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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.BuilderImplements
BatchPredictionJob.InstanceConfigOrBuilderStatic 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 |
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 |
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 |
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
, ortf-record-gzip
.
- For
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
, ortf-record-gzip
. If not specified, Vertex AI converts the batch prediction input as follows:- For
bigquery
andcsv
, the behavior is the same asarray
. 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.
- For
- For
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 akey
field instead of theinstance
field. - For
csv
/bigquery
output format, the output will have have akey
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 |
clone()
public BatchPredictionJob.InstanceConfig.Builder clone()
Returns | |
---|---|
Type | Description |
BatchPredictionJob.InstanceConfig.Builder |
getDefaultInstanceForType()
public BatchPredictionJob.InstanceConfig getDefaultInstanceForType()
Returns | |
---|---|
Type | Description |
BatchPredictionJob.InstanceConfig |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Returns | |
---|---|
Type | Description |
Descriptor |
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
, ortf-record-gzip
.
- For
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
, ortf-record-gzip
. If not specified, Vertex AI converts the batch prediction input as follows:- For
bigquery
andcsv
, the behavior is the same asarray
. 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.
- For
- For
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
, ortf-record-gzip
.
- For
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
, ortf-record-gzip
. If not specified, Vertex AI converts the batch prediction input as follows:- For
bigquery
andcsv
, the behavior is the same asarray
. 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.
- For
- For
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.
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 akey
field instead of theinstance
field. - For
csv
/bigquery
output format, the output will have have akey
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.
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 akey
field instead of theinstance
field. - For
csv
/bigquery
output format, the output will have have akey
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 |
isInitialized()
public final boolean isInitialized()
Returns | |
---|---|
Type | Description |
boolean |
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 |
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 |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final BatchPredictionJob.InstanceConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter | |
---|---|
Name | Description |
unknownFields | UnknownFieldSet |
Returns | |
---|---|
Type | Description |
BatchPredictionJob.InstanceConfig.Builder |
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 |
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
, ortf-record-gzip
.
- For
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
, ortf-record-gzip
. If not specified, Vertex AI converts the batch prediction input as follows:- For
bigquery
andcsv
, the behavior is the same asarray
. 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.
- For
- For
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
, ortf-record-gzip
.
- For
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
, ortf-record-gzip
. If not specified, Vertex AI converts the batch prediction input as follows:- For
bigquery
andcsv
, the behavior is the same asarray
. 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.
- For
- For
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.
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 akey
field instead of theinstance
field. - For
csv
/bigquery
output format, the output will have have akey
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.
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 akey
field instead of theinstance
field. - For
csv
/bigquery
output format, the output will have have akey
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 |
setUnknownFields(UnknownFieldSet unknownFields)
public final BatchPredictionJob.InstanceConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter | |
---|---|
Name | Description |
unknownFields | UnknownFieldSet |
Returns | |
---|---|
Type | Description |
BatchPredictionJob.InstanceConfig.Builder |