Package com.google.cloud.aiplatform.v1

Interface BatchPredictionJob.OutputConfigOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
BatchPredictionJob.OutputConfig, BatchPredictionJob.OutputConfig.Builder
Enclosing class:
BatchPredictionJob
public static interface BatchPredictionJob.OutputConfigOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Details

    • 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;

    • hasVertexMultimodalDatasetDestination

      boolean hasVertexMultimodalDatasetDestination()
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;
      Returns:
      Whether the vertexMultimodalDatasetDestination field is set.

    • getVertexMultimodalDatasetDestination

      VertexMultimodalDatasetDestination getVertexMultimodalDatasetDestination()
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;
      Returns:
      The vertexMultimodalDatasetDestination.

    • getVertexMultimodalDatasetDestinationOrBuilder

      VertexMultimodalDatasetDestinationOrBuilder getVertexMultimodalDatasetDestinationOrBuilder()
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;

    • 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.

    • getDestinationCase

      BatchPredictionJob.OutputConfig.DestinationCase getDestinationCase()