GoogleCloudAiplatformV1BatchPredictionJobInstanceConfig
import type { GoogleCloudAiplatformV1BatchPredictionJobInstanceConfig } from "https://googleapis.deno.dev/v1/aiplatform:v1.ts";
Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.
§Properties
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, BigQuery or TfRecord.
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, BigQuery or TfRecord.
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": }
, where 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": }`, where
is the
Base64-encoded string of the content of the file.
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.