Packages

c

org.tensorflow.metadata.v0

ProblemStatement

final class ProblemStatement extends GeneratedMessageV3 with ProblemStatementOrBuilder

Protobuf type tensorflow.metadata.v0.ProblemStatement

Source
ProblemStatement.java
Linear Supertypes
ProblemStatementOrBuilder, GeneratedMessageV3, Serializable, AbstractMessage, Message, MessageOrBuilder, AbstractMessageLite[MessageType, BuilderType], MessageLite, MessageLiteOrBuilder, AnyRef, Any
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Inherited
  1. ProblemStatement
  2. ProblemStatementOrBuilder
  3. GeneratedMessageV3
  4. Serializable
  5. AbstractMessage
  6. Message
  7. MessageOrBuilder
  8. AbstractMessageLite
  9. MessageLite
  10. MessageLiteOrBuilder
  11. AnyRef
  12. Any
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Visibility
  1. Public
  2. Protected

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(obj: AnyRef): Boolean
    Definition Classes
    ProblemStatement → AbstractMessage → Message → AnyRef → Any
    Annotations
    @Override()
  8. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  9. def findInitializationErrors(): List[String]
    Definition Classes
    AbstractMessage → MessageOrBuilder
  10. def getAllFields(): Map[FieldDescriptor, AnyRef]
    Definition Classes
    GeneratedMessageV3 → MessageOrBuilder
  11. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  12. def getDefaultInstanceForType(): ProblemStatement
    Definition Classes
    ProblemStatement → MessageOrBuilder → MessageLiteOrBuilder
    Annotations
    @Override()
  13. def getDescription(): String

    Description of the problem statement. For example, should describe how
the problem statement was arrived at: what experiments were run, what
side-by-sides were considered.


    Description of the problem statement. For example, should describe how
the problem statement was arrived at: what experiments were run, what
side-by-sides were considered.

    string description = 2;

    returns

    The description.

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  14. def getDescriptionBytes(): ByteString

    Description of the problem statement. For example, should describe how
the problem statement was arrived at: what experiments were run, what
side-by-sides were considered.


    Description of the problem statement. For example, should describe how
the problem statement was arrived at: what experiments were run, what
side-by-sides were considered.

    string description = 2;

    returns

    The bytes for description.

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  15. def getDescriptorForType(): Descriptor
    Definition Classes
    GeneratedMessageV3 → MessageOrBuilder
  16. def getEnvironment(): String

    The environment of the ProblemStatement (optional). Specifies an
environment string in the SchemaProto.


    The environment of the ProblemStatement (optional). Specifies an
environment string in the SchemaProto.

    string environment = 4;

    returns

    The environment.

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  17. def getEnvironmentBytes(): ByteString

    The environment of the ProblemStatement (optional). Specifies an
environment string in the SchemaProto.


    The environment of the ProblemStatement (optional). Specifies an
environment string in the SchemaProto.

    string environment = 4;

    returns

    The bytes for environment.

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  18. def getField(field: FieldDescriptor): AnyRef
    Definition Classes
    GeneratedMessageV3 → MessageOrBuilder
  19. def getInitializationErrorString(): String
    Definition Classes
    AbstractMessage → MessageOrBuilder
  20. def getMetaOptimizationTarget(index: Int): MetaOptimizationTarget

    The target used for meta-optimization. This is used to compare multiple
solutions for this problem. For example, if two solutions have different
candidates, a tuning tool can use meta_optimization_target to decide which
candidate performs the best.
A repeated meta-optimization target implies the weighted sum of the
meta_optimization targets of any non-thresholded metrics.


    The target used for meta-optimization. This is used to compare multiple
solutions for this problem. For example, if two solutions have different
candidates, a tuning tool can use meta_optimization_target to decide which
candidate performs the best.
A repeated meta-optimization target implies the weighted sum of the
meta_optimization targets of any non-thresholded metrics.

    repeated .tensorflow.metadata.v0.MetaOptimizationTarget meta_optimization_target = 7;

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  21. def getMetaOptimizationTargetCount(): Int

    The target used for meta-optimization. This is used to compare multiple
solutions for this problem. For example, if two solutions have different
candidates, a tuning tool can use meta_optimization_target to decide which
candidate performs the best.
A repeated meta-optimization target implies the weighted sum of the
meta_optimization targets of any non-thresholded metrics.


