Class BatchPredictionJob.OutputConfig.Builder (3.84.0)

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public static final class BatchPredictionJob.OutputConfig.Builder extends GeneratedMessage.Builder<BatchPredictionJob.OutputConfig.Builder> implements BatchPredictionJob.OutputConfigOrBuilder

Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.

Protobuf type google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig

Inheritance

java.lang.Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessage.Builder > BatchPredictionJob.OutputConfig.Builder

Implements

BatchPredictionJob.OutputConfigOrBuilder

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)

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

GeneratedMessage.Builder.clear()

GeneratedMessage.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessage.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessage.Builder.clone()

GeneratedMessage.Builder.getAllFields()

GeneratedMessage.Builder.getDescriptorForType()

GeneratedMessage.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessage.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessage.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessage.Builder.getParentForChildren()

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

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

GeneratedMessage.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessage.Builder.getUnknownFieldSetBuilder()

GeneratedMessage.Builder.getUnknownFields()

GeneratedMessage.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessage.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessage.Builder.internalGetFieldAccessorTable()

GeneratedMessage.Builder.internalGetMapField(int)

com.google.protobuf.GeneratedMessage.Builder.internalGetMapFieldReflection(int)

GeneratedMessage.Builder.internalGetMutableMapField(int)

com.google.protobuf.GeneratedMessage.Builder.internalGetMutableMapFieldReflection(int)

GeneratedMessage.Builder.isClean()

GeneratedMessage.Builder.isInitialized()

GeneratedMessage.Builder.markClean()

GeneratedMessage.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessage.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessage.Builder.mergeUnknownVarintField(int,int)

GeneratedMessage.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessage.Builder.onBuilt()

GeneratedMessage.Builder.onChanged()

com.google.protobuf.GeneratedMessage.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

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

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

com.google.protobuf.GeneratedMessage.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessage.Builder.setUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessage.Builder.setUnknownFieldsProto3(com.google.protobuf.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

build()

public BatchPredictionJob.OutputConfig build()

Returns
Type	Description
BatchPredictionJob.OutputConfig

buildPartial()

public BatchPredictionJob.OutputConfig buildPartial()

Returns
Type	Description
BatchPredictionJob.OutputConfig

clear()

public BatchPredictionJob.OutputConfig.Builder clear()

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

Overrides

GeneratedMessage.Builder<BuilderType>.clear()

clearBigqueryDestination()

public BatchPredictionJob.OutputConfig.Builder clearBigqueryDestination()

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where <model-display-name> is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, predictions, and errors. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

clearDestination()

public BatchPredictionJob.OutputConfig.Builder clearDestination()

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

clearGcsDestination()

public BatchPredictionJob.OutputConfig.Builder clearGcsDestination()

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

clearPredictionsFormat()

public BatchPredictionJob.OutputConfig.Builder clearPredictionsFormat()

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder	This builder for chaining.

getBigqueryDestination()

public BigQueryDestination getBigqueryDestination()

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where <model-display-name> is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, predictions, and errors. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

Returns
Type	Description
BigQueryDestination	The bigqueryDestination.

getBigqueryDestinationBuilder()

public BigQueryDestination.Builder getBigqueryDestinationBuilder()

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where <model-display-name> is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, predictions, and errors. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

Returns
Type	Description
BigQueryDestination.Builder

getBigqueryDestinationOrBuilder()

public BigQueryDestinationOrBuilder getBigqueryDestinationOrBuilder()

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where <model-display-name> is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, predictions, and errors. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

Returns
Type	Description
BigQueryDestinationOrBuilder

getDefaultInstanceForType()

public BatchPredictionJob.OutputConfig getDefaultInstanceForType()

Returns
Type	Description
BatchPredictionJob.OutputConfig

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
Descriptor

Overrides

GeneratedMessage.Builder<BuilderType>.getDescriptorForType()

getDestinationCase()

public BatchPredictionJob.OutputConfig.DestinationCase getDestinationCase()

