/*
 * 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/automl/v1beta1/text_extraction.proto

package com.google.cloud.automl.v1beta1;

/**
 *
 *
 * <pre>
 * Model evaluation metrics for text extraction problems.
 * </pre>
 *
 * Protobuf type {@code google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics}
 */
public final class TextExtractionEvaluationMetrics extends com.google.protobuf.GeneratedMessageV3
    implements
    // @@protoc_insertion_point(message_implements:google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics)
    TextExtractionEvaluationMetricsOrBuilder {
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  // Use TextExtractionEvaluationMetrics.newBuilder() to construct.
  private TextExtractionEvaluationMetrics(
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  }

  private TextExtractionEvaluationMetrics() {
    confidenceMetricsEntries_ = java.util.Collections.emptyList();
  }

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  public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
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        .internal_static_google_cloud_automl_v1beta1_TextExtractionEvaluationMetrics_descriptor;
  }

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  public interface ConfidenceMetricsEntryOrBuilder
      extends
      // @@protoc_insertion_point(interface_extends:google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry)
      com.google.protobuf.MessageOrBuilder {

    /**
     *
     *
     * <pre>
     * Output only. The confidence threshold value used to compute the metrics.
     * Only annotations with score of at least this threshold are considered to
     * be ones the model would return.
     * </pre>
     *
     * <code>float confidence_threshold = 1;</code>
     *
     * @return The confidenceThreshold.
     */
    float getConfidenceThreshold();

    /**
     *
     *
     * <pre>
     * Output only. Recall under the given confidence threshold.
     * </pre>
     *
     * <code>float recall = 3;</code>
     *
     * @return The recall.
     */
    float getRecall();

    /**
     *
     *
     * <pre>
     * Output only. Precision under the given confidence threshold.
     * </pre>
     *
     * <code>float precision = 4;</code>
     *
     * @return The precision.
     */
    float getPrecision();

    /**
     *
     *
     * <pre>
     * Output only. The harmonic mean of recall and precision.
     * </pre>
     *
     * <code>float f1_score = 5;</code>
     *
     * @return The f1Score.
     */
    float getF1Score();
  }
  /**
   *
   *
   * <pre>
   * Metrics for a single confidence threshold.
   * </pre>
   *
   * Protobuf type {@code
   * google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry}
   */
  public static final class ConfidenceMetricsEntry extends com.google.protobuf.GeneratedMessageV3
      implements
      // @@protoc_insertion_point(message_implements:google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry)
      ConfidenceMetricsEntryOrBuilder {
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    private float confidenceThreshold_ = 0F;
    /**
     *
     *
     * <pre>
     * Output only. The confidence threshold value used to compute the metrics.
     * Only annotations with score of at least this threshold are considered to
     * be ones the model would return.
     * </pre>
     *
     * <code>float confidence_threshold = 1;</code>
     *
     * @return The confidenceThreshold.
     */
    @java.lang.Override
    public float getConfidenceThreshold() {
      return confidenceThreshold_;
    }

    public static final int RECALL_FIELD_NUMBER = 3;
    private float recall_ = 0F;
    /**
     *
     *
     * <pre>
     * Output only. Recall under the given confidence threshold.
     * </pre>
     *
     * <code>float recall = 3;</code>
     *
     * @return The recall.
     */
    @java.lang.Override
    public float getRecall() {
      return recall_;
    }

    public static final int PRECISION_FIELD_NUMBER = 4;
    private float precision_ = 0F;
    /**
     *
     *
     * <pre>
     * Output only. Precision under the given confidence threshold.
     * </pre>
     *
     * <code>float precision = 4;</code>
     *
     * @return The precision.
     */
    @java.lang.Override
    public float getPrecision() {
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    }

