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t

org.tensorflow.metadata.v0

SequenceMetadataOrBuilder

trait SequenceMetadataOrBuilder extends MessageOrBuilder

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  1. SequenceMetadataOrBuilder
  2. MessageOrBuilder
  3. MessageLiteOrBuilder
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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 getJointGroup(): String

    An arbitrary string defining a "group" of features that could be modeled as
    a single joint sequence. For example, consider a dataset that contains
    three sequential features "purchase_time", "product_id", "purchase_price".
    These belong to the same sequence of purchases and could be modeled
    jointly. Specifying joint_group = "purchase" on all three sequences would
    communicate that the features can be considered part of a single conceptual
    sequence.
    

    An arbitrary string defining a "group" of features that could be modeled as
    a single joint sequence. For example, consider a dataset that contains
    three sequential features "purchase_time", "product_id", "purchase_price".
    These belong to the same sequence of purchases and could be modeled
    jointly. Specifying joint_group = "purchase" on all three sequences would
    communicate that the features can be considered part of a single conceptual
    sequence.
    

    optional string joint_group = 4;

    returns

    The jointGroup.

  8. abstract def getJointGroupBytes(): ByteString

    An arbitrary string defining a "group" of features that could be modeled as
    a single joint sequence. For example, consider a dataset that contains
    three sequential features "purchase_time", "product_id", "purchase_price".
    These belong to the same sequence of purchases and could be modeled
    jointly. Specifying joint_group = "purchase" on all three sequences would
    communicate that the features can be considered part of a single conceptual
    sequence.
    

    An arbitrary string defining a "group" of features that could be modeled as
    a single joint sequence. For example, consider a dataset that contains
    three sequential features "purchase_time", "product_id", "purchase_price".
    These belong to the same sequence of purchases and could be modeled
    jointly. Specifying joint_group = "purchase" on all three sequences would
    communicate that the features can be considered part of a single conceptual
    sequence.
    

    optional string joint_group = 4;

    returns

    The bytes for jointGroup.

  9. abstract def getOneofFieldDescriptor(oneof: OneofDescriptor): FieldDescriptor
    Definition Classes
    MessageOrBuilder
  10. abstract def getRepeatedField(field: FieldDescriptor, index: Int): AnyRef
    Definition Classes
    MessageOrBuilder
  11. abstract def getRepeatedFieldCount(field: FieldDescriptor): Int
    Definition Classes
    MessageOrBuilder
  12. abstract def getSequenceTruncationLimit(): Long

    Specifies the maximum sequence length that should be processed. Sequences
    may exceed this limit but are expected to be truncated by modeling layers.
    

    Specifies the maximum sequence length that should be processed. Sequences
    may exceed this limit but are expected to be truncated by modeling layers.
    

    optional int64 sequence_truncation_limit = 5;

    returns

    The sequenceTruncationLimit.

  13. abstract def getSequentialStatus(): SequentialStatus

    optional .tensorflow.metadata.v0.SequenceMetadata.SequentialStatus sequential_status = 3;

    optional .tensorflow.metadata.v0.SequenceMetadata.SequentialStatus sequential_status = 3;

    returns

    The sequentialStatus.

  14. abstract def getUnknownFields(): UnknownFieldSet
    Definition Classes
    MessageOrBuilder
  15. abstract def hasField(field: FieldDescriptor): Boolean
    Definition Classes
    MessageOrBuilder
  16. abstract def hasJointGroup(): Boolean

    An arbitrary string defining a "group" of features that could be modeled as
    a single joint sequence. For example, consider a dataset that contains
    three sequential features "purchase_time", "product_id", "purchase_price".
    These belong to the same sequence of purchases and could be modeled
    jointly. Specifying joint_group = "purchase" on all three sequences would
    communicate that the features can be considered part of a single conceptual
    sequence.
    

    An arbitrary string defining a "group" of features that could be modeled as
    a single joint sequence. For example, consider a dataset that contains
    three sequential features "purchase_time", "product_id", "purchase_price".
    These belong to the same sequence of purchases and could be modeled
    jointly. Specifying joint_group = "purchase" on all three sequences would
    communicate that the features can be considered part of a single conceptual
    sequence.
    

    optional string joint_group = 4;

    returns

    Whether the jointGroup field is set.

  17. abstract def hasOneof(oneof: OneofDescriptor): Boolean
    Definition Classes
    MessageOrBuilder
  18. abstract def hasSequenceTruncationLimit(): Boolean

    Specifies the maximum sequence length that should be processed. Sequences
    may exceed this limit but are expected to be truncated by modeling layers.
    

    Specifies the maximum sequence length that should be processed. Sequences
    may exceed this limit but are expected to be truncated by modeling layers.
    

    optional int64 sequence_truncation_limit = 5;

    returns

    Whether the sequenceTruncationLimit field is set.

  19. abstract def hasSequentialStatus(): Boolean

    optional .tensorflow.metadata.v0.SequenceMetadata.SequentialStatus sequential_status = 3;

    optional .tensorflow.metadata.v0.SequenceMetadata.SequentialStatus sequential_status = 3;

    returns

    Whether the sequentialStatus field is set.

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