Returns
Type	Description
BatchPredictionJob.OutputConfig.DestinationCase

getGcsDestination()

public GcsDestination getGcsDestination()

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

Returns
Type	Description
GcsDestination	The gcsDestination.

getGcsDestinationBuilder()

public GcsDestination.Builder getGcsDestinationBuilder()

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

Returns
Type	Description
GcsDestination.Builder

getGcsDestinationOrBuilder()

public GcsDestinationOrBuilder getGcsDestinationOrBuilder()

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

Returns
Type	Description
GcsDestinationOrBuilder

getPredictionsFormat()

public String getPredictionsFormat()

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
String	The predictionsFormat.

getPredictionsFormatBytes()

public ByteString getPredictionsFormatBytes()

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ByteString	The bytes for predictionsFormat.

hasBigqueryDestination()

public boolean hasBigqueryDestination()

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where <model-display-name> is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, predictions, and errors. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

Returns
Type	Description
boolean	Whether the bigqueryDestination field is set.

hasGcsDestination()

public boolean hasGcsDestination()

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

Returns
Type	Description
boolean	Whether the gcsDestination field is set.

internalGetFieldAccessorTable()

protected GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
FieldAccessorTable

Overrides

GeneratedMessage.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
boolean

Overrides

GeneratedMessage.Builder<BuilderType>.isInitialized()

mergeBigqueryDestination(BigQueryDestination value)

public BatchPredictionJob.OutputConfig.Builder mergeBigqueryDestination(BigQueryDestination value)

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where <model-display-name> is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, predictions, and errors. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

Parameter
Name	Description
value	BigQueryDestination

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

mergeFrom(BatchPredictionJob.OutputConfig other)

public BatchPredictionJob.OutputConfig.Builder mergeFrom(BatchPredictionJob.OutputConfig other)

Parameter
Name	Description
other	BatchPredictionJob.OutputConfig

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public BatchPredictionJob.OutputConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

Overrides

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

Exceptions
Type	Description
IOException

mergeFrom(Message other)

public BatchPredictionJob.OutputConfig.Builder mergeFrom(Message other)

Parameter
Name	Description
other	Message

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

Overrides

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

mergeGcsDestination(GcsDestination value)

public BatchPredictionJob.OutputConfig.Builder mergeGcsDestination(GcsDestination value)

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

Parameter
Name	Description
value	GcsDestination

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

setBigqueryDestination(BigQueryDestination value)

public BatchPredictionJob.OutputConfig.Builder setBigqueryDestination(BigQueryDestination value)

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where <model-display-name> is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, predictions, and errors. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

Parameter
Name	Description
value	BigQueryDestination

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

setBigqueryDestination(BigQueryDestination.Builder builderForValue)

public BatchPredictionJob.OutputConfig.Builder setBigqueryDestination(BigQueryDestination.Builder builderForValue)

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where <model-display-name> is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, predictions, and errors. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

Parameter
Name	Description
builderForValue	BigQueryDestination.Builder

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

setGcsDestination(GcsDestination value)

public BatchPredictionJob.OutputConfig.Builder setGcsDestination(GcsDestination value)

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

Parameter
Name	Description
value	GcsDestination

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

setGcsDestination(GcsDestination.Builder builderForValue)

public BatchPredictionJob.OutputConfig.Builder setGcsDestination(GcsDestination.Builder builderForValue)

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

Parameter
Name	Description
builderForValue	GcsDestination.Builder

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder

setPredictionsFormat(String value)

public BatchPredictionJob.OutputConfig.Builder setPredictionsFormat(String value)

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	String The predictionsFormat to set.

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder	This builder for chaining.

setPredictionsFormatBytes(ByteString value)

public BatchPredictionJob.OutputConfig.Builder setPredictionsFormatBytes(ByteString value)

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	ByteString The bytes for predictionsFormat to set.

Returns
Type	Description
BatchPredictionJob.OutputConfig.Builder	This builder for chaining.