    public static final int F1_SCORE_FIELD_NUMBER = 5;
    private float f1Score_ = 0F;
    /**
     *
     *
     * <pre>
     * Output only. The harmonic mean of recall and precision.
     * </pre>
     *
     * <code>float f1_score = 5;</code>
     *
     * @return The f1Score.
     */
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    public static com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
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    public static com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
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    public static com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
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    public static com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
            .ConfidenceMetricsEntry
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            com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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    /**
     *
     *
     * <pre>
     * Metrics for a single confidence threshold.
     * </pre>
     *
     * Protobuf type {@code
     * google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry}
     */
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        extends com.google.protobuf.GeneratedMessageV3.Builder<Builder>
        implements
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        com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
            .ConfidenceMetricsEntryOrBuilder {
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            .internal_static_google_cloud_automl_v1beta1_TextExtractionEvaluationMetrics_ConfidenceMetricsEntry_descriptor;
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        confidenceThreshold_ = 0F;
        recall_ = 0F;
        precision_ = 0F;
        f1Score_ = 0F;
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      @java.lang.Override
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      private float confidenceThreshold_;
      /**
       *
       *
       * <pre>
       * Output only. The confidence threshold value used to compute the metrics.
       * Only annotations with score of at least this threshold are considered to
       * be ones the model would return.
       * </pre>
       *
       * <code>float confidence_threshold = 1;</code>
       *
       * @return The confidenceThreshold.
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      /**
       *
       *
       * <pre>
       * Output only. The confidence threshold value used to compute the metrics.
       * Only annotations with score of at least this threshold are considered to
       * be ones the model would return.
       * </pre>
       *
       * <code>float confidence_threshold = 1;</code>
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       * @return This builder for chaining.
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      /**
       *
       *
       * <pre>
       * Output only. The confidence threshold value used to compute the metrics.
       * Only annotations with score of at least this threshold are considered to
       * be ones the model would return.
       * </pre>
       *
       * <code>float confidence_threshold = 1;</code>
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       *
       *
       * <pre>
       * Output only. Recall under the given confidence threshold.
       * </pre>
       *
       * <code>float recall = 3;</code>
       *
       * @return The recall.
       */
      @java.lang.Override
      public float getRecall() {
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       *
       *
       * <pre>
       * Output only. Recall under the given confidence threshold.
       * </pre>
       *
       * <code>float recall = 3;</code>
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       * @return This builder for chaining.
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        recall_ = value;
        bitField0_ |= 0x00000002;
        onChanged();
        return this;
      }
      /**
       *
       *
       * <pre>
       * Output only. Recall under the given confidence threshold.
       * </pre>
       *
       * <code>float recall = 3;</code>
       *
       * @return This builder for chaining.
       */
      public Builder clearRecall() {
        bitField0_ = (bitField0_ & ~0x00000002);
        recall_ = 0F;
        onChanged();
        return this;
      }

      private float precision_;
      /**
       *
       *
       * <pre>
       * Output only. Precision under the given confidence threshold.
       * </pre>
       *
       * <code>float precision = 4;</code>
       *
       * @return The precision.
       */
      @java.lang.Override
      public float getPrecision() {
        return precision_;
      }
      /**
       *
       *
       * <pre>
       * Output only. Precision under the given confidence threshold.
       * </pre>
       *
       * <code>float precision = 4;</code>
       *
       * @param value The precision to set.
       * @return This builder for chaining.
       */
      public Builder setPrecision(float value) {

        precision_ = value;
        bitField0_ |= 0x00000004;
        onChanged();
        return this;
      }
      /**
       *
       *
       * <pre>
       * Output only. Precision under the given confidence threshold.
       * </pre>
       *
       * <code>float precision = 4;</code>
       *
       * @return This builder for chaining.
       */
      public Builder clearPrecision() {
        bitField0_ = (bitField0_ & ~0x00000004);
        precision_ = 0F;
        onChanged();
        return this;
      }

      private float f1Score_;
      /**
       *
       *
       * <pre>
       * Output only. The harmonic mean of recall and precision.
       * </pre>
       *
       * <code>float f1_score = 5;</code>
       *
       * @return The f1Score.
       */
      @java.lang.Override
      public float getF1Score() {
        return f1Score_;
      }
      /**
       *
       *
       * <pre>
       * Output only. The harmonic mean of recall and precision.
       * </pre>
       *
       * <code>float f1_score = 5;</code>
       *
       * @param value The f1Score to set.
       * @return This builder for chaining.
       */
      public Builder setF1Score(float value) {

        f1Score_ = value;
        bitField0_ |= 0x00000008;
        onChanged();
        return this;
      }
      /**
       *
       *
       * <pre>
       * Output only. The harmonic mean of recall and precision.
       * </pre>
       *
       * <code>float f1_score = 5;</code>
       *
       * @return This builder for chaining.
       */
      public Builder clearF1Score() {
        bitField0_ = (bitField0_ & ~0x00000008);
        f1Score_ = 0F;
        onChanged();
        return this;
      }

