Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1BatchPredictionJob

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1beta1/classes.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb,
lib/google/apis/aiplatform_v1beta1/representations.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.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1BatchPredictionJob

Returns a new instance of GoogleCloudAiplatformV1beta1BatchPredictionJob.



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10721

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#completion_stats ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1CompletionStats

Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch. Corresponds to the JSON property completionStats

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10498

def completion_stats
  @completion_stats
end

#create_time ⇒ String

Output only. Time when the BatchPredictionJob was created. Corresponds to the JSON property createTime

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10503

def create_time
  @create_time
end

#dedicated_resources ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1BatchDedicatedResources

A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration. Corresponds to the JSON property dedicatedResources

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10509

def dedicated_resources
  @dedicated_resources
end

#disable_container_logging ⇒ Boolean Also known as: disable_container_logging?

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. Corresponds to the JSON property disableContainerLogging

Returns:

  • (Boolean) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10518

def disable_container_logging
  @disable_container_logging
end

#display_name ⇒ String

Required. The user-defined name of this BatchPredictionJob. Corresponds to the JSON property displayName

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10524

def display_name
  @display_name
end

#encryption_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1EncryptionSpec

Represents a customer-managed encryption key specification that can be applied to a Vertex AI resource. Corresponds to the JSON property encryptionSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10530

def encryption_spec
  @encryption_spec
end

#end_time ⇒ String

Output only. Time when the BatchPredictionJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED. Corresponds to the JSON property endTime

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10536

def end_time
  @end_time
end

#endpoint ⇒ String

For Bring-Your-Own-Endpoint (BYOE), the name of the Endpoint resource that produces the predictions via this job, must share the same ancestor Location. Exactly one of model, unmanaged_container_model, or endpoint must be set. Example: projects/193595526740/locations/us-central1/endpoints/ 4203439000301600768 Corresponds to the JSON property endpoint

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10545

def endpoint
  @endpoint
end

#error ⇒ Google::Apis::AiplatformV1beta1::GoogleRpcStatus

The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. Each Status message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the API Design Guide. Corresponds to the JSON property error

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10555

def error
  @error
end

#explanation_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ExplanationSpec

Specification of Model explanation. Corresponds to the JSON property explanationSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10560

def explanation_spec
  @explanation_spec
end

#generate_explanation ⇒ Boolean Also known as: generate_explanation?

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. Corresponds to the JSON property generateExplanation

Returns:

  • (Boolean) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10573

def generate_explanation
  @generate_explanation
end

#input_config ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1BatchPredictionJobInputConfig

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. Corresponds to the JSON property inputConfig

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10581

def input_config
  @input_config
end

#instance_config ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1BatchPredictionJobInstanceConfig

Configuration defining how to transform batch prediction input instances to the instances that the Model accepts. Corresponds to the JSON property instanceConfig

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10587

def instance_config
  @instance_config
end

#labels ⇒ Hash<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. Corresponds to the JSON property labels

Returns:

  • (Hash<String,String>) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10596

def labels
  @labels
end

#manual_batch_tuning_parameters ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ManualBatchTuningParameters

Manual batch tuning parameters. Corresponds to the JSON property manualBatchTuningParameters

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10601

def manual_batch_tuning_parameters
  @manual_batch_tuning_parameters
end

#model ⇒ 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, unmanaged_container_model, or endpoint 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/modelor ` projects/`project`/locations/`location`/publishers/`publisher`/models/`model Corresponds to the JSON property model

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10615

def model
  @model
end

#model_monitoring_config ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelMonitoringConfig

The model monitoring configuration used for Batch Prediction Job. Corresponds to the JSON property modelMonitoringConfig

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10620

def model_monitoring_config
  @model_monitoring_config
end

#model_monitoring_stats_anomalies ⇒ Array<Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies>

Get batch prediction job monitoring statistics. Corresponds to the JSON property modelMonitoringStatsAnomalies

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10625

def model_monitoring_stats_anomalies
  @model_monitoring_stats_anomalies
end

#model_monitoring_status ⇒ Google::Apis::AiplatformV1beta1::GoogleRpcStatus

The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. Each Status message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the API Design Guide. Corresponds to the JSON property modelMonitoringStatus

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10635

def model_monitoring_status
  @model_monitoring_status
end

#model_parameters ⇒ Object

The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri. Corresponds to the JSON property modelParameters

Returns:

  • (Object) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10641

def model_parameters
  @model_parameters
end

#model_version_id ⇒ String

Output only. The version ID of the Model that produces the predictions via this job. Corresponds to the JSON property modelVersionId

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10647

def model_version_id
  @model_version_id
end

#name ⇒ String

Output only. Resource name of the BatchPredictionJob. Corresponds to the JSON property name

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10652

def name
  @name
end

#output_config ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1BatchPredictionJobOutputConfig

