Class BatchPredictionJob (3.47.0)

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.

Protobuf type google.cloud.aiplatform.v1beta1.BatchPredictionJob

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.

map<string, string> labels = 19;

Output only. Statistics on completed and failed prediction instances.

.google.cloud.aiplatform.v1beta1.CompletionStats completion_stats = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Statistics on completed and failed prediction instances.

.google.cloud.aiplatform.v1beta1.CompletionStats completion_stats = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Time when the BatchPredictionJob was created.

.google.protobuf.Timestamp create_time = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Time when the BatchPredictionJob was created.

.google.protobuf.Timestamp create_time = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

.google.cloud.aiplatform.v1beta1.BatchDedicatedResources dedicated_resources = 7;

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.

.google.cloud.aiplatform.v1beta1.BatchDedicatedResources dedicated_resources = 7;

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

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

bool disable_container_logging = 34;

Required. The user-defined name of this BatchPredictionJob.

string display_name = 2 [(.google.api.field_behavior) = REQUIRED];

Required. The user-defined name of this BatchPredictionJob.

string display_name = 2 [(.google.api.field_behavior) = REQUIRED];

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.

.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;

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.

.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;

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

.google.protobuf.Timestamp end_time = 17 [(.google.api.field_behavior) = OUTPUT_ONLY];

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

.google.protobuf.Timestamp end_time = 17 [(.google.api.field_behavior) = OUTPUT_ONLY];

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

.google.rpc.Status error = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];

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

.google.rpc.Status error = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 25;

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.

.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 25;

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.

bool generate_explanation = 23;

Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig input_config = 4 [(.google.api.field_behavior) = REQUIRED];

Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig input_config = 4 [(.google.api.field_behavior) = REQUIRED];

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

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.InstanceConfig instance_config = 27;

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

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.InstanceConfig instance_config = 27;

Use #getLabelsMap() instead.

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.

map<string, string> labels = 19;

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.

map<string, string> labels = 19;

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.

map<string, string> labels = 19;

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.

map<string, string> labels = 19;

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

.google.cloud.aiplatform.v1beta1.ManualBatchTuningParameters manual_batch_tuning_parameters = 8 [(.google.api.field_behavior) = IMMUTABLE];

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

.google.cloud.aiplatform.v1beta1.ManualBatchTuningParameters manual_batch_tuning_parameters = 8 [(.google.api.field_behavior) = IMMUTABLE];

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}

string model = 3 [(.google.api.resource_reference) = { ... }

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}

string model = 3 [(.google.api.resource_reference) = { ... }

Model monitoring config will be used for analysis model behaviors, based on the input and output to the batch prediction job, as well as the provided training dataset.

.google.cloud.aiplatform.v1beta1.ModelMonitoringConfig model_monitoring_config = 26;

Model monitoring config will be used for analysis model behaviors, based on the input and output to the batch prediction job, as well as the provided training dataset.

.google.cloud.aiplatform.v1beta1.ModelMonitoringConfig model_monitoring_config = 26;

Get batch prediction job monitoring statistics.

repeated .google.cloud.aiplatform.v1beta1.ModelMonitoringStatsAnomalies model_monitoring_stats_anomalies = 31;

Get batch prediction job monitoring statistics.

repeated .google.cloud.aiplatform.v1beta1.ModelMonitoringStatsAnomalies model_monitoring_stats_anomalies = 31;

Get batch prediction job monitoring statistics.

repeated .google.cloud.aiplatform.v1beta1.ModelMonitoringStatsAnomalies model_monitoring_stats_anomalies = 31;

Get batch prediction job monitoring statistics.

repeated .google.cloud.aiplatform.v1beta1.ModelMonitoringStatsAnomalies model_monitoring_stats_anomalies = 31;

Get batch prediction job monitoring statistics.

repeated .google.cloud.aiplatform.v1beta1.ModelMonitoringStatsAnomalies model_monitoring_stats_anomalies = 31;

Output only. The running status of the model monitoring pipeline.