      @java.lang.Override
      public final Builder setUnknownFields(
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      }

      @java.lang.Override
      public final Builder mergeUnknownFields(
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        return super.mergeUnknownFields(unknownFields);
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      // @@protoc_insertion_point(builder_scope:google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry)
    }

    // @@protoc_insertion_point(class_scope:google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry)
    private static final com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
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          new com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
              .ConfidenceMetricsEntry();
    }

    public static com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
            .ConfidenceMetricsEntry
        getDefaultInstance() {
      return DEFAULT_INSTANCE;
    }

    private static final com.google.protobuf.Parser<ConfidenceMetricsEntry> PARSER =
        new com.google.protobuf.AbstractParser<ConfidenceMetricsEntry>() {
          @java.lang.Override
          public ConfidenceMetricsEntry 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) {
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                  .setUnfinishedMessage(builder.buildPartial());
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            return builder.buildPartial();
          }
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    @java.lang.Override
    public com.google.protobuf.Parser<ConfidenceMetricsEntry> getParserForType() {
      return PARSER;
    }

    @java.lang.Override
    public com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
        getDefaultInstanceForType() {
      return DEFAULT_INSTANCE;
    }
  }

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  private float auPrc_ = 0F;
  /**
   *
   *
   * <pre>
   * Output only. The Area under precision recall curve metric.
   * </pre>
   *
   * <code>float au_prc = 1;</code>
   *
   * @return The auPrc.
   */
  @java.lang.Override
  public float getAuPrc() {
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  }

  public static final int CONFIDENCE_METRICS_ENTRIES_FIELD_NUMBER = 2;

  @SuppressWarnings("serial")
  private java.util.List<
          com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry>
      confidenceMetricsEntries_;
  /**
   *
   *
   * <pre>
   * Output only. Metrics that have confidence thresholds.
   * Precision-recall curve can be derived from it.
   * </pre>
   *
   * <code>
   * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
   * </code>
   */
  @java.lang.Override
  public java.util.List<
          com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry>
      getConfidenceMetricsEntriesList() {
    return confidenceMetricsEntries_;
  }
  /**
   *
   *
   * <pre>
   * Output only. Metrics that have confidence thresholds.
   * Precision-recall curve can be derived from it.
   * </pre>
   *
   * <code>
   * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
   * </code>
   */
  @java.lang.Override
  public java.util.List<
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              com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
                  .ConfidenceMetricsEntryOrBuilder>
      getConfidenceMetricsEntriesOrBuilderList() {
    return confidenceMetricsEntries_;
  }
  /**
   *
   *
   * <pre>
   * Output only. Metrics that have confidence thresholds.
   * Precision-recall curve can be derived from it.
   * </pre>
   *
   * <code>
   * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
   * </code>
   */
  @java.lang.Override
  public int getConfidenceMetricsEntriesCount() {
    return confidenceMetricsEntries_.size();
  }
  /**
   *
   *
   * <pre>
   * Output only. Metrics that have confidence thresholds.
   * Precision-recall curve can be derived from it.
   * </pre>
   *
   * <code>
   * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
   * </code>
   */
  @java.lang.Override
  public com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
      getConfidenceMetricsEntries(int index) {
    return confidenceMetricsEntries_.get(index);
  }
  /**
   *
   *
   * <pre>
   * Output only. Metrics that have confidence thresholds.
   * Precision-recall curve can be derived from it.
   * </pre>
   *
   * <code>
   * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
   * </code>
   */
  @java.lang.Override
  public com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
          .ConfidenceMetricsEntryOrBuilder
      getConfidenceMetricsEntriesOrBuilder(int index) {
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  }