    The target used for meta-optimization. This is used to compare multiple
solutions for this problem. For example, if two solutions have different
candidates, a tuning tool can use meta_optimization_target to decide which
candidate performs the best.
A repeated meta-optimization target implies the weighted sum of the
meta_optimization targets of any non-thresholded metrics.

    repeated .tensorflow.metadata.v0.MetaOptimizationTarget meta_optimization_target = 7;

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  22. def getMetaOptimizationTargetList(): List[MetaOptimizationTarget]

    The target used for meta-optimization. This is used to compare multiple
solutions for this problem. For example, if two solutions have different
candidates, a tuning tool can use meta_optimization_target to decide which
candidate performs the best.
A repeated meta-optimization target implies the weighted sum of the
meta_optimization targets of any non-thresholded metrics.


    The target used for meta-optimization. This is used to compare multiple
solutions for this problem. For example, if two solutions have different
candidates, a tuning tool can use meta_optimization_target to decide which
candidate performs the best.
A repeated meta-optimization target implies the weighted sum of the
meta_optimization targets of any non-thresholded metrics.

    repeated .tensorflow.metadata.v0.MetaOptimizationTarget meta_optimization_target = 7;

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  23. def getMetaOptimizationTargetOrBuilder(index: Int): MetaOptimizationTargetOrBuilder

    The target used for meta-optimization. This is used to compare multiple
solutions for this problem. For example, if two solutions have different
candidates, a tuning tool can use meta_optimization_target to decide which
candidate performs the best.
A repeated meta-optimization target implies the weighted sum of the
meta_optimization targets of any non-thresholded metrics.


    The target used for meta-optimization. This is used to compare multiple
solutions for this problem. For example, if two solutions have different
candidates, a tuning tool can use meta_optimization_target to decide which
candidate performs the best.
A repeated meta-optimization target implies the weighted sum of the
meta_optimization targets of any non-thresholded metrics.

    repeated .tensorflow.metadata.v0.MetaOptimizationTarget meta_optimization_target = 7;

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  24. def getMetaOptimizationTargetOrBuilderList(): List[_ <: MetaOptimizationTargetOrBuilder]

    The target used for meta-optimization. This is used to compare multiple
solutions for this problem. For example, if two solutions have different
candidates, a tuning tool can use meta_optimization_target to decide which
candidate performs the best.
A repeated meta-optimization target implies the weighted sum of the
meta_optimization targets of any non-thresholded metrics.


    The target used for meta-optimization. This is used to compare multiple
solutions for this problem. For example, if two solutions have different
candidates, a tuning tool can use meta_optimization_target to decide which
candidate performs the best.
A repeated meta-optimization target implies the weighted sum of the
meta_optimization targets of any non-thresholded metrics.

    repeated .tensorflow.metadata.v0.MetaOptimizationTarget meta_optimization_target = 7;

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  25. def getOneofFieldDescriptor(oneof: OneofDescriptor): FieldDescriptor
    Definition Classes
    GeneratedMessageV3 → AbstractMessage → MessageOrBuilder
  26. def getOwner(index: Int): String

    repeated string owner = 3;

    repeated string owner = 3;

    index

    The index of the element to return.

    returns

    The owner at the given index.

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
  27. def getOwnerBytes(index: Int): ByteString

    repeated string owner = 3;

    repeated string owner = 3;

    index

    The index of the value to return.

    returns

    The bytes of the owner at the given index.

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
  28. def getOwnerCount(): Int

    repeated string owner = 3;

    repeated string owner = 3;

    returns

    The count of owner.

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
  29. def getOwnerList(): ProtocolStringList

    repeated string owner = 3;

    repeated string owner = 3;

    returns

    A list containing the owner.

