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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
The name of the Model resoure 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. |
unmanaged_container_model |
google.cloud.aiplatform_v1.types.UnmanagedContainerModel
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. |
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). |
generate_explanation |
bool
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. |
explanation_spec |
google.cloud.aiplatform_v1.types.ExplanationSpec
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. |
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 |
Mapping[str, str]
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 > BatchPredictionJobClasses
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.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
LabelsEntry
LabelsEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)
The abstract base class for a message.
Name | Description |
kwargs |
dict
Keys and values corresponding to the fields of the message. |
mapping |
Union[dict, `.Message`]
A dictionary or message to be used to determine the values for this message. |
ignore_unknown_fields |
Optional(bool)
If True, do not raise errors for unknown fields. Only applied if |
OutputConfig
OutputConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
OutputInfo
OutputInfo(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Further describes this job's output. Supplements output_config.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields