Class ModelMonitoringObjectiveConfig.TrainingDataset.Builder (3.47.0)

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

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

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

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

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

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

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

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

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

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
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

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

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

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

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