Class BatchPredictionJob.InstanceConfig.Builder (3.23.0)

public static final class BatchPredictionJob.InstanceConfig.Builder extends GeneratedMessageV3.Builder<BatchPredictionJob.InstanceConfig.Builder> implements BatchPredictionJob.InstanceConfigOrBuilder

Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.

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

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > BatchPredictionJob.InstanceConfig.Builder

Implements

BatchPredictionJob.InstanceConfigOrBuilder

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)

GeneratedMessageV3.Builder.internalGetMutableMapField(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

addAllExcludedFields(Iterable<String> values)

public BatchPredictionJob.InstanceConfig.Builder addAllExcludedFields(Iterable<String> values)

Fields that will be excluded in the prediction instance that is sent to the Model.

Excluded will be attached to the batch prediction output if key_field is not specified.

When excluded_fields is populated, included_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string excluded_fields = 4;

Parameter
Name	Description
`values`	`Iterable<String>` The excludedFields to add.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

addAllIncludedFields(Iterable<String> values)

public BatchPredictionJob.InstanceConfig.Builder addAllIncludedFields(Iterable<String> values)

Fields that will be included in the prediction instance that is sent to the Model.

If instance_type is array, the order of field names in included_fields also determines the order of the values in the array.

When included_fields is populated, excluded_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string included_fields = 3;

Parameter
Name	Description
`values`	`Iterable<String>` The includedFields to add.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

addExcludedFields(String value)

public BatchPredictionJob.InstanceConfig.Builder addExcludedFields(String value)

Fields that will be excluded in the prediction instance that is sent to the Model.

Excluded will be attached to the batch prediction output if key_field is not specified.

When excluded_fields is populated, included_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string excluded_fields = 4;

Parameter
Name	Description
`value`	`String` The excludedFields to add.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

addExcludedFieldsBytes(ByteString value)

public BatchPredictionJob.InstanceConfig.Builder addExcludedFieldsBytes(ByteString value)

Fields that will be excluded in the prediction instance that is sent to the Model.

Excluded will be attached to the batch prediction output if key_field is not specified.

When excluded_fields is populated, included_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string excluded_fields = 4;

Parameter
Name	Description
`value`	`ByteString` The bytes of the excludedFields to add.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

addIncludedFields(String value)

public BatchPredictionJob.InstanceConfig.Builder addIncludedFields(String value)

Fields that will be included in the prediction instance that is sent to the Model.

If instance_type is array, the order of field names in included_fields also determines the order of the values in the array.

When included_fields is populated, excluded_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string included_fields = 3;

Parameter
Name	Description
`value`	`String` The includedFields to add.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

addIncludedFieldsBytes(ByteString value)

public BatchPredictionJob.InstanceConfig.Builder addIncludedFieldsBytes(ByteString value)

Fields that will be included in the prediction instance that is sent to the Model.

If instance_type is array, the order of field names in included_fields also determines the order of the values in the array.

When included_fields is populated, excluded_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string included_fields = 3;

Parameter
Name	Description
`value`	`ByteString` The bytes of the includedFields to add.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public BatchPredictionJob.InstanceConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

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

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

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

build()

public BatchPredictionJob.InstanceConfig build()

Returns
Type	Description
`BatchPredictionJob.InstanceConfig`

buildPartial()

public BatchPredictionJob.InstanceConfig buildPartial()

Returns
Type	Description
`BatchPredictionJob.InstanceConfig`

clear()

public BatchPredictionJob.InstanceConfig.Builder clear()

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearExcludedFields()

public BatchPredictionJob.InstanceConfig.Builder clearExcludedFields()

Fields that will be excluded in the prediction instance that is sent to the Model.

Excluded will be attached to the batch prediction output if key_field is not specified.

When excluded_fields is populated, included_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string excluded_fields = 4;

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public BatchPredictionJob.InstanceConfig.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
`field`	`FieldDescriptor`

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

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

clearIncludedFields()

public BatchPredictionJob.InstanceConfig.Builder clearIncludedFields()

Fields that will be included in the prediction instance that is sent to the Model.

If instance_type is array, the order of field names in included_fields also determines the order of the values in the array.

