Class BatchPredictOutputConfig.Builder (2.46.0)

public static final class BatchPredictOutputConfig.Builder extends GeneratedMessageV3.Builder<BatchPredictOutputConfig.Builder> implements BatchPredictOutputConfigOrBuilder

Output configuration for BatchPredict Action.

As destination the

gcs_destination must be set unless specified otherwise for a domain. If gcs_destination is set then in the given directory a new directory is created. Its name will be "prediction-<model-display-name>-<timestamp-of-prediction-call>", where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. The contents of it depends on the ML problem the predictions are made for. * For Image Classification: In the created directory files image_classification_1.jsonl, image_classification_2.jsonl,...,image_classification_N.jsonl will be created, where N may be 1, and depends on the total number of the successfully predicted images and annotations. A single image will be listed only once with all its annotations, and its annotations will never be split across files. Each .JSONL file will contain, per line, a JSON representation of a proto that wraps image's "ID" : "<id_value>" followed by a list of zero or more AnnotationPayload protos (called annotations), which have classification detail populated. If prediction for any image failed (partially or completely), then an additional errors_1.jsonl, errors_2.jsonl,..., errors_N.jsonl files will be created (N depends on total number of failed predictions). These files will have a JSON representation of a proto that wraps the same "ID" : "<id_value>" but here followed by exactly one google.rpc.Status containing only code and messagefields. * For Image Object Detection: In the created directory files image_object_detection_1.jsonl, image_object_detection_2.jsonl,...,image_object_detection_N.jsonl will be created, where N may be 1, and depends on the total number of the successfully predicted images and annotations. Each .JSONL file will contain, per line, a JSON representation of a proto that wraps image's "ID" : "<id_value>" followed by a list of zero or more AnnotationPayload protos (called annotations), which have image_object_detection detail populated. A single image will be listed only once with all its annotations, and its annotations will never be split across files. If prediction for any image failed (partially or completely), then additional errors_1.jsonl, errors_2.jsonl,..., errors_N.jsonl files will be created (N depends on total number of failed predictions). These files will have a JSON representation of a proto that wraps the same "ID" : "<id_value>" but here followed by exactly one google.rpc.Status containing only code and messagefields. * For Video Classification: In the created directory a video_classification.csv file, and a .JSON file per each video classification requested in the input (i.e. each line in given CSV(s)), will be created. The format of video_classification.csv is: GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END,JSON_FILE_NAME,STATUS where: GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END = matches 1 to 1 the prediction input lines (i.e. video_classification.csv has precisely the same number of lines as the prediction input had.) JSON_FILE_NAME = Name of .JSON file in the output directory, which contains prediction responses for the video time segment. STATUS = "OK" if prediction completed successfully, or an error code with message otherwise. If STATUS is not "OK" then the .JSON file for that line may not exist or be empty. Each .JSON file, assuming STATUS is "OK", will contain a list of AnnotationPayload protos in JSON format, which are the predictions for the video time segment the file is assigned to in the video_classification.csv. All AnnotationPayload protos will have video_classification field set, and will be sorted by video_classification.type field (note that the returned types are governed by classifaction_types parameter in [PredictService.BatchPredictRequest.params][]). * For Video Object Tracking: In the created directory a video_object_tracking.csv file will be created, and multiple files video_object_trackinng_1.json, video_object_trackinng_2.json,..., video_object_trackinng_N.json, where N is the number of requests in the input (i.e. the number of lines in given CSV(s)). The format of video_object_tracking.csv is: GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END,JSON_FILE_NAME,STATUS where: GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END = matches 1 to 1 the prediction input lines (i.e. video_object_tracking.csv has precisely the same number of lines as the prediction input had.) JSON_FILE_NAME = Name of .JSON file in the output directory, which contains prediction responses for the video time segment. STATUS = "OK" if prediction completed successfully, or an error code with message otherwise. If STATUS is not "OK" then the .JSON file for that line may not exist or be empty. Each .JSON file, assuming STATUS is "OK", will contain a list of AnnotationPayload protos in JSON format, which are the predictions for each frame of the video time segment the file is assigned to in video_object_tracking.csv. All AnnotationPayload protos will have video_object_tracking field set. * For Text Classification: In the created directory files text_classification_1.jsonl, text_classification_2.jsonl,...,text_classification_N.jsonl will be created, where N may be 1, and depends on the total number of inputs and annotations found. Each .JSONL file will contain, per line, a JSON representation of a proto that wraps input text snippet or input text file and a list of zero or more AnnotationPayload protos (called annotations), which have classification detail populated. A single text snippet or file will be listed only once with