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
  30. def getParserForType(): Parser[ProblemStatement]
    Definition Classes
    ProblemStatement → GeneratedMessageV3 → Message → MessageLite
    Annotations
    @Override()
  31. def getRepeatedField(field: FieldDescriptor, index: Int): AnyRef
    Definition Classes
    GeneratedMessageV3 → MessageOrBuilder
  32. def getRepeatedFieldCount(field: FieldDescriptor): Int
    Definition Classes
    GeneratedMessageV3 → MessageOrBuilder
  33. def getSerializedSize(): Int
    Definition Classes
    ProblemStatement → GeneratedMessageV3 → AbstractMessage → MessageLite
    Annotations
    @Override()
  34. def getTasks(index: Int): Task

    Tasks for heads of the generated model. This field is repeated because some
models are multi-task models. Each task should have a unique name.
If you wish to directly optimize this problem statement, you need
to specify the objective in the task.


    Tasks for heads of the generated model. This field is repeated because some
models are multi-task models. Each task should have a unique name.
If you wish to directly optimize this problem statement, you need
to specify the objective in the task.

    repeated .tensorflow.metadata.v0.Task tasks = 9;

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  35. def getTasksCount(): Int

    Tasks for heads of the generated model. This field is repeated because some
models are multi-task models. Each task should have a unique name.
If you wish to directly optimize this problem statement, you need
to specify the objective in the task.


    Tasks for heads of the generated model. This field is repeated because some
models are multi-task models. Each task should have a unique name.
If you wish to directly optimize this problem statement, you need
to specify the objective in the task.

    repeated .tensorflow.metadata.v0.Task tasks = 9;

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  36. def getTasksList(): List[Task]

    Tasks for heads of the generated model. This field is repeated because some
models are multi-task models. Each task should have a unique name.
If you wish to directly optimize this problem statement, you need
to specify the objective in the task.


    Tasks for heads of the generated model. This field is repeated because some
models are multi-task models. Each task should have a unique name.
If you wish to directly optimize this problem statement, you need
to specify the objective in the task.

    repeated .tensorflow.metadata.v0.Task tasks = 9;

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  37. def getTasksOrBuilder(index: Int): TaskOrBuilder

    Tasks for heads of the generated model. This field is repeated because some
models are multi-task models. Each task should have a unique name.
If you wish to directly optimize this problem statement, you need
to specify the objective in the task.


    Tasks for heads of the generated model. This field is repeated because some
models are multi-task models. Each task should have a unique name.
If you wish to directly optimize this problem statement, you need
to specify the objective in the task.

    repeated .tensorflow.metadata.v0.Task tasks = 9;

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  38. def getTasksOrBuilderList(): List[_ <: TaskOrBuilder]

    Tasks for heads of the generated model. This field is repeated because some
models are multi-task models. Each task should have a unique name.
If you wish to directly optimize this problem statement, you need
to specify the objective in the task.


    Tasks for heads of the generated model. This field is repeated because some
models are multi-task models. Each task should have a unique name.
If you wish to directly optimize this problem statement, you need
to specify the objective in the task.

    repeated .tensorflow.metadata.v0.Task tasks = 9;