When included_fields is populated, excluded_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string included_fields = 3;

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

clearInstanceType()

public BatchPredictionJob.InstanceConfig.Builder clearInstanceType()

The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format.

Supported values are:

object: Each input is converted to JSON object format.
- For bigquery, each row is converted to an object.
- For jsonl, each line of the JSONL input must be an object.
- Does not apply to csv, file-list, tf-record, or tf-record-gzip.
array: Each input is converted to JSON array format.
- For bigquery, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders.
- For jsonl, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders.
- Does not apply to csv, file-list, tf-record, or tf-record-gzip.
If not specified, Vertex AI converts the batch prediction input as follows:
- For bigquery and csv, the behavior is the same as array. The order of columns is the same as defined in the file or table, unless included_fields is populated.
- For jsonl, the prediction instance format is determined by each line of the input.
- For tf-record/tf-record-gzip, each record will be converted to an object in the format of {"b64": <value>}, where <value> is the Base64-encoded string of the content of the record.
- For file-list, each file in the list will be converted to an object in the format of {"b64": <value>}, where <value> is the Base64-encoded string of the content of the file.

string instance_type = 1;

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

clearKeyField()

public BatchPredictionJob.InstanceConfig.Builder clearKeyField()

The name of the field that is considered as a key.

The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named key in the output:

For jsonl output format, the output will have a key field instead of the instance field.
For csv/bigquery output format, the output will have have a key column instead of the instance feature columns.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

string key_field = 2;

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public BatchPredictionJob.InstanceConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
`oneof`	`OneofDescriptor`

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

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

clone()

public BatchPredictionJob.InstanceConfig.Builder clone()

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getDefaultInstanceForType()

public BatchPredictionJob.InstanceConfig getDefaultInstanceForType()

Returns
Type	Description
`BatchPredictionJob.InstanceConfig`

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
`Descriptor`

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getExcludedFields(int index)

public String getExcludedFields(int index)

Fields that will be excluded in the prediction instance that is sent to the Model.

Excluded will be attached to the batch prediction output if key_field is not specified.

When excluded_fields is populated, included_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string excluded_fields = 4;

Parameter
Name	Description
`index`	`int` The index of the element to return.

Returns
Type	Description
`String`	The excludedFields at the given index.

getExcludedFieldsBytes(int index)

public ByteString getExcludedFieldsBytes(int index)

Fields that will be excluded in the prediction instance that is sent to the Model.

Excluded will be attached to the batch prediction output if key_field is not specified.

When excluded_fields is populated, included_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string excluded_fields = 4;

Parameter
Name	Description
`index`	`int` The index of the value to return.

Returns
Type	Description
`ByteString`	The bytes of the excludedFields at the given index.

getExcludedFieldsCount()

public int getExcludedFieldsCount()

Fields that will be excluded in the prediction instance that is sent to the Model.

Excluded will be attached to the batch prediction output if key_field is not specified.

When excluded_fields is populated, included_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string excluded_fields = 4;

Returns
Type	Description
`int`	The count of excludedFields.

getExcludedFieldsList()

public ProtocolStringList getExcludedFieldsList()

Fields that will be excluded in the prediction instance that is sent to the Model.

Excluded will be attached to the batch prediction output if key_field is not specified.

When excluded_fields is populated, included_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string excluded_fields = 4;

Returns
Type	Description
`ProtocolStringList`	A list containing the excludedFields.

getIncludedFields(int index)

public String getIncludedFields(int index)

Fields that will be included in the prediction instance that is sent to the Model.

If instance_type is array, the order of field names in included_fields also determines the order of the values in the array.

When included_fields is populated, excluded_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string included_fields = 3;

Parameter
Name	Description
`index`	`int` The index of the element to return.

Returns
Type	Description
`String`	The includedFields at the given index.

getIncludedFieldsBytes(int index)

public ByteString getIncludedFieldsBytes(int index)

Fields that will be included in the prediction instance that is sent to the Model.

If instance_type is array, the order of field names in included_fields also determines the order of the values in the array.

When included_fields is populated, excluded_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string included_fields = 3;

Parameter
Name	Description
`index`	`int` The index of the value to return.