all its annotations, and its annotations will never be split across files. If prediction for any text snippet or file failed (partially or completely), then additional errors_1.jsonl, errors_2.jsonl,..., errors_N.jsonl files will be created (N depends on total number of failed predictions). These files will have a JSON representation of a proto that wraps input text snippet or input text file followed by exactly one google.rpc.Status containing only code and message. * For Text Sentiment: In the created directory files text_sentiment_1.jsonl, text_sentiment_2.jsonl,...,text_sentiment_N.jsonl will be created, where N may be 1, and depends on the total number of inputs and annotations found. Each .JSONL file will contain, per line, a JSON representation of a proto that wraps input text snippet or input text file and a list of zero or more AnnotationPayload protos (called annotations), which have text_sentiment detail populated. A single text snippet or file will be listed only once with all its annotations, and its annotations will never be split across files. If prediction for any text snippet or file failed (partially or completely), then additional errors_1.jsonl, errors_2.jsonl,..., errors_N.jsonl files will be created (N depends on total number of failed predictions). These files will have a JSON representation of a proto that wraps input text snippet or input text file followed by exactly one google.rpc.Status containing only code and message. * For Text Extraction: In the created directory files text_extraction_1.jsonl, text_extraction_2.jsonl,...,text_extraction_N.jsonl will be created, where N may be 1, and depends on the total number of inputs and annotations found. The contents of these .JSONL file(s) depend on whether the input used inline text, or documents. If input was inline, then each .JSONL file will contain, per line, a JSON representation of a proto that wraps given in request text snippet's "id" (if specified), followed by input text snippet, and a list of zero or more AnnotationPayload protos (called annotations), which have text_extraction detail populated. A single text snippet will be listed only once with all its annotations, and its annotations will never be split across files. If input used documents, then each .JSONL file will contain, per line, a JSON representation of a proto that wraps given in request document proto, followed by its OCR-ed representation in the form of a text snippet, finally followed by a list of zero or more AnnotationPayload protos (called annotations), which have text_extraction detail populated and refer, via their indices, to the OCR-ed text snippet. A single document (and its text snippet) will be listed only once with all its annotations, and its annotations will never be split across files. If prediction for any text snippet failed (partially or completely), then additional errors_1.jsonl, errors_2.jsonl,..., errors_N.jsonl files will be created (N depends on total number of failed predictions). These files will have a JSON representation of a proto that wraps either the "id" : "<id_value>" (in case of inline) or the document proto (in case of document) but here followed by exactly one google.rpc.Status containing only code and message. * For Tables: Output depends on whether gcs_destination or bigquery_destination is set (either is allowed). GCS case: In the created directory files tables_1.csv, tables_2.csv,..., tables_N.csv will be created, where N may be 1, and depends on the total number of the successfully predicted rows. For all CLASSIFICATION prediction_type-s: Each .csv file will contain a header, listing all columns' display_name-s given on input followed by M target column names in the format of "<target_column_specs display_name><target value>_score" where M is the number of distinct target values, i.e. number of distinct values in the target column of the table used to train the model. Subsequent lines will contain the respective values of successfully predicted rows, with the last, i.e. the target, columns having the corresponding prediction scores. For REGRESSION and FORECASTING prediction_type-s: Each .csv file will contain a header, listing all columns' display_name-s given on input followed by the predicted target column with name in the format of "predicted<target_column_specs display_name>" Subsequent lines will contain the respective values of successfully predicted rows, with the last, i.e. the target, column having the predicted target value. If prediction for any rows failed, then an additional errors_1.csv, errors_2.csv,..., errors_N.csv will be created (N depends on total number of failed rows). These files will have analogous format as tables_*.csv, but always with a single target column having google.rpc.Status represented as a JSON string, and containing only code and message. BigQuery case: bigquery_destination pointing to a BigQuery project must be set. In the given project a new dataset will be created with name prediction_<model-display-name><timestamp-of-prediction-call> where <model-display-name> will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores), and timestamp will be in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, predictions, and errors. The predictions table's column names will be the input columns' display_name-s followed by the target column with name in the format of "predicted<target_column_specs display_name>" The input feature columns will contain the respective values of successfully predicted rows, with the target column having an ARRAY of AnnotationPayloads, represented as STRUCT-s, containing TablesAnnotation. The errors table contains rows for which the prediction has failed, it has analogous input columns while the target column name is in the format of "errors_<target_column_specs