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    return size;
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  @java.lang.Override
  public boolean equals(final java.lang.Object obj) {
    if (obj == this) {
      return true;
    }
    if (!(obj instanceof com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics)) {
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    hash = (37 * hash) + AU_PRC_FIELD_NUMBER;
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    return PARSER.parseFrom(data, extensionRegistry);
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  public static com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics parseFrom(
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      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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  public static com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics parseFrom(
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  public static com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics parseFrom(
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  public static com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics parseFrom(
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      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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    return com.google.protobuf.GeneratedMessageV3.parseWithIOException(
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  @java.lang.Override
  public Builder newBuilderForType() {
    return newBuilder();
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  public static Builder newBuilder() {
    return DEFAULT_INSTANCE.toBuilder();
  }

  public static Builder newBuilder(
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  @java.lang.Override
  public Builder toBuilder() {
    return this == DEFAULT_INSTANCE ? new Builder() : new Builder().mergeFrom(this);
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  @java.lang.Override
  protected Builder newBuilderForType(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
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  /**
   *
   *
   * <pre>
   * Model evaluation metrics for text extraction problems.
   * </pre>
   *
   * Protobuf type {@code google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics}
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    public Builder mergeFrom(
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     *
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     * <code>float au_prc = 1;</code>
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    }

    private com.google.protobuf.RepeatedFieldBuilderV3<
            com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry,
            com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
                .Builder,
            com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
                .ConfidenceMetricsEntryOrBuilder>
        confidenceMetricsEntriesBuilder_;

    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public java.util.List<
            com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry>
        getConfidenceMetricsEntriesList() {
      if (confidenceMetricsEntriesBuilder_ == null) {
        return java.util.Collections.unmodifiableList(confidenceMetricsEntries_);
      } else {
        return confidenceMetricsEntriesBuilder_.getMessageList();
      }
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public int getConfidenceMetricsEntriesCount() {
      if (confidenceMetricsEntriesBuilder_ == null) {
        return confidenceMetricsEntries_.size();
      } else {
        return confidenceMetricsEntriesBuilder_.getCount();
      }
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
        getConfidenceMetricsEntries(int index) {
      if (confidenceMetricsEntriesBuilder_ == null) {
        return confidenceMetricsEntries_.get(index);
      } else {
        return confidenceMetricsEntriesBuilder_.getMessage(index);
      }
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public Builder setConfidenceMetricsEntries(
        int index,
        com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
            value) {
      if (confidenceMetricsEntriesBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        ensureConfidenceMetricsEntriesIsMutable();
        confidenceMetricsEntries_.set(index, value);
        onChanged();
      } else {
        confidenceMetricsEntriesBuilder_.setMessage(index, value);
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public Builder setConfidenceMetricsEntries(
        int index,
        com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
                .Builder
            builderForValue) {
      if (confidenceMetricsEntriesBuilder_ == null) {
        ensureConfidenceMetricsEntriesIsMutable();
        confidenceMetricsEntries_.set(index, builderForValue.build());
        onChanged();
      } else {
        confidenceMetricsEntriesBuilder_.setMessage(index, builderForValue.build());
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public Builder addConfidenceMetricsEntries(
        com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
            value) {
      if (confidenceMetricsEntriesBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        ensureConfidenceMetricsEntriesIsMutable();
        confidenceMetricsEntries_.add(value);
        onChanged();
      } else {
        confidenceMetricsEntriesBuilder_.addMessage(value);
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public Builder addConfidenceMetricsEntries(
        int index,
        com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
            value) {
      if (confidenceMetricsEntriesBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        ensureConfidenceMetricsEntriesIsMutable();
        confidenceMetricsEntries_.add(index, value);
        onChanged();
      } else {
        confidenceMetricsEntriesBuilder_.addMessage(index, value);
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public Builder addConfidenceMetricsEntries(
        com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
                .Builder
            builderForValue) {
      if (confidenceMetricsEntriesBuilder_ == null) {
        ensureConfidenceMetricsEntriesIsMutable();
        confidenceMetricsEntries_.add(builderForValue.build());
        onChanged();
      } else {
        confidenceMetricsEntriesBuilder_.addMessage(builderForValue.build());
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public Builder addConfidenceMetricsEntries(
        int index,
        com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
                .Builder
            builderForValue) {
      if (confidenceMetricsEntriesBuilder_ == null) {
        ensureConfidenceMetricsEntriesIsMutable();
        confidenceMetricsEntries_.add(index, builderForValue.build());
        onChanged();
      } else {
        confidenceMetricsEntriesBuilder_.addMessage(index, builderForValue.build());
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public Builder addAllConfidenceMetricsEntries(
        java.lang.Iterable<
                ? extends
                    com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
                        .ConfidenceMetricsEntry>
            values) {
      if (confidenceMetricsEntriesBuilder_ == null) {
        ensureConfidenceMetricsEntriesIsMutable();
        com.google.protobuf.AbstractMessageLite.Builder.addAll(values, confidenceMetricsEntries_);
        onChanged();
      } else {
        confidenceMetricsEntriesBuilder_.addAllMessages(values);
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public Builder clearConfidenceMetricsEntries() {
      if (confidenceMetricsEntriesBuilder_ == null) {
        confidenceMetricsEntries_ = java.util.Collections.emptyList();
        bitField0_ = (bitField0_ & ~0x00000002);
        onChanged();
      } else {
        confidenceMetricsEntriesBuilder_.clear();
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public Builder removeConfidenceMetricsEntries(int index) {
      if (confidenceMetricsEntriesBuilder_ == null) {
        ensureConfidenceMetricsEntriesIsMutable();
        confidenceMetricsEntries_.remove(index);
        onChanged();
      } else {
        confidenceMetricsEntriesBuilder_.remove(index);
      }
      return this;
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
            .Builder
        getConfidenceMetricsEntriesBuilder(int index) {
      return getConfidenceMetricsEntriesFieldBuilder().getBuilder(index);
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
            .ConfidenceMetricsEntryOrBuilder
        getConfidenceMetricsEntriesOrBuilder(int index) {
      if (confidenceMetricsEntriesBuilder_ == null) {
        return confidenceMetricsEntries_.get(index);
      } else {
        return confidenceMetricsEntriesBuilder_.getMessageOrBuilder(index);
      }
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public java.util.List<
            ? extends
                com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
                    .ConfidenceMetricsEntryOrBuilder>
        getConfidenceMetricsEntriesOrBuilderList() {
      if (confidenceMetricsEntriesBuilder_ != null) {
        return confidenceMetricsEntriesBuilder_.getMessageOrBuilderList();
      } else {
        return java.util.Collections.unmodifiableList(confidenceMetricsEntries_);
      }
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
            .Builder
        addConfidenceMetricsEntriesBuilder() {
      return getConfidenceMetricsEntriesFieldBuilder()
          .addBuilder(
              com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
                  .getDefaultInstance());
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
            .Builder
        addConfidenceMetricsEntriesBuilder(int index) {
      return getConfidenceMetricsEntriesFieldBuilder()
          .addBuilder(
              index,
              com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
                  .getDefaultInstance());
    }
    /**
     *
     *
     * <pre>
     * Output only. Metrics that have confidence thresholds.
     * Precision-recall curve can be derived from it.
     * </pre>
     *
     * <code>
     * repeated .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entries = 2;
     * </code>
     */
    public java.util.List<
            com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
                .Builder>
        getConfidenceMetricsEntriesBuilderList() {
      return getConfidenceMetricsEntriesFieldBuilder().getBuilderList();
    }