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override()
  39. def getUnknownFields(): UnknownFieldSet
    Definition Classes
    GeneratedMessageV3 → MessageOrBuilder
  40. def hasField(field: FieldDescriptor): Boolean
    Definition Classes
    GeneratedMessageV3 → MessageOrBuilder
  41. def hasOneof(oneof: OneofDescriptor): Boolean
    Definition Classes
    GeneratedMessageV3 → AbstractMessage → MessageOrBuilder
  42. def hashCode(): Int
    Definition Classes
    ProblemStatement → AbstractMessage → Message → AnyRef → Any
    Annotations
    @Override()
  43. def internalGetFieldAccessorTable(): FieldAccessorTable
    Attributes
    protected[v0]
    Definition Classes
    ProblemStatement → GeneratedMessageV3
    Annotations
    @Override()
  44. def internalGetMapFieldReflection(fieldNumber: Int): MapFieldReflectionAccessor
    Attributes
    protected[protobuf]
    Definition Classes
    GeneratedMessageV3
  45. final def isInitialized(): Boolean
    Definition Classes
    ProblemStatement → GeneratedMessageV3 → AbstractMessage → MessageLiteOrBuilder
    Annotations
    @Override()
  46. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  47. def makeExtensionsImmutable(): Unit
    Attributes
    protected[protobuf]
    Definition Classes
    GeneratedMessageV3
  48. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  49. def newBuilderForType(parent: BuilderParent): Builder
    Attributes
    protected[v0]
    Definition Classes
    ProblemStatement → GeneratedMessageV3
    Annotations
    @Override()
  50. def newBuilderForType(): Builder
    Definition Classes
    ProblemStatement → Message → MessageLite
    Annotations
    @Override()
  51. def newBuilderForType(parent: BuilderParent): Builder
    Attributes
    protected[protobuf]
    Definition Classes
    GeneratedMessageV3 → AbstractMessage
  52. def newInstance(unused: UnusedPrivateParameter): AnyRef
    Attributes
    protected[v0]
    Definition Classes
    ProblemStatement → GeneratedMessageV3
    Annotations
    @Override() @SuppressWarnings()
  53. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  54. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  55. def parseUnknownField(input: CodedInputStream, unknownFields: Builder, extensionRegistry: ExtensionRegistryLite, tag: Int): Boolean
    Attributes
    protected[protobuf]
    Definition Classes
    GeneratedMessageV3
    Annotations
    @throws(classOf[java.io.IOException])
  56. def parseUnknownFieldProto3(input: CodedInputStream, unknownFields: Builder, extensionRegistry: ExtensionRegistryLite, tag: Int): Boolean
    Attributes
    protected[protobuf]
    Definition Classes
    GeneratedMessageV3
    Annotations
    @throws(classOf[java.io.IOException])
  57. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  58. def toBuilder(): Builder
    Definition Classes
    ProblemStatement → Message → MessageLite
    Annotations
    @Override()
  59. def toByteArray(): Array[Byte]
    Definition Classes
    AbstractMessageLite → MessageLite
  60. def toByteString(): ByteString
    Definition Classes
    AbstractMessageLite → MessageLite
  61. final def toString(): String
    Definition Classes
    AbstractMessage → Message → AnyRef → Any
  62. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  63. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  64. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  65. def writeDelimitedTo(output: OutputStream): Unit
    Definition Classes
    AbstractMessageLite → MessageLite
    Annotations
    @throws(classOf[java.io.IOException])
  66. def writeReplace(): AnyRef
    Attributes
    protected[protobuf]
    Definition Classes
    GeneratedMessageV3
    Annotations
    @throws(classOf[java.io.ObjectStreamException])
  67. def writeTo(output: CodedOutputStream): Unit
    Definition Classes
    ProblemStatement → GeneratedMessageV3 → AbstractMessage → MessageLite
    Annotations
    @Override()
  68. def writeTo(output: OutputStream): Unit
    Definition Classes
    AbstractMessageLite → MessageLite
    Annotations
    @throws(classOf[java.io.IOException])

Deprecated Value Members

  1. def getMultiObjective(): Boolean

    bool multi_objective = 8 [deprecated = true];

    bool multi_objective = 8 [deprecated = true];

    returns

    The multiObjective.

    Definition Classes
    ProblemStatement → ProblemStatementOrBuilder
    Annotations
    @Override() @Deprecated
    Deprecated
  2. def internalGetMapField(fieldNumber: Int): MapField[_ <: AnyRef, _ <: AnyRef]
    Attributes
    protected[protobuf]
    Definition Classes
    GeneratedMessageV3
    Annotations
    @Deprecated
    Deprecated
  3. def mergeFromAndMakeImmutableInternal(input: CodedInputStream, extensionRegistry: ExtensionRegistryLite): Unit
    Attributes
    protected[protobuf]
    Definition Classes
    GeneratedMessageV3
    Annotations
    @throws(classOf[com.google.protobuf.InvalidProtocolBufferException]) @Deprecated
    Deprecated

Inherited from ProblemStatementOrBuilder

Inherited from GeneratedMessageV3

Inherited from Serializable

Inherited from AbstractMessage

Inherited from Message

Inherited from MessageOrBuilder

Inherited from AbstractMessageLite[MessageType, BuilderType]

Inherited from MessageLite

Inherited from MessageLiteOrBuilder

Inherited from AnyRef

Inherited from Any

Ungrouped