Returns
Type	Description
`ByteString`	The bytes of the includedFields at the given index.

getIncludedFieldsCount()

public int getIncludedFieldsCount()

Fields that will be included in the prediction instance that is sent to the Model.

If instance_type is array, the order of field names in included_fields also determines the order of the values in the array.

When included_fields is populated, excluded_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string included_fields = 3;

Returns
Type	Description
`int`	The count of includedFields.

getIncludedFieldsList()

public ProtocolStringList getIncludedFieldsList()

Fields that will be included in the prediction instance that is sent to the Model.

If instance_type is array, the order of field names in included_fields also determines the order of the values in the array.

When included_fields is populated, excluded_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string included_fields = 3;

Returns
Type	Description
`ProtocolStringList`	A list containing the includedFields.

getInstanceType()

public String getInstanceType()

The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format.

Supported values are:

object: Each input is converted to JSON object format.
- For bigquery, each row is converted to an object.
- For jsonl, each line of the JSONL input must be an object.
- Does not apply to csv, file-list, tf-record, or tf-record-gzip.
array: Each input is converted to JSON array format.
- For bigquery, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders.
- For jsonl, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders.
- Does not apply to csv, file-list, tf-record, or tf-record-gzip.
If not specified, Vertex AI converts the batch prediction input as follows:
- For bigquery and csv, the behavior is the same as array. The order of columns is the same as defined in the file or table, unless included_fields is populated.
- For jsonl, the prediction instance format is determined by each line of the input.
- For tf-record/tf-record-gzip, each record will be converted to an object in the format of {"b64": <value>}, where <value> is the Base64-encoded string of the content of the record.
- For file-list, each file in the list will be converted to an object in the format of {"b64": <value>}, where <value> is the Base64-encoded string of the content of the file.

string instance_type = 1;

Returns
Type	Description
`String`	The instanceType.

getInstanceTypeBytes()

public ByteString getInstanceTypeBytes()

The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format.

Supported values are:

object: Each input is converted to JSON object format.
- For bigquery, each row is converted to an object.
- For jsonl, each line of the JSONL input must be an object.
- Does not apply to csv, file-list, tf-record, or tf-record-gzip.
array: Each input is converted to JSON array format.
- For bigquery, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders.
- For jsonl, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders.
- Does not apply to csv, file-list, tf-record, or tf-record-gzip.
If not specified, Vertex AI converts the batch prediction input as follows:
- For bigquery and csv, the behavior is the same as array. The order of columns is the same as defined in the file or table, unless included_fields is populated.
- For jsonl, the prediction instance format is determined by each line of the input.
- For tf-record/tf-record-gzip, each record will be converted to an object in the format of {"b64": <value>}, where <value> is the Base64-encoded string of the content of the record.
- For file-list, each file in the list will be converted to an object in the format of {"b64": <value>}, where <value> is the Base64-encoded string of the content of the file.

string instance_type = 1;

Returns
Type	Description
`ByteString`	The bytes for instanceType.

getKeyField()

public String getKeyField()

The name of the field that is considered as a key.

For jsonl output format, the output will have a key field instead of the instance field.
For csv/bigquery output format, the output will have have a key column instead of the instance feature columns.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

string key_field = 2;

Returns
Type	Description
`String`	The keyField.

getKeyFieldBytes()

public ByteString getKeyFieldBytes()

The name of the field that is considered as a key.

For jsonl output format, the output will have a key field instead of the instance field.
For csv/bigquery output format, the output will have have a key column instead of the instance feature columns.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

string key_field = 2;

Returns
Type	Description
`ByteString`	The bytes for keyField.

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()

mergeFrom(BatchPredictionJob.InstanceConfig other)

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

Parameter
Name	Description
`other`	`BatchPredictionJob.InstanceConfig`

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

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

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

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

Exceptions
Type	Description
`IOException`

mergeFrom(Message other)

public BatchPredictionJob.InstanceConfig.Builder mergeFrom(Message other)

Parameter
Name	Description
`other`	`Message`

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

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

mergeUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictionJob.InstanceConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
`unknownFields`	`UnknownFieldSet`

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

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

setExcludedFields(int index, String value)

public BatchPredictionJob.InstanceConfig.Builder setExcludedFields(int index, String value)

Fields that will be excluded in the prediction instance that is sent to the Model.