display_name>", and as a value has

google.rpc.Status represented as a STRUCT, and containing only code and message.

Protobuf type google.cloud.automl.v1beta1.BatchPredictOutputConfig

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > BatchPredictOutputConfig.Builder

Implements

BatchPredictOutputConfigOrBuilder

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)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

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

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

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

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 BatchPredictOutputConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
`field`	`FieldDescriptor`
`value`	`Object`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

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

build()

public BatchPredictOutputConfig build()

Returns
Type	Description
`BatchPredictOutputConfig`

buildPartial()

public BatchPredictOutputConfig buildPartial()

Returns
Type	Description
`BatchPredictOutputConfig`

clear()

public BatchPredictOutputConfig.Builder clear()

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearBigqueryDestination()

public BatchPredictOutputConfig.Builder clearBigqueryDestination()

The BigQuery location where the output is to be written to.

.google.cloud.automl.v1beta1.BigQueryDestination bigquery_destination = 2;

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

clearDestination()

public BatchPredictOutputConfig.Builder clearDestination()

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

clearField(Descriptors.FieldDescriptor field)

public BatchPredictOutputConfig.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
`field`	`FieldDescriptor`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

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

clearGcsDestination()

public BatchPredictOutputConfig.Builder clearGcsDestination()

The Google Cloud Storage location of the directory where the output is to be written to.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

clearOneof(Descriptors.OneofDescriptor oneof)

public BatchPredictOutputConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
`oneof`	`OneofDescriptor`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

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

clone()

public BatchPredictOutputConfig.Builder clone()

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getBigqueryDestination()

public BigQueryDestination getBigqueryDestination()

The BigQuery location where the output is to be written to.

.google.cloud.automl.v1beta1.BigQueryDestination bigquery_destination = 2;

Returns
Type	Description
`BigQueryDestination`	The bigqueryDestination.

getBigqueryDestinationBuilder()

public BigQueryDestination.Builder getBigqueryDestinationBuilder()

The BigQuery location where the output is to be written to.

.google.cloud.automl.v1beta1.BigQueryDestination bigquery_destination = 2;

Returns
Type	Description
`BigQueryDestination.Builder`

getBigqueryDestinationOrBuilder()

public BigQueryDestinationOrBuilder getBigqueryDestinationOrBuilder()

The BigQuery location where the output is to be written to.

.google.cloud.automl.v1beta1.BigQueryDestination bigquery_destination = 2;

Returns
Type	Description
`BigQueryDestinationOrBuilder`

getDefaultInstanceForType()

public BatchPredictOutputConfig getDefaultInstanceForType()

Returns
Type	Description
`BatchPredictOutputConfig`

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
`Descriptor`

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getDestinationCase()

public BatchPredictOutputConfig.DestinationCase getDestinationCase()

Returns
Type	Description
`BatchPredictOutputConfig.DestinationCase`

getGcsDestination()

public GcsDestination getGcsDestination()

The Google Cloud Storage location of the directory where the output is to be written to.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Returns
Type	Description
`GcsDestination`	The gcsDestination.

getGcsDestinationBuilder()

public GcsDestination.Builder getGcsDestinationBuilder()

The Google Cloud Storage location of the directory where the output is to be written to.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Returns
Type	Description
`GcsDestination.Builder`

getGcsDestinationOrBuilder()

public GcsDestinationOrBuilder getGcsDestinationOrBuilder()

The Google Cloud Storage location of the directory where the output is to be written to.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Returns
Type	Description
`GcsDestinationOrBuilder`

hasBigqueryDestination()

public boolean hasBigqueryDestination()

The BigQuery location where the output is to be written to.

.google.cloud.automl.v1beta1.BigQueryDestination bigquery_destination = 2;

Returns
Type	Description
`boolean`	Whether the bigqueryDestination field is set.

hasGcsDestination()

public boolean hasGcsDestination()

The Google Cloud Storage location of the directory where the output is to be written to.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Returns
Type	Description
`boolean`	Whether the gcsDestination 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()

mergeBigqueryDestination(BigQueryDestination value)

public BatchPredictOutputConfig.Builder mergeBigqueryDestination(BigQueryDestination value)

The BigQuery location where the output is to be written to.

.google.cloud.automl.v1beta1.BigQueryDestination bigquery_destination = 2;

Parameter
Name	Description
`value`	`BigQueryDestination`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

mergeFrom(BatchPredictOutputConfig other)

public BatchPredictOutputConfig.Builder mergeFrom(BatchPredictOutputConfig other)

Parameter
Name	Description
`other`	`BatchPredictOutputConfig`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public BatchPredictOutputConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
`input`	`CodedInputStream`
`extensionRegistry`	`ExtensionRegistryLite`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

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

Exceptions
Type	Description
`IOException`

mergeFrom(Message other)

public BatchPredictOutputConfig.Builder mergeFrom(Message other)

Parameter
Name	Description
`other`	`Message`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

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

mergeGcsDestination(GcsDestination value)

public BatchPredictOutputConfig.Builder mergeGcsDestination(GcsDestination value)

The Google Cloud Storage location of the directory where the output is to be written to.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Parameter
Name	Description
`value`	`GcsDestination`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

mergeUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictOutputConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
`unknownFields`	`UnknownFieldSet`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

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

setBigqueryDestination(BigQueryDestination value)

public BatchPredictOutputConfig.Builder setBigqueryDestination(BigQueryDestination value)

The BigQuery location where the output is to be written to.

.google.cloud.automl.v1beta1.BigQueryDestination bigquery_destination = 2;

Parameter
Name	Description
`value`	`BigQueryDestination`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

setBigqueryDestination(BigQueryDestination.Builder builderForValue)

public BatchPredictOutputConfig.Builder setBigqueryDestination(BigQueryDestination.Builder builderForValue)

The BigQuery location where the output is to be written to.

.google.cloud.automl.v1beta1.BigQueryDestination bigquery_destination = 2;

Parameter
Name	Description
`builderForValue`	`BigQueryDestination.Builder`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

setField(Descriptors.FieldDescriptor field, Object value)

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

Parameters
Name	Description
`field`	`FieldDescriptor`
`value`	`Object`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

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

setGcsDestination(GcsDestination value)

public BatchPredictOutputConfig.Builder setGcsDestination(GcsDestination value)

The Google Cloud Storage location of the directory where the output is to be written to.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Parameter
Name	Description
`value`	`GcsDestination`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

setGcsDestination(GcsDestination.Builder builderForValue)

public BatchPredictOutputConfig.Builder setGcsDestination(GcsDestination.Builder builderForValue)

The Google Cloud Storage location of the directory where the output is to be written to.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Parameter
Name	Description
`builderForValue`	`GcsDestination.Builder`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

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

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

Parameters
Name	Description
`field`	`FieldDescriptor`
`index`	`int`
`value`	`Object`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

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

setUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictOutputConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
`unknownFields`	`UnknownFieldSet`

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

Overrides

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