Class ModelMonitoringObjectiveConfig.TrainingDataset.Builder (3.0.0)

Version 3.0.0

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public static final class ModelMonitoringObjectiveConfig.TrainingDataset.Builder extends GeneratedMessageV3.Builder<ModelMonitoringObjectiveConfig.TrainingDataset.Builder> implements ModelMonitoringObjectiveConfig.TrainingDatasetOrBuilder

Training Dataset information.

Protobuf type google.cloud.aiplatform.v1.ModelMonitoringObjectiveConfig.TrainingDataset

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Implements

ModelMonitoringObjectiveConfig.TrainingDatasetOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns

Type	Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

public ModelMonitoringObjectiveConfig.TrainingDataset build()

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset

buildPartial()

public ModelMonitoringObjectiveConfig.TrainingDataset buildPartial()

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset

clear()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clear()

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearBigquerySource()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearBigquerySource()

The BigQuery table of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.BigQuerySource bigquery_source = 5;

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

clearDataFormat()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearDataFormat()

Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.

string data_format = 2;

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder	This builder for chaining.

clearDataSource()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearDataSource()

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

clearDataset()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearDataset()

The resource name of the Dataset used to train this Model.

string dataset = 3 [(.google.api.resource_reference) = { ... }

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearField(Descriptors.FieldDescriptor field)

Parameter

Name	Description
field	FieldDescriptor

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearGcsSource()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearGcsSource()

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.GcsSource gcs_source = 4;

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

clearLoggingSamplingStrategy()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearLoggingSamplingStrategy()

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 7;

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

clearOneof(Descriptors.OneofDescriptor oneof)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter

Name	Description
oneof	OneofDescriptor

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

clearTargetField()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearTargetField()

The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.

string target_field = 6;

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder	This builder for chaining.

clone()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clone()

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getBigquerySource()

public BigQuerySource getBigquerySource()

The BigQuery table of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.BigQuerySource bigquery_source = 5;

Returns

Type	Description
BigQuerySource	The bigquerySource.

getBigquerySourceBuilder()

public BigQuerySource.Builder getBigquerySourceBuilder()

The BigQuery table of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.BigQuerySource bigquery_source = 5;

Returns

Type	Description
BigQuerySource.Builder

getBigquerySourceOrBuilder()

public BigQuerySourceOrBuilder getBigquerySourceOrBuilder()

The BigQuery table of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.BigQuerySource bigquery_source = 5;

Returns

Type	Description
BigQuerySourceOrBuilder

getDataFormat()

public String getDataFormat()

Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.

string data_format = 2;

Returns

Type	Description
String	The dataFormat.

getDataFormatBytes()

public ByteString getDataFormatBytes()

Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.

string data_format = 2;

Returns

Type	Description
ByteString	The bytes for dataFormat.

getDataSourceCase()

public ModelMonitoringObjectiveConfig.TrainingDataset.DataSourceCase getDataSourceCase()

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.DataSourceCase

getDataset()

public String getDataset()

The resource name of the Dataset used to train this Model.

string dataset = 3 [(.google.api.resource_reference) = { ... }

Returns

Type	Description
String	The dataset.

getDatasetBytes()

public ByteString getDatasetBytes()

The resource name of the Dataset used to train this Model.

string dataset = 3 [(.google.api.resource_reference) = { ... }

Returns

Type	Description
ByteString	The bytes for dataset.

getDefaultInstanceForType()

public ModelMonitoringObjectiveConfig.TrainingDataset getDefaultInstanceForType()

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns

Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getGcsSource()

public GcsSource getGcsSource()

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.GcsSource gcs_source = 4;

Returns

Type	Description
GcsSource	The gcsSource.

getGcsSourceBuilder()

public GcsSource.Builder getGcsSourceBuilder()

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.GcsSource gcs_source = 4;

Returns

Type	Description
GcsSource.Builder

getGcsSourceOrBuilder()

public GcsSourceOrBuilder getGcsSourceOrBuilder()

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.GcsSource gcs_source = 4;

Returns

Type	Description
GcsSourceOrBuilder

getLoggingSamplingStrategy()

public SamplingStrategy getLoggingSamplingStrategy()

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 7;

Returns

Type	Description
SamplingStrategy	The loggingSamplingStrategy.

getLoggingSamplingStrategyBuilder()

public SamplingStrategy.Builder getLoggingSamplingStrategyBuilder()

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 7;

Returns

Type	Description
SamplingStrategy.Builder

getLoggingSamplingStrategyOrBuilder()

public SamplingStrategyOrBuilder getLoggingSamplingStrategyOrBuilder()

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 7;

Returns

Type	Description
SamplingStrategyOrBuilder

getTargetField()

public String getTargetField()

The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.

string target_field = 6;

Returns

Type	Description
String	The targetField.

