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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 resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: projects/{project}/locations/{location}/models/{model}@2
or
projects/{project}/locations/{location}/models/{model}@golden
if no version is specified, the default version will be
deployed.
The model resource could also be a publisher model. Example:
publishers/{publisher}/models/{model} or
projects/{project}/locations/{location}/publishers/{publisher}/models/{model}
|
model_version_id |
str
Output only. The version ID of the Model that produces the predictions via this job. |
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. |
instance_config |
google.cloud.aiplatform_v1.types.BatchPredictionJob.InstanceConfig
Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model. |
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. |
service_account |
str
The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the iam.serviceAccounts.actAs permission on this service
account.
|
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 |
MutableSequence[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 Google Cloud 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 |
MutableMapping[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. |
disable_container_logging |
bool
For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send stderr and stdout streams to Cloud Logging by
default. Please note that the logs incur cost, which are
subject to `Cloud Logging
pricing |
satisfies_pzs |
bool
Output only. Reserved for future use. |
satisfies_pzi |
bool
Output only. Reserved for future use. |
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.
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
InstanceConfig
InstanceConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.
LabelsEntry
LabelsEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)
The abstract base class for a message.
Parameters | |
---|---|
Name | Description |
kwargs |
dict
Keys and values corresponding to the fields of the message. |
mapping |
Union[dict,
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
Methods
BatchPredictionJob
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.