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// Generated by the protocol buffer compiler.  DO NOT EDIT!
// source: tensorflow_metadata/proto/v0/problem_statement.proto

// Protobuf Java Version: 3.25.4
package org.tensorflow.metadata.v0;

public interface TaskOrBuilder extends
    // @@protoc_insertion_point(interface_extends:tensorflow.metadata.v0.Task)
    com.google.protobuf.MessageOrBuilder {

  /**
   *    * Specification of the label and weight columns, and the type of the
   * prediction or classification.
   * 
   *
   * .tensorflow.metadata.v0.Type type = 1;
   * @return Whether the type field is set.
   */
  boolean hasType();
  /**
   *    * Specification of the label and weight columns, and the type of the
   * prediction or classification.
   * 
   *
   * .tensorflow.metadata.v0.Type type = 1;
   * @return The type.
   */
  org.tensorflow.metadata.v0.Type getType();
  /**
   *    * Specification of the label and weight columns, and the type of the
   * prediction or classification.
   * 
   *
   * .tensorflow.metadata.v0.Type type = 1;
   */
  org.tensorflow.metadata.v0.TypeOrBuilder getTypeOrBuilder();

  /**
   *    * The task name. Tasks within the same ProblemStatement should have unique
   * names. This a REQUIRED field in case of multi-task learning problems.
   * 
   *
   * string name = 5;
   * @return The name.
   */
  java.lang.String getName();
  /**
   *    * The task name. Tasks within the same ProblemStatement should have unique
   * names. This a REQUIRED field in case of multi-task learning problems.
   * 
   *
   * string name = 5;
   * @return The bytes for name.
   */
  com.google.protobuf.ByteString
      getNameBytes();

  /**
   *    * If a Problem is composed of mulitple sub-tasks, the weight of each task
   * determines the importance of solving each sub-task. It is used to
   * rank and select the best solution for multi-task problems.
   * Not meaningful for a problem with one task.
   * If the problem has multiple tasks and all task_weight=0 (unset) then all
   * tasks are weighted equally.
   * 
   *
   * double task_weight = 2 [deprecated = true];
   * @deprecated tensorflow.metadata.v0.Task.task_weight is deprecated.
   *     See tensorflow_metadata/proto/v0/problem_statement.proto;l=259
   * @return The taskWeight.
   */
  @java.lang.Deprecated double getTaskWeight();

  /**
   *    * This field includes performance metrics of this head that are important to
   * the problem owner and need to be monitored and reported. However, unlike
   * fields such as "meta_optimization_target", these metrics are not
   * not automatically used in meta-optimization.
   * 
   *
   * repeated .tensorflow.metadata.v0.PerformanceMetric performance_metric = 4;
   */
  java.util.List 
      getPerformanceMetricList();
  /**
   *    * This field includes performance metrics of this head that are important to
   * the problem owner and need to be monitored and reported. However, unlike
   * fields such as "meta_optimization_target", these metrics are not
   * not automatically used in meta-optimization.
   * 
   *
   * repeated .tensorflow.metadata.v0.PerformanceMetric performance_metric = 4;
   */
  org.tensorflow.metadata.v0.PerformanceMetric getPerformanceMetric(int index);
  /**
   *    * This field includes performance metrics of this head that are important to
   * the problem owner and need to be monitored and reported. However, unlike
   * fields such as "meta_optimization_target", these metrics are not
   * not automatically used in meta-optimization.
   * 
   *
   * repeated .tensorflow.metadata.v0.PerformanceMetric performance_metric = 4;
   */
  int getPerformanceMetricCount();
  /**
   *    * This field includes performance metrics of this head that are important to
   * the problem owner and need to be monitored and reported. However, unlike
   * fields such as "meta_optimization_target", these metrics are not
   * not automatically used in meta-optimization.
   * 
   *
   * repeated .tensorflow.metadata.v0.PerformanceMetric performance_metric = 4;
   */
  java.util.List 
      getPerformanceMetricOrBuilderList();
  /**
   *    * This field includes performance metrics of this head that are important to
   * the problem owner and need to be monitored and reported. However, unlike
   * fields such as "meta_optimization_target", these metrics are not
   * not automatically used in meta-optimization.
   * 
   *
   * repeated .tensorflow.metadata.v0.PerformanceMetric performance_metric = 4;
   */
  org.tensorflow.metadata.v0.PerformanceMetricOrBuilder getPerformanceMetricOrBuilder(
      int index);

  /**
   *    * True to indicate the task is an auxiliary task in a multi-task setting.
   * Auxiliary tasks are of minor relevance for the application and they are
   * added only to improve the performance on a primary task (by providing
   * additional regularization or data augmentation), and thus are not
   * considered in the meta optimization process (but may be utilized in the
   * learner optimization).
   * 
   *
   * bool is_auxiliary = 6;
   * @return The isAuxiliary.
   */
  boolean getIsAuxiliary();
}