Interface BatchPredictionJob.InstanceConfigOrBuilder (3.24.0)

public static interface BatchPredictionJob.InstanceConfigOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getExcludedFields(int index)

public abstract 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
NameDescription
indexint

The index of the element to return.

Returns
TypeDescription
String

The excludedFields at the given index.

getExcludedFieldsBytes(int index)

public abstract 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
NameDescription
indexint

The index of the value to return.

Returns
TypeDescription
ByteString

The bytes of the excludedFields at the given index.

getExcludedFieldsCount()

public abstract 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
TypeDescription
int

The count of excludedFields.

getExcludedFieldsList()

public abstract List<String> 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
TypeDescription
List<String>

A list containing the excludedFields.

getIncludedFields(int index)

public abstract 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
NameDescription
indexint

The index of the element to return.

Returns
TypeDescription
String

The includedFields at the given index.

getIncludedFieldsBytes(int index)

public abstract 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
NameDescription
indexint

The index of the value to return.

Returns
TypeDescription
ByteString

The bytes of the includedFields at the given index.

getIncludedFieldsCount()

public abstract 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
TypeDescription
int

The count of includedFields.

getIncludedFieldsList()

public abstract List<String> 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
TypeDescription
List<String>

A list containing the includedFields.

getInstanceType()

public abstract 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
TypeDescription
String

The instanceType.

getInstanceTypeBytes()

public abstract 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
TypeDescription
ByteString

The bytes for instanceType.

getKeyField()

public abstract 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 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
TypeDescription
String

The keyField.

getKeyFieldBytes()

public abstract 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 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
TypeDescription
ByteString

The bytes for keyField.