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 1960

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

Instance Attribute Details

#completion_statsGoogle::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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1758

def completion_stats
  @completion_stats
end

#create_timeString

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 1763

def create_time
  @create_time
end

#dedicated_resourcesGoogle::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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1769

def dedicated_resources
  @dedicated_resources
end

#disable_container_loggingBoolean 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 1778

def disable_container_logging
  @disable_container_logging
end

#display_nameString

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 1784

def display_name
  @display_name
end

#encryption_specGoogle::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1EncryptionSpec

Represents a customer-managed encryption key spec that can be applied to a top- level resource. Corresponds to the JSON property encryptionSpec



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1790

def encryption_spec
  @encryption_spec
end

#end_timeString

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 1796

def end_time
  @end_time
end

#errorGoogle::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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1806

def error
  @error
end

#explanation_specGoogle::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ExplanationSpec

Specification of Model explanation. Corresponds to the JSON property explanationSpec



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1811

def explanation_spec
  @explanation_spec
end

#generate_explanationBoolean 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 1824

def generate_explanation
  @generate_explanation
end

#input_configGoogle::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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1832

def input_config
  @input_config
end

#instance_configGoogle::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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1838

def instance_config
  @instance_config
end

#labelsHash<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 1847

def labels
  @labels
end

#manual_batch_tuning_parametersGoogle::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ManualBatchTuningParameters

Manual batch tuning parameters. Corresponds to the JSON property manualBatchTuningParameters



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1852

def manual_batch_tuning_parameters
  @manual_batch_tuning_parameters
end

#modelString

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/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 1866

def model
  @model
end

#model_monitoring_configGoogle::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelMonitoringConfig

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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1871

def model_monitoring_config
  @model_monitoring_config
end

#model_monitoring_stats_anomaliesArray<Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies>

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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1876

def model_monitoring_stats_anomalies
  @model_monitoring_stats_anomalies
end

#model_monitoring_statusGoogle::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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1886

def model_monitoring_status
  @model_monitoring_status
end

#model_parametersObject

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 1892

def model_parameters
  @model_parameters
end

#model_version_idString

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 1898

def model_version_id
  @model_version_id
end

#nameString

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 1903

def name
  @name
end

#output_configGoogle::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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1910

def output_config
  @output_config
end

#output_infoGoogle::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1BatchPredictionJobOutputInfo

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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1915

def output_info
  @output_info
end

#partial_failuresArray<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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1922

def partial_failures
  @partial_failures
end

#resources_consumedGoogle::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ResourcesConsumed

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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1927

def resources_consumed
  @resources_consumed
end

#service_accountString

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 1936

def 
  @service_account
end

#start_timeString

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 1942

def start_time
  @start_time
end

#stateString

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 1947

def state
  @state
end

#unmanaged_container_modelGoogle::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1UnmanagedContainerModel

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



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 1953

def unmanaged_container_model
  @unmanaged_container_model
end

#update_timeString

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 1958

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 1965

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)
  @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)
  @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