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. 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, 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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, if no version is specified, the default version will be used.

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, if no version is specified, the default version will be used.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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 GCP 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 GCP error details.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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.



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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:



168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
 
# File 'proto_docs/google/cloud/aiplatform/v1/batch_prediction_job.rb', line 168

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

  # 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