getTargetFieldBytes()

public ByteString getTargetFieldBytes()

The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.

string target_field = 6;

Returns

Type	Description
ByteString	The bytes for targetField.

hasBigquerySource()

public boolean hasBigquerySource()

The BigQuery table of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.BigQuerySource bigquery_source = 5;

Returns

Type	Description
boolean	Whether the bigquerySource field is set.

hasDataset()

public boolean hasDataset()

The resource name of the Dataset used to train this Model.

string dataset = 3 [(.google.api.resource_reference) = { ... }

Returns

Type	Description
boolean	Whether the dataset field is set.

hasGcsSource()

public boolean hasGcsSource()

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.GcsSource gcs_source = 4;

Returns

Type	Description
boolean	Whether the gcsSource field is set.

hasLoggingSamplingStrategy()

public boolean hasLoggingSamplingStrategy()

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 7;

Returns

Type	Description
boolean	Whether the loggingSamplingStrategy field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns

Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns

Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeBigquerySource(BigQuerySource value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeBigquerySource(BigQuerySource value)

The BigQuery table of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.BigQuerySource bigquery_source = 5;

Parameter

Name	Description
value	BigQuerySource

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

mergeFrom(ModelMonitoringObjectiveConfig.TrainingDataset other)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeFrom(ModelMonitoringObjectiveConfig.TrainingDataset other)

Parameter

Name	Description
other	ModelMonitoringObjectiveConfig.TrainingDataset

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions

Type	Description
IOException

mergeFrom(Message other)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeFrom(Message other)

Parameter

Name	Description
other	Message

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeGcsSource(GcsSource value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeGcsSource(GcsSource value)

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.GcsSource gcs_source = 4;

Parameter

Name	Description
value	GcsSource

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

mergeLoggingSamplingStrategy(SamplingStrategy value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeLoggingSamplingStrategy(SamplingStrategy value)

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 7;

Parameter

Name	Description
value	SamplingStrategy

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

setBigquerySource(BigQuerySource value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setBigquerySource(BigQuerySource value)

The BigQuery table of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.BigQuerySource bigquery_source = 5;

Parameter

Name	Description
value	BigQuerySource

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

setBigquerySource(BigQuerySource.Builder builderForValue)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setBigquerySource(BigQuerySource.Builder builderForValue)

The BigQuery table of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.BigQuerySource bigquery_source = 5;

Parameter

Name	Description
builderForValue	BigQuerySource.Builder

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

setDataFormat(String value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setDataFormat(String value)

Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.

string data_format = 2;

Parameter

Name	Description
value	String The dataFormat to set.

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder	This builder for chaining.

setDataFormatBytes(ByteString value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setDataFormatBytes(ByteString value)

Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.

string data_format = 2;

Parameter

Name	Description
value	ByteString The bytes for dataFormat to set.

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder	This builder for chaining.

setDataset(String value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setDataset(String value)

The resource name of the Dataset used to train this Model.

string dataset = 3 [(.google.api.resource_reference) = { ... }

Parameter

Name	Description
value	String The dataset to set.

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder	This builder for chaining.

setDatasetBytes(ByteString value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setDatasetBytes(ByteString value)

The resource name of the Dataset used to train this Model.

string dataset = 3 [(.google.api.resource_reference) = { ... }

Parameter

Name	Description
value	ByteString The bytes for dataset to set.

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setGcsSource(GcsSource value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setGcsSource(GcsSource value)

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.GcsSource gcs_source = 4;

Parameter

Name	Description
value	GcsSource

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

setGcsSource(GcsSource.Builder builderForValue)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setGcsSource(GcsSource.Builder builderForValue)

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

.google.cloud.aiplatform.v1.GcsSource gcs_source = 4;

Parameter

Name	Description
builderForValue	GcsSource.Builder

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

setLoggingSamplingStrategy(SamplingStrategy value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setLoggingSamplingStrategy(SamplingStrategy value)

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 7;

Parameter

Name	Description
value	SamplingStrategy

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

setLoggingSamplingStrategy(SamplingStrategy.Builder builderForValue)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setLoggingSamplingStrategy(SamplingStrategy.Builder builderForValue)

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 7;

Parameter

Name	Description
builderForValue	SamplingStrategy.Builder

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters

Name	Description
field	FieldDescriptor
index	int
value	Object

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setTargetField(String value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setTargetField(String value)

The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.

string target_field = 6;

Parameter

Name	Description
value	String The targetField to set.

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder	This builder for chaining.

setTargetFieldBytes(ByteString value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setTargetFieldBytes(ByteString value)

The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.

string target_field = 6;

Parameter

Name	Description
value	ByteString The bytes for targetField to set.

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder	This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final ModelMonitoringObjectiveConfig.TrainingDataset.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)