Configures the output of BatchPredictionJob. See Model. supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them. Corresponds to the JSON property outputConfig

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10659

def output_config
  @output_config
end

#output_info ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1BatchPredictionJobOutputInfo

Further describes this job's output. Supplements output_config. Corresponds to the JSON property outputInfo

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10664

def output_info
  @output_info
end

#partial_failures ⇒ Array<Google::Apis::AiplatformV1beta1::GoogleRpcStatus>

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. Corresponds to the JSON property partialFailures

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10671

def partial_failures
  @partial_failures
end

#resources_consumed ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ResourcesConsumed

Statistics information about resource consumption. Corresponds to the JSON property resourcesConsumed

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10676

def resources_consumed
  @resources_consumed
end

#satisfies_pzi ⇒ Boolean Also known as: satisfies_pzi?

Output only. Reserved for future use. Corresponds to the JSON property satisfiesPzi

Returns:

  • (Boolean) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10681

def satisfies_pzi
  @satisfies_pzi
end

#satisfies_pzs ⇒ Boolean Also known as: satisfies_pzs?

Output only. Reserved for future use. Corresponds to the JSON property satisfiesPzs

Returns:

  • (Boolean) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10687

def satisfies_pzs
  @satisfies_pzs
end

#service_account ⇒ String

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. Corresponds to the JSON property serviceAccount

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10697

def 
  @service_account
end

#start_time ⇒ String

Output only. Time when the BatchPredictionJob for the first time entered the JOB_STATE_RUNNING state. Corresponds to the JSON property startTime

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10703

def start_time
  @start_time
end

#state ⇒ String

Output only. The detailed state of the job. Corresponds to the JSON property state

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10708

def state
  @state
end

#unmanaged_container_model ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1UnmanagedContainerModel

Contains model information necessary to perform batch prediction without requiring a full model import. Corresponds to the JSON property unmanagedContainerModel

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10714

def unmanaged_container_model
  @unmanaged_container_model
end

#update_time ⇒ String

Output only. Time when the BatchPredictionJob was most recently updated. Corresponds to the JSON property updateTime

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10719

def update_time
  @update_time
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 10726

def update!(**args)
  @completion_stats = args[:completion_stats] if args.key?(:completion_stats)
  @create_time = args[:create_time] if args.key?(:create_time)
  @dedicated_resources = args[:dedicated_resources] if args.key?(:dedicated_resources)
  @disable_container_logging = args[:disable_container_logging] if args.key?(:disable_container_logging)
  @display_name = args[:display_name] if args.key?(:display_name)
  @encryption_spec = args[:encryption_spec] if args.key?(:encryption_spec)
  @end_time = args[:end_time] if args.key?(:end_time)
  @endpoint = args[:endpoint] if args.key?(:endpoint)
  @error = args[:error] if args.key?(:error)
  @explanation_spec = args[:explanation_spec] if args.key?(:explanation_spec)
  @generate_explanation = args[:generate_explanation] if args.key?(:generate_explanation)
  @input_config = args[:input_config] if args.key?(:input_config)
  @instance_config = args[:instance_config] if args.key?(:instance_config)
  @labels = args[:labels] if args.key?(:labels)
  @manual_batch_tuning_parameters = args[:manual_batch_tuning_parameters] if args.key?(:manual_batch_tuning_parameters)
  @model = args[:model] if args.key?(:model)
  @model_monitoring_config = args[:model_monitoring_config] if args.key?(:model_monitoring_config)
  @model_monitoring_stats_anomalies = args[:model_monitoring_stats_anomalies] if args.key?(:model_monitoring_stats_anomalies)
  @model_monitoring_status = args[:model_monitoring_status] if args.key?(:model_monitoring_status)
  @model_parameters = args[:model_parameters] if args.key?(:model_parameters)
  @model_version_id = args[:model_version_id] if args.key?(:model_version_id)
  @name = args[:name] if args.key?(:name)
  @output_config = args[:output_config] if args.key?(:output_config)
  @output_info = args[:output_info] if args.key?(:output_info)
  @partial_failures = args[:partial_failures] if args.key?(:partial_failures)
  @resources_consumed = args[:resources_consumed] if args.key?(:resources_consumed)
  @satisfies_pzi = args[:satisfies_pzi] if args.key?(:satisfies_pzi)
  @satisfies_pzs = args[:satisfies_pzs] if args.key?(:satisfies_pzs)
  @service_account = args[:service_account] if args.key?(:service_account)
  @start_time = args[:start_time] if args.key?(:start_time)
  @state = args[:state] if args.key?(:state)
  @unmanaged_container_model = args[:unmanaged_container_model] if args.key?(:unmanaged_container_model)
  @update_time = args[:update_time] if args.key?(:update_time)
end