Class ModelMonitoringObjectiveConfig.TrainingDataset.Builder (3.8.0)

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
TypeDescription
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder
Overrides

build()

public ModelMonitoringObjectiveConfig.TrainingDataset build()
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset

buildPartial()

public ModelMonitoringObjectiveConfig.TrainingDataset buildPartial()
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset

clear()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clear()
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

This builder for chaining.

clearDataSource()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearDataSource()
Returns
TypeDescription
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
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

clearOneof(Descriptors.OneofDescriptor oneof)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
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
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

This builder for chaining.

clone()

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clone()
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
ByteString

The bytes for dataFormat.

getDataSourceCase()

public ModelMonitoringObjectiveConfig.TrainingDataset.DataSourceCase getDataSourceCase()
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
ByteString

The bytes for dataset.

getDefaultInstanceForType()

public ModelMonitoringObjectiveConfig.TrainingDataset getDefaultInstanceForType()
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
boolean

Whether the loggingSamplingStrategy field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
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
NameDescription
valueBigQuerySource
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

mergeFrom(ModelMonitoringObjectiveConfig.TrainingDataset other)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeFrom(ModelMonitoringObjectiveConfig.TrainingDataset other)
Parameter
NameDescription
otherModelMonitoringObjectiveConfig.TrainingDataset
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder
Overrides Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
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
NameDescription
valueGcsSource
Returns
TypeDescription
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
NameDescription
valueSamplingStrategy
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
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
NameDescription
valueBigQuerySource
Returns
TypeDescription
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
NameDescription
builderForValueBigQuerySource.Builder
Returns
TypeDescription
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
NameDescription
valueString

The dataFormat to set.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes for dataFormat to set.

Returns
TypeDescription
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
NameDescription
valueString

The dataset to set.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes for dataset to set.

Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
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
NameDescription
valueGcsSource
Returns
TypeDescription
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
NameDescription
builderForValueGcsSource.Builder
Returns
TypeDescription
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
NameDescription
valueSamplingStrategy
Returns
TypeDescription
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
NameDescription
builderForValueSamplingStrategy.Builder
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

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

public ModelMonitoringObjectiveConfig.TrainingDataset.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
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
NameDescription
valueString

The targetField to set.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes for targetField to set.

Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final ModelMonitoringObjectiveConfig.TrainingDataset.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingDataset.Builder
Overrides