org.tensorflow.metadata.v0.SequenceMetadataOrBuilder Maven / Gradle / Ivy
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// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow_metadata/proto/v0/schema.proto
// Protobuf Java Version: 3.25.4
package org.tensorflow.metadata.v0;
public interface SequenceMetadataOrBuilder extends
// @@protoc_insertion_point(interface_extends:tensorflow.metadata.v0.SequenceMetadata)
com.google.protobuf.MessageOrBuilder {
/**
* optional .tensorflow.metadata.v0.SequenceMetadata.SequentialStatus sequential_status = 3;
* @return Whether the sequentialStatus field is set.
*/
boolean hasSequentialStatus();
/**
* optional .tensorflow.metadata.v0.SequenceMetadata.SequentialStatus sequential_status = 3;
* @return The sequentialStatus.
*/
org.tensorflow.metadata.v0.SequenceMetadata.SequentialStatus getSequentialStatus();
/**
*
* 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;
* @return Whether the jointGroup field is set.
*/
boolean hasJointGroup();
/**
*
* 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;
* @return The jointGroup.
*/
java.lang.String getJointGroup();
/**
*
* 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;
* @return The bytes for jointGroup.
*/
com.google.protobuf.ByteString
getJointGroupBytes();
/**
*
* 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;
* @return Whether the sequenceTruncationLimit field is set.
*/
boolean hasSequenceTruncationLimit();
/**
*
* 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;
* @return The sequenceTruncationLimit.
*/
long getSequenceTruncationLimit();
}
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