Class: Google::Cloud::AIPlatform::V1::BatchPredictionJob

Inherits:
Object
  • Object
show all
Extended by:
Protobuf::MessageExts::ClassMethods
Includes:
Protobuf::MessageExts
Defined in:
proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb

Overview

A job that uses a Model to produce predictions on multiple [input instances][google.cloud.aiplatform.v1.BatchPredictionJob.input_config]. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.

Defined Under Namespace

Classes: InputConfig, InstanceConfig, LabelsEntry, OutputConfig, OutputInfo

Instance Attribute Summary collapse

Instance Attribute Details

#completion_stats ⇒ ::Google::Cloud::AIPlatform::V1::CompletionStats (readonly)

Returns Output only. Statistics on completed and failed prediction instances.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#create_time ⇒ ::Google::Protobuf::Timestamp (readonly)

Returns Output only. Time when the BatchPredictionJob was created.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#dedicated_resources ⇒ ::Google::Cloud::AIPlatform::V1::BatchDedicatedResources

Returns The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided.

Returns:

  • (::Google::Cloud::AIPlatform::V1::BatchDedicatedResources) —

    The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#disable_container_logging ⇒ ::Boolean

Returns For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send stderr and stdout streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to Cloud Logging pricing.

User can disable container logging by setting this flag to true.

Returns:

  • (::Boolean) —

    For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send stderr and stdout streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to Cloud Logging pricing.

    User can disable container logging by setting this flag to true.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#display_name ⇒ ::String

Returns Required. The user-defined name of this BatchPredictionJob.

Returns:

  • (::String) —

    Required. The user-defined name of this BatchPredictionJob.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#encryption_spec ⇒ ::Google::Cloud::AIPlatform::V1::EncryptionSpec

Returns Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key.

Returns:

  • (::Google::Cloud::AIPlatform::V1::EncryptionSpec) —

    Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#end_time ⇒ ::Google::Protobuf::Timestamp (readonly)

Returns Output only. Time when the BatchPredictionJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED.

Returns:

  • (::Google::Protobuf::Timestamp) —

    Output only. Time when the BatchPredictionJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#error ⇒ ::Google::Rpc::Status (readonly)

Returns Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

Returns:

  • (::Google::Rpc::Status) —

    Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#explanation_spec ⇒ ::Google::Cloud::AIPlatform::V1::ExplanationSpec

Returns Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to true.

This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#generate_explanation ⇒ ::Boolean

Returns Generate explanation with the batch prediction results.

When set to true, the batch prediction output changes based on the predictions_format field of the BatchPredictionJob.output_config object:

  • bigquery: output includes a column named explanation. The value is a struct that conforms to the Explanation object.
  • jsonl: The JSON objects on each line include an additional entry keyed explanation. The value of the entry is a JSON object that conforms to the Explanation object.
  • csv: Generating explanations for CSV format is not supported.

If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.

Returns:

  • (::Boolean) —

    Generate explanation with the batch prediction results.

    When set to true, the batch prediction output changes based on the predictions_format field of the BatchPredictionJob.output_config object:

    • bigquery: output includes a column named explanation. The value is a struct that conforms to the Explanation object.
    • jsonl: The JSON objects on each line include an additional entry keyed explanation. The value of the entry is a JSON object that conforms to the Explanation object.
    • csv: Generating explanations for CSV format is not supported.

    If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#input_config ⇒ ::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InputConfig

Returns Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] instance_schema_uri.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#instance_config ⇒ ::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig

Returns Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#labels ⇒ ::Google::Protobuf::Map{::String => ::String}

Returns The labels with user-defined metadata to organize BatchPredictionJobs.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information and examples of labels.

Returns:

  • (::Google::Protobuf::Map{::String => ::String}) —

    The labels with user-defined metadata to organize BatchPredictionJobs.

    Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

    See https://goo.gl/xmQnxf for more information and examples of labels.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#manual_batch_tuning_parameters ⇒ ::Google::Cloud::AIPlatform::V1::ManualBatchTuningParameters

Returns Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#model ⇒ ::String

Returns The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set.

The model resource name may contain version id or version alias to specify the version. Example: projects/{project}/locations/{location}/models/{model}@2 or projects/{project}/locations/{location}/models/{model}@golden if no version is specified, the default version will be deployed.

