Google Cloud Ai Platform V1 Client - Class OutputConfig (0.30.0)

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class OutputConfig.

Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.

Generated from protobuf message google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig

Namespace

Google \ Cloud \ AIPlatform \ V1 \ BatchPredictionJob

Methods

__construct

Constructor.

Parameters
NameDescription
data array

Optional. Data for populating the Message object.

↳ gcs_destination Google\Cloud\AIPlatform\V1\GcsDestination

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

↳ bigquery_destination Google\Cloud\AIPlatform\V1\BigQueryDestination

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where

↳ predictions_format string

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

getGcsDestination

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created.

Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

Returns
TypeDescription
Google\Cloud\AIPlatform\V1\GcsDestination|null

hasGcsDestination

setGcsDestination

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created.

Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

Parameter
NameDescription
var Google\Cloud\AIPlatform\V1\GcsDestination
Returns
TypeDescription
$this

getBigqueryDestination

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where

If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

Returns
TypeDescription
Google\Cloud\AIPlatform\V1\BigQueryDestination|null

hasBigqueryDestination

setBigqueryDestination

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where

If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

Parameter
NameDescription
var Google\Cloud\AIPlatform\V1\BigQueryDestination
Returns
TypeDescription
$this

getPredictionsFormat

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

Returns
TypeDescription
string

setPredictionsFormat

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

Parameter
NameDescription
var string
Returns
TypeDescription
$this

getDestination

Returns
TypeDescription
string