Excluded will be attached to the batch prediction output if key_field is not specified.

When excluded_fields is populated, included_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string excluded_fields = 4;

Parameters
Name	Description
`index`	`int` The index to set the value at.
`value`	`String` The excludedFields to set.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

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

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

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

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

setIncludedFields(int index, String value)

public BatchPredictionJob.InstanceConfig.Builder setIncludedFields(int index, String value)

Fields that will be included in the prediction instance that is sent to the Model.

If instance_type is array, the order of field names in included_fields also determines the order of the values in the array.

When included_fields is populated, excluded_fields must be empty.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

repeated string included_fields = 3;

Parameters
Name	Description
`index`	`int` The index to set the value at.
`value`	`String` The includedFields to set.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

setInstanceType(String value)

public BatchPredictionJob.InstanceConfig.Builder setInstanceType(String value)

The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format.

Supported values are:

object: Each input is converted to JSON object format.
- For bigquery, each row is converted to an object.
- For jsonl, each line of the JSONL input must be an object.
- Does not apply to csv, file-list, tf-record, or tf-record-gzip.
array: Each input is converted to JSON array format.
- For bigquery, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders.
- For jsonl, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders.
- Does not apply to csv, file-list, tf-record, or tf-record-gzip.
If not specified, Vertex AI converts the batch prediction input as follows:
- For bigquery and csv, the behavior is the same as array. The order of columns is the same as defined in the file or table, unless included_fields is populated.
- For jsonl, the prediction instance format is determined by each line of the input.
- For tf-record/tf-record-gzip, each record will be converted to an object in the format of {"b64": <value>}, where <value> is the Base64-encoded string of the content of the record.
- For file-list, each file in the list will be converted to an object in the format of {"b64": <value>}, where <value> is the Base64-encoded string of the content of the file.

string instance_type = 1;

Parameter
Name	Description
`value`	`String` The instanceType to set.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

setInstanceTypeBytes(ByteString value)

public BatchPredictionJob.InstanceConfig.Builder setInstanceTypeBytes(ByteString value)

The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format.

Supported values are:

object: Each input is converted to JSON object format.
- For bigquery, each row is converted to an object.
- For jsonl, each line of the JSONL input must be an object.
- Does not apply to csv, file-list, tf-record, or tf-record-gzip.
array: Each input is converted to JSON array format.
- For bigquery, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders.
- For jsonl, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders.
- Does not apply to csv, file-list, tf-record, or tf-record-gzip.
If not specified, Vertex AI converts the batch prediction input as follows:
- For bigquery and csv, the behavior is the same as array. The order of columns is the same as defined in the file or table, unless included_fields is populated.
- For jsonl, the prediction instance format is determined by each line of the input.
- For tf-record/tf-record-gzip, each record will be converted to an object in the format of {"b64": <value>}, where <value> is the Base64-encoded string of the content of the record.
- For file-list, each file in the list will be converted to an object in the format of {"b64": <value>}, where <value> is the Base64-encoded string of the content of the file.

string instance_type = 1;

Parameter
Name	Description
`value`	`ByteString` The bytes for instanceType to set.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

setKeyField(String value)

public BatchPredictionJob.InstanceConfig.Builder setKeyField(String value)

The name of the field that is considered as a key.

For jsonl output format, the output will have a key field instead of the instance field.
For csv/bigquery output format, the output will have have a key column instead of the instance feature columns.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

string key_field = 2;

Parameter
Name	Description
`value`	`String` The keyField to set.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

setKeyFieldBytes(ByteString value)

public BatchPredictionJob.InstanceConfig.Builder setKeyFieldBytes(ByteString value)

The name of the field that is considered as a key.

For jsonl output format, the output will have a key field instead of the instance field.
For csv/bigquery output format, the output will have have a key column instead of the instance feature columns.

The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

string key_field = 2;

Parameter
Name	Description
`value`	`ByteString` The bytes for keyField to set.

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`	This builder for chaining.

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

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

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

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

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

setUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictionJob.InstanceConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
`unknownFields`	`UnknownFieldSet`

Returns
Type	Description
`BatchPredictionJob.InstanceConfig.Builder`

Overrides

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