The model resource could also be a publisher model. Example: publishers/{publisher}/models/{model} or projects/{project}/locations/{location}/publishers/{publisher}/models/{model}.

Returns:

  • (::String) —

    The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set.

    The model resource name may contain version id or version alias to specify the version. Example: projects/{project}/locations/{location}/models/{model}@2 or projects/{project}/locations/{location}/models/{model}@golden if no version is specified, the default version will be deployed.

    The model resource could also be a publisher model. Example: publishers/{publisher}/models/{model} or projects/{project}/locations/{location}/publishers/{publisher}/models/{model}



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#model_parameters ⇒ ::Google::Protobuf::Value

Returns The parameters that govern the predictions. The schema of the parameters may be specified via the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] parameters_schema_uri.

Returns:

  • (::Google::Protobuf::Value) —

    The parameters that govern the predictions. The schema of the parameters may be specified via the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] parameters_schema_uri.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#model_version_id ⇒ ::String (readonly)

Returns Output only. The version ID of the Model that produces the predictions via this job.

Returns:

  • (::String) —

    Output only. The version ID of the Model that produces the predictions via this job.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#name ⇒ ::String (readonly)

Returns Output only. Resource name of the BatchPredictionJob.

Returns:

  • (::String) —

    Output only. Resource name of the BatchPredictionJob.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#output_config ⇒ ::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig

Returns Required. The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] instance_schema_uri and prediction_schema_uri.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#output_info ⇒ ::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputInfo (readonly)

Returns Output only. Information further describing the output of this job.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#partial_failures ⇒ ::Array<::Google::Rpc::Status> (readonly)

Returns Output only. Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details.

Returns:

  • (::Array<::Google::Rpc::Status>) —

    Output only. Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#resources_consumed ⇒ ::Google::Cloud::AIPlatform::V1::ResourcesConsumed (readonly)

Returns Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes.

Note: This field currently may be not populated for batch predictions that use AutoML Models.

Returns:

  • (::Google::Cloud::AIPlatform::V1::ResourcesConsumed) —

    Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes.

    Note: This field currently may be not populated for batch predictions that use AutoML Models.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#satisfies_pzi ⇒ ::Boolean (readonly)

Returns Output only. Reserved for future use.

Returns:

  • (::Boolean) —

    Output only. Reserved for future use.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#satisfies_pzs ⇒ ::Boolean (readonly)

Returns Output only. Reserved for future use.

Returns:

  • (::Boolean) —

    Output only. Reserved for future use.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#service_account ⇒ ::String

Returns The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources.

Users deploying the Model must have the iam.serviceAccounts.actAs permission on this service account.

Returns:

  • (::String) —

    The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources.

    Users deploying the Model must have the iam.serviceAccounts.actAs permission on this service account.



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#start_time ⇒ ::Google::Protobuf::Timestamp (readonly)

Returns Output only. Time when the BatchPredictionJob for the first time entered the JOB_STATE_RUNNING state.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#state ⇒ ::Google::Cloud::AIPlatform::V1::JobState (readonly)

Returns Output only. The detailed state of the job.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#unmanaged_container_model ⇒ ::Google::Cloud::AIPlatform::V1::UnmanagedContainerModel

Returns Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#update_time ⇒ ::Google::Protobuf::Timestamp (readonly)

Returns Output only. Time when the BatchPredictionJob was most recently updated.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 224