    private com.google.protobuf.RepeatedFieldBuilderV3<
            com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry,
            com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics.ConfidenceMetricsEntry
                .Builder,
            com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
                .ConfidenceMetricsEntryOrBuilder>
        getConfidenceMetricsEntriesFieldBuilder() {
      if (confidenceMetricsEntriesBuilder_ == null) {
        confidenceMetricsEntriesBuilder_ =
            new com.google.protobuf.RepeatedFieldBuilderV3<
                com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
                    .ConfidenceMetricsEntry,
                com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
                    .ConfidenceMetricsEntry.Builder,
                com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
                    .ConfidenceMetricsEntryOrBuilder>(
                confidenceMetricsEntries_,
                ((bitField0_ & 0x00000002) != 0),
                getParentForChildren(),
                isClean());
        confidenceMetricsEntries_ = null;
      }
      return confidenceMetricsEntriesBuilder_;
    }

    @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.automl.v1beta1.TextExtractionEvaluationMetrics)
  }

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

  static {
    DEFAULT_INSTANCE = new com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics();
  }

  public static com.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics
      getDefaultInstance() {
    return DEFAULT_INSTANCE;
  }

  private static final com.google.protobuf.Parser<TextExtractionEvaluationMetrics> PARSER =
      new com.google.protobuf.AbstractParser<TextExtractionEvaluationMetrics>() {
        @java.lang.Override
        public TextExtractionEvaluationMetrics 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<TextExtractionEvaluationMetrics> parser() {
    return PARSER;
  }

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

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