Struct GoogleCloudAiplatformV1BatchPredictionJobOutputConfig

pub struct GoogleCloudAiplatformV1BatchPredictionJobOutputConfig {
    pub predictions_format: Option<String>,
    pub gcs_destination: Option<GoogleCloudAiplatformV1GcsDestination>,
    pub bigquery_destination: Option<GoogleCloudAiplatformV1BigQueryDestination>,
}

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

This type is not used in any activity, and only used as part of another schema.

Fields

predictions_format: Option<String>

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

gcs_destination: Option<GoogleCloudAiplatformV1GcsDestination>

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--, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001., predictions_0002., …, predictions_N. are created where `` 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., errors_0002.,…, errors_N. 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: Option<GoogleCloudAiplatformV1BigQueryDestination>

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__ where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ “based on ISO-8601” format. In the dataset two tables will be created, predictions, and errors. 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.

Trait Implementations

impl Clone for GoogleCloudAiplatformV1BatchPredictionJobOutputConfig

fn clone(&self) -> GoogleCloudAiplatformV1BatchPredictionJobOutputConfig

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for GoogleCloudAiplatformV1BatchPredictionJobOutputConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for GoogleCloudAiplatformV1BatchPredictionJobOutputConfig

fn default() -> GoogleCloudAiplatformV1BatchPredictionJobOutputConfig

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for GoogleCloudAiplatformV1BatchPredictionJobOutputConfig

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for GoogleCloudAiplatformV1BatchPredictionJobOutputConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Part for GoogleCloudAiplatformV1BatchPredictionJobOutputConfig