class BatchPredictionJob
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Configures the input to
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
  # for Model's supported input formats, and how instances should be expressed
  # via any of them.
  # @!attribute [rw] gcs_source
  #   @return [::Google::Cloud::AIPlatform::V1::GcsSource]
  #     The Cloud Storage location for the input instances.
  # @!attribute [rw] bigquery_source
  #   @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
  #     The BigQuery location of the input table.
  #     The schema of the table should be in the format described by the given
  #     context OpenAPI Schema, if one is provided. The table may contain
  #     additional columns that are not described by the schema, and they will
  #     be ignored.
  # @!attribute [rw] instances_format
  #   @return [::String]
  #     Required. The format in which instances are given, must be one of the
  #     [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
  class InputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configuration defining how to transform batch prediction input instances to
  # the instances that the Model accepts.
  # @!attribute [rw] instance_type
  #   @return [::String]
  #     The format of the instance that the Model accepts. Vertex AI will
  #     convert compatible
  #     [batch prediction input instance
  #     formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
  #     to the specified format.
  #
  #     Supported values are:
  #
  #     * `object`: Each input is converted to JSON object format.
  #         * For `bigquery`, each row is converted to an object.
  #         * For `jsonl`, each line of the JSONL input must be an object.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     * `array`: Each input is converted to JSON array format.
  #         * For `bigquery`, each row is converted to an array. The order
  #           of columns is determined by the BigQuery column order, unless
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           is populated.
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * For `jsonl`, if each line of the JSONL input is an object,
  #           {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #           must be populated for specifying field orders.
  #         * Does not apply to `csv`, `file-list`, `tf-record`, or
  #           `tf-record-gzip`.
  #
  #     If not specified, Vertex AI converts the batch prediction input as
  #     follows:
  #
  #      * For `bigquery` and `csv`, the behavior is the same as `array`. The
  #        order of columns is the same as defined in the file or table, unless
  #        {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #        is populated.
  #      * For `jsonl`, the prediction instance format is determined by
  #        each line of the input.
  #      * For `tf-record`/`tf-record-gzip`, each record will be converted to
  #        an object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the record.
  #      * For `file-list`, each file in the list will be converted to an
  #        object in the format of `{"b64": <value>}`, where `<value>` is
  #        the Base64-encoded string of the content of the file.
  # @!attribute [rw] key_field
  #   @return [::String]
  #     The name of the field that is considered as a key.
  #
  #     The values identified by the key field is not included in the transformed
  #     instances that is sent to the Model. This is similar to
  #     specifying this name of the field in
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
  #     In addition, the batch prediction output will not include the instances.
  #     Instead the output will only include the value of the key field, in a
  #     field named `key` in the output:
  #
  #      * For `jsonl` output format, the output will have a `key` field
  #        instead of the `instance` field.
  #      * For `csv`/`bigquery` output format, the output will have have a `key`
  #        column instead of the instance feature columns.
  #
  #     The input must be JSONL with objects at each line, CSV, BigQuery
  #     or TfRecord.
  # @!attribute [rw] included_fields
  #   @return [::Array<::String>]
  #     Fields that will be included in the prediction instance that is
  #     sent to the Model.
  #
  #     If
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
  #     is `array`, the order of field names in included_fields also determines
  #     the order of the values in the array.
  #
  #     When included_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  # @!attribute [rw] excluded_fields
  #   @return [::Array<::String>]
  #     Fields that will be excluded in the prediction instance that is
  #     sent to the Model.
  #
  #     Excluded will be attached to the batch prediction output if
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
  #     is not specified.
  #
  #     When excluded_fields is populated,
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
  #     must be empty.
  #
  #     The input must be JSONL with objects at each line, BigQuery
  #     or TfRecord.
  class InstanceConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Configures the output of
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
  # {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
  # for supported output formats, and how predictions are expressed via any of
  # them.
  # @!attribute [rw] gcs_destination
  #   @return [::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
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
  #     and N may equal 0001 and depends on the total number of successfully
  #     predicted instances. If the Model has both
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
  #     schemata defined then each such file contains predictions as per the
  #     {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format 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.
  # @!attribute [rw] bigquery_destination
  #   @return [::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 <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
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
  #     and
  #     {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri 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 google.rpc.Status}
  #     represented as a STRUCT, and containing only `code` and `message`.
  # @!attribute [rw] predictions_format
  #   @return [::String]
  #     Required. The format in which Vertex AI gives the predictions, must be
  #     one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
  #     {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
  class OutputConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Further describes this job's output.
  # Supplements
  # {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
  # @!attribute [r] gcs_output_directory
  #   @return [::String]
  #     Output only. The full path of the Cloud Storage directory created, into
  #     which the prediction output is written.
  # @!attribute [r] bigquery_output_dataset
  #   @return [::String]
  #     Output only. The path of the BigQuery dataset created, in
  #     `bq://projectId.bqDatasetId`
  #     format, into which the prediction output is written.
  # @!attribute [r] bigquery_output_table
  #   @return [::String]
  #     Output only. The name of the BigQuery table created, in
  #     `predictions_<timestamp>`
  #     format, into which the prediction output is written.
  #     Can be used by UI to generate the BigQuery output path, for example.
  class OutputInfo
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class LabelsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end