Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig (v0.63.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::BatchPredictionJob::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.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#bigquery_destination

def bigquery_destination() -> ::Google::Cloud::AIPlatform::V1::BigQueryDestination
Returns

#bigquery_destination=

def bigquery_destination=(value) -> ::Google::Cloud::AIPlatform::V1::BigQueryDestination
Parameter
  • value (::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
Returns

#gcs_destination

def gcs_destination() -> ::Google::Cloud::AIPlatform::V1::GcsDestination
Returns
  • (::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.

    Note: The following fields are mutually exclusive: gcs_destination, bigquery_destination. If a field in that set is populated, all other fields in the set will automatically be cleared.

#gcs_destination=

def gcs_destination=(value) -> ::Google::Cloud::AIPlatform::V1::GcsDestination
Parameter
  • value (::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.

    Note: The following fields are mutually exclusive: gcs_destination, bigquery_destination. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns
  • (::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.

    Note: The following fields are mutually exclusive: gcs_destination, bigquery_destination. If a field in that set is populated, all other fields in the set will automatically be cleared.

#predictions_format

def predictions_format() -> ::String
Returns
  • (::String) — Required. The format in which Vertex AI gives the predictions, must be one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model] supported_output_storage_formats.

#predictions_format=

def predictions_format=(value) -> ::String
Parameter
  • value (::String) — Required. The format in which Vertex AI gives the predictions, must be one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model] supported_output_storage_formats.
Returns
  • (::String) — Required. The format in which Vertex AI gives the predictions, must be one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model] supported_output_storage_formats.