEvaluationJobAlertConfig() {
      return ((bitField0_ & 0x00000200) != 0);
    }
    /**
     *
     *
     * <pre>
     * Optional. Configuration details for evaluation job alerts. Specify this
     * field if you want to receive email alerts if the evaluation job finds that
     * your predictions have low mean average precision during a run.
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
     * </code>
     *
     * @return The evaluationJobAlertConfig.
     */
    public com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig
        getEvaluationJobAlertConfig() {
      if (evaluationJobAlertConfigBuilder_ == null) {
        return evaluationJobAlertConfig_ == null
            ? com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig.getDefaultInstance()
            : evaluationJobAlertConfig_;
      } else {
        return evaluationJobAlertConfigBuilder_.getMessage();
      }
    }
    /**
     *
     *
     * <pre>
     * Optional. Configuration details for evaluation job alerts. Specify this
     * field if you want to receive email alerts if the evaluation job finds that
     * your predictions have low mean average precision during a run.
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
     * </code>
     */
    public Builder setEvaluationJobAlertConfig(
        com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig value) {
      if (evaluationJobAlertConfigBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        evaluationJobAlertConfig_ = value;
      } else {
        evaluationJobAlertConfigBuilder_.setMessage(value);
      }
      bitField0_ |= 0x00000200;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Optional. Configuration details for evaluation job alerts. Specify this
     * field if you want to receive email alerts if the evaluation job finds that
     * your predictions have low mean average precision during a run.
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
     * </code>
     */
    public Builder setEvaluationJobAlertConfig(
        com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig.Builder builderForValue) {
      if (evaluationJobAlertConfigBuilder_ == null) {
        evaluationJobAlertConfig_ = builderForValue.build();
      } else {
        evaluationJobAlertConfigBuilder_.setMessage(builderForValue.build());
      }
      bitField0_ |= 0x00000200;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Optional. Configuration details for evaluation job alerts. Specify this
     * field if you want to receive email alerts if the evaluation job finds that
     * your predictions have low mean average precision during a run.
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
     * </code>
     */
    public Builder mergeEvaluationJobAlertConfig(
        com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig value) {
      if (evaluationJobAlertConfigBuilder_ == null) {
        if (((bitField0_ & 0x00000200) != 0)
            && evaluationJobAlertConfig_ != null
            && evaluationJobAlertConfig_
                != com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig
                    .getDefaultInstance()) {
          getEvaluationJobAlertConfigBuilder().mergeFrom(value);
        } else {
          evaluationJobAlertConfig_ = value;
        }
      } else {
        evaluationJobAlertConfigBuilder_.mergeFrom(value);
      }
      bitField0_ |= 0x00000200;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Optional. Configuration details for evaluation job alerts. Specify this
     * field if you want to receive email alerts if the evaluation job finds that
     * your predictions have low mean average precision during a run.
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
     * </code>
     */
    public Builder clearEvaluationJobAlertConfig() {
      bitField0_ = (bitField0_ & ~0x00000200);
      evaluationJobAlertConfig_ = null;
      if (evaluationJobAlertConfigBuilder_ != null) {
        evaluationJobAlertConfigBuilder_.dispose();
        evaluationJobAlertConfigBuilder_ = null;
      }
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Optional. Configuration details for evaluation job alerts. Specify this
     * field if you want to receive email alerts if the evaluation job finds that
     * your predictions have low mean average precision during a run.
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
     * </code>
     */
    public com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig.Builder
        getEvaluationJobAlertConfigBuilder() {
      bitField0_ |= 0x00000200;
      onChanged();
      return getEvaluationJobAlertConfigFieldBuilder().getBuilder();
    }
    /**
     *
     *
     * <pre>
     * Optional. Configuration details for evaluation job alerts. Specify this
     * field if you want to receive email alerts if the evaluation job finds that
     * your predictions have low mean average precision during a run.
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
     * </code>
     */
    public com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfigOrBuilder
        getEvaluationJobAlertConfigOrBuilder() {
      if (evaluationJobAlertConfigBuilder_ != null) {
        return evaluationJobAlertConfigBuilder_.getMessageOrBuilder();
      } else {
        return evaluationJobAlertConfig_ == null
            ? com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig.getDefaultInstance()
            : evaluationJobAlertConfig_;
      }
    }
    /**
     *
     *
     * <pre>
     * Optional. Configuration details for evaluation job alerts. Specify this
     * field if you want to receive email alerts if the evaluation job finds that
     * your predictions have low mean average precision during a run.
     * </pre>
     *
     * <code>
     * .google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
     * </code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig,
            com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig.Builder,
            com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfigOrBuilder>
        getEvaluationJobAlertConfigFieldBuilder() {
      if (evaluationJobAlertConfigBuilder_ == null) {
        evaluationJobAlertConfigBuilder_ =
            new com.google.protobuf.SingleFieldBuilderV3<
                com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig,
                com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig.Builder,
                com.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfigOrBuilder>(
                getEvaluationJobAlertConfig(), getParentForChildren(), isClean());
        evaluationJobAlertConfig_ = null;
      }
      return evaluationJobAlertConfigBuilder_;
    }

    @java.lang.Override
    public final Builder setUnknownFields(final com.google.protobuf.UnknownFieldSet unknownFields) {
      return super.setUnknownFields(unknownFields);
    }

    @java.lang.Override
    public final Builder mergeUnknownFields(
        final com.google.protobuf.UnknownFieldSet unknownFields) {
      return super.mergeUnknownFields(unknownFields);
    }

    // @@protoc_insertion_point(builder_scope:google.cloud.datalabeling.v1beta1.EvaluationJobConfig)
  }

  // @@protoc_insertion_point(class_scope:google.cloud.datalabeling.v1beta1.EvaluationJobConfig)
  private static final com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig DEFAULT_INSTANCE;

  static {
    DEFAULT_INSTANCE = new com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig();
  }

  public static com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig getDefaultInstance() {
    return DEFAULT_INSTANCE;
  }

  private static final com.google.protobuf.Parser<EvaluationJobConfig> PARSER =
      new com.google.protobuf.AbstractParser<EvaluationJobConfig>() {
        @java.lang.Override
        public EvaluationJobConfig parsePartialFrom(
            com.google.protobuf.CodedInputStream input,
            com.google.protobuf.ExtensionRegistryLite extensionRegistry)
            throws com.google.protobuf.InvalidProtocolBufferException {
          Builder builder = newBuilder();
          try {
            builder.mergeFrom(input, extensionRegistry);
          } catch (com.google.protobuf.InvalidProtocolBufferException e) {
            throw e.setUnfinishedMessage(builder.buildPartial());
          } catch (com.google.protobuf.UninitializedMessageException e) {
            throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
          } catch (java.io.IOException e) {
            throw new com.google.protobuf.InvalidProtocolBufferException(e)
                .setUnfinishedMessage(builder.buildPartial());
          }
          return builder.buildPartial();
        }
      };

  public static com.google.protobuf.Parser<EvaluationJobConfig> parser() {
    return PARSER;
  }

  @java.lang.Override
  public com.google.protobuf.Parser<EvaluationJobConfig> getParserForType() {
    return PARSER;
  }

  @java.lang.Override
  public com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig getDefaultInstanceForType() {
    return DEFAULT_INSTANCE;
  }
}