Package com.google.cloud.aiplatform.v1

Interface BatchPredictionJob.OutputConfigOrBuilder

    • Method Detail

      • hasGcsDestination

        boolean hasGcsDestination()
         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][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.predictions_format],
 and N may equal 0001 and depends on the total number of successfully
 predicted instances. If the Model has both
 [instance][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.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][google.rpc.Status]
 containing only `code` and `message` fields.
        .google.cloud.aiplatform.v1.GcsDestination gcs_destination = 2;
        Returns:
        Whether the gcsDestination field is set.

      • getGcsDestination

        GcsDestination 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][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.predictions_format],
 and N may equal 0001 and depends on the total number of successfully
 predicted instances. If the Model has both
 [instance][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.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][google.rpc.Status]
 containing only `code` and `message` fields.
        .google.cloud.aiplatform.v1.GcsDestination gcs_destination = 2;
        Returns:
        The gcsDestination.

      • getGcsDestinationOrBuilder

        GcsDestinationOrBuilder getGcsDestinationOrBuilder()
         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][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.predictions_format],
 and N may equal 0001 and depends on the total number of successfully
 predicted instances. If the Model has both
 [instance][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.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][google.rpc.Status]
 containing only `code` and `message` fields.
        .google.cloud.aiplatform.v1.GcsDestination gcs_destination = 2;

      • hasBigqueryDestination

        boolean hasBigqueryDestination()
         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 <model-display-name> 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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 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][google.rpc.Status]
 represented as a STRUCT, and containing only `code` and `message`.
        .google.cloud.aiplatform.v1.BigQueryDestination bigquery_destination = 3;
        Returns:
        Whether the bigqueryDestination field is set.

      • getBigqueryDestination

        BigQueryDestination 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 <model-display-name> 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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 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][google.rpc.Status]
 represented as a STRUCT, and containing only `code` and `message`.
        .google.cloud.aiplatform.v1.BigQueryDestination bigquery_destination = 3;
        Returns:
        The bigqueryDestination.

      • getBigqueryDestinationOrBuilder

        BigQueryDestinationOrBuilder getBigqueryDestinationOrBuilder()
         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 <model-display-name> 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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 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][google.rpc.Status]
 represented as a STRUCT, and containing only `code` and `message`.
        .google.cloud.aiplatform.v1.BigQueryDestination bigquery_destination = 3;

      • getPredictionsFormat

        String getPredictionsFormat()
         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][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
        string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        The predictionsFormat.

      • getPredictionsFormatBytes

        com.google.protobuf.ByteString getPredictionsFormatBytes()
         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][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
        string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        The bytes for predictionsFormat.