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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.v1beta1.ModelMonitoringObjectiveConfig.TrainingDataset
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ModelMonitoringObjectiveConfig.TrainingDataset.BuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Type | Description |
Descriptor |
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
build()
public ModelMonitoringObjectiveConfig.TrainingDataset build()
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset |
buildPartial()
public ModelMonitoringObjectiveConfig.TrainingDataset buildPartial()
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset |
clear()
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clear()
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
clearBigquerySource()
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearBigquerySource()
The BigQuery table of the unmanaged Dataset used to train this Model.
.google.cloud.aiplatform.v1beta1.BigQuerySource bigquery_source = 5;
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;
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder | This builder for chaining. |
clearDataSource()
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearDataSource()
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) = { ... }
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder | This builder for chaining. |
clearField(Descriptors.FieldDescriptor field)
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearField(Descriptors.FieldDescriptor field)
Name | Description |
field | FieldDescriptor |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
clearGcsSource()
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearGcsSource()
The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.
.google.cloud.aiplatform.v1beta1.GcsSource gcs_source = 4;
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.v1beta1.SamplingStrategy logging_sampling_strategy = 7;
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
clearOneof(Descriptors.OneofDescriptor oneof)
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Name | Description |
oneof | OneofDescriptor |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
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;
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder | This builder for chaining. |
clone()
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder clone()
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
getBigquerySource()
public BigQuerySource getBigquerySource()
The BigQuery table of the unmanaged Dataset used to train this Model.
.google.cloud.aiplatform.v1beta1.BigQuerySource bigquery_source = 5;
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.v1beta1.BigQuerySource bigquery_source = 5;
Type | Description |
BigQuerySource.Builder |
getBigquerySourceOrBuilder()
public BigQuerySourceOrBuilder getBigquerySourceOrBuilder()
The BigQuery table of the unmanaged Dataset used to train this Model.
.google.cloud.aiplatform.v1beta1.BigQuerySource bigquery_source = 5;
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;
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;
Type | Description |
ByteString | The bytes for dataFormat. |
getDataSourceCase()
public ModelMonitoringObjectiveConfig.TrainingDataset.DataSourceCase getDataSourceCase()
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) = { ... }
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) = { ... }
Type | Description |
ByteString | The bytes for dataset. |
getDefaultInstanceForType()
public ModelMonitoringObjectiveConfig.TrainingDataset getDefaultInstanceForType()
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Type | Description |
Descriptor |
getGcsSource()
public GcsSource getGcsSource()
The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.
.google.cloud.aiplatform.v1beta1.GcsSource gcs_source = 4;
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.v1beta1.GcsSource gcs_source = 4;
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.v1beta1.GcsSource gcs_source = 4;
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.v1beta1.SamplingStrategy logging_sampling_strategy = 7;
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.v1beta1.SamplingStrategy logging_sampling_strategy = 7;
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.v1beta1.SamplingStrategy logging_sampling_strategy = 7;
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;
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;
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.v1beta1.BigQuerySource bigquery_source = 5;
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) = { ... }
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.v1beta1.GcsSource gcs_source = 4;
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.v1beta1.SamplingStrategy logging_sampling_strategy = 7;
Type | Description |
boolean | Whether the loggingSamplingStrategy field is set. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Type | Description |
FieldAccessorTable |
isInitialized()
public final boolean isInitialized()
Type | Description |
boolean |
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.v1beta1.BigQuerySource bigquery_source = 5;
Name | Description |
value | BigQuerySource |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
mergeFrom(ModelMonitoringObjectiveConfig.TrainingDataset other)
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeFrom(ModelMonitoringObjectiveConfig.TrainingDataset other)
Name | Description |
other | ModelMonitoringObjectiveConfig.TrainingDataset |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
Type | Description |
IOException |
mergeFrom(Message other)
public ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeFrom(Message other)
Name | Description |
other | Message |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
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.v1beta1.GcsSource gcs_source = 4;
Name | Description |
value | GcsSource |
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.v1beta1.SamplingStrategy logging_sampling_strategy = 7;
Name | Description |
value | SamplingStrategy |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final ModelMonitoringObjectiveConfig.TrainingDataset.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
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.v1beta1.BigQuerySource bigquery_source = 5;
Name | Description |
value | BigQuerySource |
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.v1beta1.BigQuerySource bigquery_source = 5;
Name | Description |
builderForValue | BigQuerySource.Builder |
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;
Name | Description |
value | String The dataFormat to set. |
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;
Name | Description |
value | ByteString The bytes for dataFormat to set. |
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) = { ... }
Name | Description |
value | String The dataset to set. |
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) = { ... }
Name | Description |
value | ByteString The bytes for dataset to set. |
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)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
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.v1beta1.GcsSource gcs_source = 4;
Name | Description |
value | GcsSource |
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.v1beta1.GcsSource gcs_source = 4;
Name | Description |
builderForValue | GcsSource.Builder |
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.v1beta1.SamplingStrategy logging_sampling_strategy = 7;
Name | Description |
value | SamplingStrategy |
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.v1beta1.SamplingStrategy logging_sampling_strategy = 7;
Name | Description |
builderForValue | SamplingStrategy.Builder |
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)
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |
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;
Name | Description |
value | String The targetField to set. |
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;
Name | Description |
value | ByteString The bytes for targetField to set. |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder | This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final ModelMonitoringObjectiveConfig.TrainingDataset.Builder setUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
ModelMonitoringObjectiveConfig.TrainingDataset.Builder |