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
Methods
__construct
Constructor.
| Parameters | |
|---|---|
| Name | Description |
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 |
↳ 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
|
↳ 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 | |
|---|---|
| Type | Description |
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 | |
|---|---|
| Name | Description |
var |
Google\Cloud\AIPlatform\V1\GcsDestination
|
| Returns | |
|---|---|
| Type | Description |
$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 | |
|---|---|
| Type | Description |
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 | |
|---|---|
| Name | Description |
var |
Google\Cloud\AIPlatform\V1\BigQueryDestination
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getPredictionsFormat
Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.
| Returns | |
|---|---|
| Type | Description |
string | |
setPredictionsFormat
Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getDestination
| Returns | |
|---|---|
| Type | Description |
string | |