.google.rpc.Status model_monitoring_status = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The running status of the model monitoring pipeline.

.google.rpc.Status model_monitoring_status = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];

The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.

.google.protobuf.Value model_parameters = 5;

The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.

.google.protobuf.Value model_parameters = 5;

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

string model_version_id = 30 [(.google.api.field_behavior) = OUTPUT_ONLY];

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

string model_version_id = 30 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Resource name of the BatchPredictionJob.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Resource name of the BatchPredictionJob.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

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 PredictSchemata's instance_schema_uri and prediction_schema_uri.

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig output_config = 6 [(.google.api.field_behavior) = REQUIRED];

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 PredictSchemata's instance_schema_uri and prediction_schema_uri.

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig output_config = 6 [(.google.api.field_behavior) = REQUIRED];

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

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputInfo output_info = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];

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

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputInfo output_info = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

repeated .google.rpc.Status partial_failures = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

repeated .google.rpc.Status partial_failures = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

repeated .google.rpc.Status partial_failures = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

repeated .google.rpc.Status partial_failures = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

repeated .google.rpc.Status partial_failures = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

.google.cloud.aiplatform.v1beta1.ResourcesConsumed resources_consumed = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

.google.cloud.aiplatform.v1beta1.ResourcesConsumed resources_consumed = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

string service_account = 29;

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.

string service_account = 29;

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

.google.protobuf.Timestamp start_time = 16 [(.google.api.field_behavior) = OUTPUT_ONLY];

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

.google.protobuf.Timestamp start_time = 16 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The detailed state of the job.

.google.cloud.aiplatform.v1beta1.JobState state = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The detailed state of the job.

.google.cloud.aiplatform.v1beta1.JobState state = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

.google.cloud.aiplatform.v1beta1.UnmanagedContainerModel unmanaged_container_model = 28;

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.

.google.cloud.aiplatform.v1beta1.UnmanagedContainerModel unmanaged_container_model = 28;

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

.google.protobuf.Timestamp update_time = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];

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

.google.protobuf.Timestamp update_time = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Statistics on completed and failed prediction instances.

.google.cloud.aiplatform.v1beta1.CompletionStats completion_stats = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Time when the BatchPredictionJob was created.

.google.protobuf.Timestamp create_time = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

.google.cloud.aiplatform.v1beta1.BatchDedicatedResources dedicated_resources = 7;

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.

.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;

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

.google.protobuf.Timestamp end_time = 17 [(.google.api.field_behavior) = OUTPUT_ONLY];

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

.google.rpc.Status error = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 25;

Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig input_config = 4 [(.google.api.field_behavior) = REQUIRED];

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

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.InstanceConfig instance_config = 27;

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

.google.cloud.aiplatform.v1beta1.ManualBatchTuningParameters manual_batch_tuning_parameters = 8 [(.google.api.field_behavior) = IMMUTABLE];

Model monitoring config will be used for analysis model behaviors, based on the input and output to the batch prediction job, as well as the provided training dataset.

.google.cloud.aiplatform.v1beta1.ModelMonitoringConfig model_monitoring_config = 26;

Output only. The running status of the model monitoring pipeline.

.google.rpc.Status model_monitoring_status = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];

The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.

.google.protobuf.Value model_parameters = 5;

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 PredictSchemata's instance_schema_uri and prediction_schema_uri.

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig output_config = 6 [(.google.api.field_behavior) = REQUIRED];

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

.google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputInfo output_info = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

.google.cloud.aiplatform.v1beta1.ResourcesConsumed resources_consumed = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

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

.google.protobuf.Timestamp start_time = 16 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

.google.cloud.aiplatform.v1beta1.UnmanagedContainerModel unmanaged_container_model = 28;

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

.google.protobuf.Timestamp update_time = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];