Class BatchPredictionJob (1.1.1)

Version 1.1.1

• 1.66.0 (latest)
• 1.65.0
• 1.63.0
• 1.62.0
• 1.60.0
• 1.59.0
• 1.58.0
• 1.57.0
• 1.56.0
• 1.55.0
• 1.54.1
• 1.53.0
• 1.52.0
• 1.51.0
• 1.50.0
• 1.49.0
• 1.48.0
• 1.47.0
• 1.46.0
• 1.45.0
• 1.44.0
• 1.43.0
• 1.39.0
• 1.38.1
• 1.37.0
• 1.36.4
• 1.35.0
• 1.34.0
• 1.33.1
• 1.32.0
• 1.31.1
• 1.30.1
• 1.29.0
• 1.28.1
• 1.27.1
• 1.26.1
• 1.25.0
• 1.24.1
• 1.23.0
• 1.22.1
• 1.21.0
• 1.20.0
• 1.19.1
• 1.18.3
• 1.17.1
• 1.16.1
• 1.15.1
• 1.14.0
• 1.13.1
• 1.12.1
• 1.11.0
• 1.10.0
• 1.9.0
• 1.8.1
• 1.7.1
• 1.6.2
• 1.5.0
• 1.4.3
• 1.3.0
• 1.2.0
• 1.1.1
• 1.0.1
• 0.9.0
• 0.8.0
• 0.7.1
• 0.6.0
• 0.5.1
• 0.4.0
• 0.3.1

BatchPredictionJob(mapping=None, *, ignore_unknown_fields=False, **kwargs)

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

Attributes

Name	Description
name	str Output only. Resource name of the BatchPredictionJob.
display_name	str Required. The user-defined name of this BatchPredictionJob.
model	str Required. The name of the Model 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.
input_config	google.cloud.aiplatform_v1.types.BatchPredictionJob.InputConfig 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.
model_parameters	google.protobuf.struct_pb2.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.
output_config	google.cloud.aiplatform_v1.types.BatchPredictionJob.OutputConfig 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.
dedicated_resources	google.cloud.aiplatform_v1.types.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.
manual_batch_tuning_parameters	google.cloud.aiplatform_v1.types.ManualBatchTuningParameters Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).
output_info	google.cloud.aiplatform_v1.types.BatchPredictionJob.OutputInfo Output only. Information further describing the output of this job.
state	google.cloud.aiplatform_v1.types.JobState Output only. The detailed state of the job.
error	google.rpc.status_pb2.Status Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
partial_failures	Sequence[google.rpc.status_pb2.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.
resources_consumed	google.cloud.aiplatform_v1.types.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.
completion_stats	google.cloud.aiplatform_v1.types.CompletionStats Output only. Statistics on completed and failed prediction instances.
create_time	google.protobuf.timestamp_pb2.Timestamp Output only. Time when the BatchPredictionJob was created.
start_time	google.protobuf.timestamp_pb2.Timestamp Output only. Time when the BatchPredictionJob for the first time entered the ``JOB_STATE_RUNNING`` state.
end_time	google.protobuf.timestamp_pb2.Timestamp Output only. Time when the BatchPredictionJob entered any of the following states: ``JOB_STATE_SUCCEEDED``, ``JOB_STATE_FAILED``, ``JOB_STATE_CANCELLED``.
update_time	google.protobuf.timestamp_pb2.Timestamp Output only. Time when the BatchPredictionJob was most recently updated.
labels	Sequence[google.cloud.aiplatform_v1.types.BatchPredictionJob.LabelsEntry] 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.
encryption_spec	google.cloud.aiplatform_v1.types.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.

Inheritance

builtins.object > proto.message.Message > BatchPredictionJob

Classes

InputConfig

InputConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.

LabelsEntry