Packages

trait TaskOrBuilder extends MessageOrBuilder

Annotations
@Generated()
Source
TaskOrBuilder.java
Linear Supertypes
MessageOrBuilder, MessageLiteOrBuilder, AnyRef, Any
Known Subclasses
Task
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Inherited
  1. TaskOrBuilder
  2. MessageOrBuilder
  3. MessageLiteOrBuilder
  4. AnyRef
  5. Any
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Visibility
  1. Public
  2. Protected

Abstract Value Members

  1. abstract def findInitializationErrors(): List[String]
    Definition Classes
    MessageOrBuilder
  2. abstract def getAllFields(): Map[FieldDescriptor, AnyRef]
    Definition Classes
    MessageOrBuilder
  3. abstract def getDefaultInstanceForType(): Message
    Definition Classes
    MessageOrBuilder → MessageLiteOrBuilder
  4. abstract def getDescriptorForType(): Descriptor
    Definition Classes
    MessageOrBuilder
  5. abstract def getField(field: FieldDescriptor): AnyRef
    Definition Classes
    MessageOrBuilder
  6. abstract def getInitializationErrorString(): String
    Definition Classes
    MessageOrBuilder
  7. abstract def getIsAuxiliary(): Boolean

    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).


    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;

    returns

    The isAuxiliary.

  8. abstract def getName(): String

    The task name. Tasks within the same ProblemStatement should have unique
names. This a REQUIRED field in case of multi-task learning problems.


    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;

    returns

    The name.

  9. abstract def getNameBytes(): ByteString

    The task name. Tasks within the same ProblemStatement should have unique
names. This a REQUIRED field in case of multi-task learning problems.


    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;

    returns

    The bytes for name.

  10. abstract def getOneofFieldDescriptor(oneof: OneofDescriptor): FieldDescriptor
    Definition Classes
    MessageOrBuilder
  11. abstract def getPerformanceMetric(index: Int): PerformanceMetric

    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.


    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;

  12. abstract def getPerformanceMetricCount(): Int

    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.


    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;

  13. abstract def getPerformanceMetricList(): List[PerformanceMetric]

    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.


    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;

  14. abstract def getPerformanceMetricOrBuilder(index: Int): PerformanceMetricOrBuilder

    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.


    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;

  15. abstract def getPerformanceMetricOrBuilderList(): List[_ <: PerformanceMetricOrBuilder]

    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.


    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;

  16. abstract def getRepeatedField(field: FieldDescriptor, index: Int): AnyRef
    Definition Classes
    MessageOrBuilder
  17. abstract def getRepeatedFieldCount(field: FieldDescriptor): Int
    Definition Classes
    MessageOrBuilder
  18. abstract def getTaskWeight(): Double

    If a Problem is composed of multiple 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.


    If a Problem is composed of multiple 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;

    returns

    The taskWeight.

  19. abstract def getType(): Type

    Specification of the label and weight columns, and the type of the
prediction or classification.


    Specification of the label and weight columns, and the type of the
prediction or classification.

    .tensorflow.metadata.v0.Type type = 1;

    returns

    The type.

  20. abstract def getTypeOrBuilder(): TypeOrBuilder

    Specification of the label and weight columns, and the type of the
prediction or classification.


    Specification of the label and weight columns, and the type of the
prediction or classification.

    .tensorflow.metadata.v0.Type type = 1;

  21. abstract def getUnknownFields(): UnknownFieldSet
    Definition Classes
    MessageOrBuilder
  22. abstract def hasField(field: FieldDescriptor): Boolean
    Definition Classes
    MessageOrBuilder
  23. abstract def hasOneof(oneof: OneofDescriptor): Boolean
    Definition Classes
    MessageOrBuilder
  24. abstract def hasType(): Boolean

    Specification of the label and weight columns, and the type of the
prediction or classification.


    Specification of the label and weight columns, and the type of the
prediction or classification.

    .tensorflow.metadata.v0.Type type = 1;

    returns

    Whether the type field is set.

  25. abstract def isInitialized(): Boolean
    Definition Classes
    MessageLiteOrBuilder

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##: Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  8. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  9. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  10. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  11. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  12. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  13. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  14. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  15. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  16. def toString(): String
    Definition Classes
    AnyRef → Any
  17. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  18. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  19. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()

Inherited from MessageOrBuilder

Inherited from MessageLiteOrBuilder

Inherited from AnyRef

Inherited from Any

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