trait SequenceMetadataOrBuilder extends MessageOrBuilder
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- abstract def findInitializationErrors(): List[String]
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- MessageOrBuilder
- abstract def getAllFields(): Map[FieldDescriptor, AnyRef]
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- MessageOrBuilder
- abstract def getDefaultInstanceForType(): Message
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- MessageOrBuilder → MessageLiteOrBuilder
- abstract def getDescriptorForType(): Descriptor
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- abstract def getField(field: FieldDescriptor): AnyRef
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- MessageOrBuilder
- abstract def getInitializationErrorString(): String
- Definition Classes
- MessageOrBuilder
- 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.
- 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.
- abstract def getOneofFieldDescriptor(oneof: OneofDescriptor): FieldDescriptor
- Definition Classes
- MessageOrBuilder
- abstract def getRepeatedField(field: FieldDescriptor, index: Int): AnyRef
- Definition Classes
- MessageOrBuilder
- abstract def getRepeatedFieldCount(field: FieldDescriptor): Int
- Definition Classes
- MessageOrBuilder
- 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.
- 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.
- abstract def getUnknownFields(): UnknownFieldSet
- Definition Classes
- MessageOrBuilder
- abstract def hasField(field: FieldDescriptor): Boolean
- Definition Classes
- MessageOrBuilder
- 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.
- abstract def hasOneof(oneof: OneofDescriptor): Boolean
- Definition Classes
- MessageOrBuilder
- 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.
- 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.
- abstract def isInitialized(): Boolean
- Definition Classes
- MessageLiteOrBuilder
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