Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1Model

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1/classes.rb,
lib/google/apis/aiplatform_v1/representations.rb,
lib/google/apis/aiplatform_v1/representations.rb

Overview

A trained machine learning Model.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1Model

Returns a new instance of GoogleCloudAiplatformV1Model.



16615
16616
16617
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16615

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

Instance Attribute Details

#artifact_uri ⇒ String

Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not required for AutoML Models. Corresponds to the JSON property artifactUri

Returns:

  • (String) 


16375
16376
16377
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16375

def artifact_uri
  @artifact_uri
end

#base_model_source ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelBaseModelSource

User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models. Corresponds to the JSON property baseModelSource

Returns:



16381
16382
16383
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16381

def base_model_source
  @base_model_source
end

#container_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelContainerSpec

Specification of a container for serving predictions. Some fields in this message correspond to fields in the Kubernetes Container v1 core specification. Corresponds to the JSON property containerSpec

Returns:



16389
16390
16391
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16389

def container_spec
  @container_spec
end

#create_time ⇒ String

Output only. Timestamp when this Model was uploaded into Vertex AI. Corresponds to the JSON property createTime

Returns:

  • (String) 


16394
16395
16396
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16394

def create_time
  @create_time
end

#data_stats ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelDataStats

Stats of data used for train or evaluate the Model. Corresponds to the JSON property dataStats

Returns:



16399
16400
16401
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16399

def data_stats
  @data_stats
end

#default_checkpoint_id ⇒ String

The default checkpoint id of a model version. Corresponds to the JSON property defaultCheckpointId

Returns:

  • (String) 


16404
16405
16406
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16404

def default_checkpoint_id
  @default_checkpoint_id
end

#deployed_models ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1DeployedModelRef>

Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations. Corresponds to the JSON property deployedModels

Returns:



16410
16411
16412
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16410

def deployed_models
  @deployed_models
end

#description ⇒ String

The description of the Model. Corresponds to the JSON property description

Returns:

  • (String) 


16415
16416
16417
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16415

def description
  @description
end

#display_name ⇒ String

Required. The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters. Corresponds to the JSON property displayName

Returns:

  • (String) 


16421
16422
16423
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16421

def display_name
  @display_name
end

#encryption_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1EncryptionSpec

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

Returns:



16427
16428
16429
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16427

def encryption_spec
  @encryption_spec
end

#etag ⇒ String

Used to perform consistent read-modify-write updates. If not set, a blind " overwrite" update happens. Corresponds to the JSON property etag

Returns:

  • (String) 


16433
16434
16435
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16433

def etag
  @etag
end

#explanation_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ExplanationSpec

Specification of Model explanation. Corresponds to the JSON property explanationSpec

Returns:



16438
16439
16440
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16438

def explanation_spec
  @explanation_spec
end

#labels ⇒ Hash<String,String>

The labels with user-defined metadata to organize your Models. 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>) 


16447
16448
16449
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16447

def labels
  @labels
end

#metadata ⇒ Object

Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information. Corresponds to the JSON property metadata

Returns:

  • (Object) 


16454
16455
16456
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16454

def metadata
  @metadata
end

#metadata_artifact ⇒ String

Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is projects/project/locations/location/metadataStores/metadata_store/ artifacts/artifact`. Corresponds to the JSON propertymetadataArtifact`

Returns:

  • (String) 


16462
16463
16464
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16462

def metadata_artifact
  @metadata_artifact
end

#metadata_schema_uri ⇒ String

Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 Schema Object. AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access. Corresponds to the JSON property metadataSchemaUri

Returns:

  • (String) 


16475
16476
16477
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16475

def metadata_schema_uri
  @metadata_schema_uri
end

#model_source_info ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelSourceInfo

Detail description of the source information of the model. Corresponds to the JSON property modelSourceInfo

Returns:



16480
16481
16482
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16480

def model_source_info
  @model_source_info
end

#name ⇒ String

The resource name of the Model. Corresponds to the JSON property name

Returns:

  • (String) 


16485
16486
16487
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16485

def name
  @name
end

#original_model_info ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelOriginalModelInfo

Contains information about the original Model if this Model is a copy. Corresponds to the JSON property originalModelInfo

Returns:



16490
16491
16492
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16490

def original_model_info
  @original_model_info
end

#pipeline_job ⇒ String

Optional. This field is populated if the model is produced by a pipeline job. Corresponds to the JSON property pipelineJob

Returns:

  • (String) 


16495
16496
16497
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16495

def pipeline_job
  @pipeline_job
end

#predict_schemata ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1PredictSchemata

Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob. Corresponds to the JSON property predictSchemata

Returns:



16501
16502
16503
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16501

def predict_schemata
  @predict_schemata
end

#satisfies_pzi ⇒ Boolean Also known as: satisfies_pzi?

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

Returns:

  • (Boolean) 


16506
16507
16508
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16506

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) 


16512
16513
16514
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16512

def satisfies_pzs
  @satisfies_pzs
end

#supported_deployment_resources_types ⇒ Array<String>

Output only. When this Model is deployed, its prediction resources are described by the prediction_resources field of the Endpoint.deployed_models object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an Endpoint and does not support online predictions (PredictionService.Predict or PredictionService. Explain). Such a Model can serve predictions by using a BatchPredictionJob, if it has at least one entry each in supported_input_storage_formats and supported_output_storage_formats. Corresponds to the JSON property supportedDeploymentResourcesTypes

Returns:

  • (Array<String>) 


16526
16527
16528
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16526

def supported_deployment_resources_types
  @supported_deployment_resources_types
end

#supported_export_formats ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelExportFormat>

Output only. The formats in which this Model may be exported. If empty, this Model is not available for export. Corresponds to the JSON property supportedExportFormats

Returns:



16532
16533
16534
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16532

def supported_export_formats
  @supported_export_formats
end

#supported_input_storage_formats ⇒ Array<String>

Output only. The formats this Model supports in BatchPredictionJob. input_config. If PredictSchemata.instance_schema_uri exists, the instances should be given as per that schema. The possible formats are: * jsonl The JSON Lines format, where each instance is a single line. Uses GcsSource. * csv The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsSource. * tf-record The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource. * tf-record-gzip Similar to tf-record, but the file is gzipped. Uses GcsSource. * bigquery Each instance is a single row in BigQuery. Uses BigQuerySource. * file-list Each line of the file is the location of an instance to process, uses gcs_source field of the InputConfig object. If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain. Corresponds to the JSON property supportedInputStorageFormats

Returns:

  • (Array<String>) 


16551
16552
16553
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16551

def supported_input_storage_formats
  @supported_input_storage_formats
end

#supported_output_storage_formats ⇒ Array<String>

Output only. The formats this Model supports in BatchPredictionJob. output_config. If both PredictSchemata.instance_schema_uri and PredictSchemata. prediction_schema_uri exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * jsonl The JSON Lines format, where each prediction is a single line. Uses GcsDestination. * csv The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsDestination. * bigquery Each prediction is a single row in a BigQuery table, uses BigQueryDestination . If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain. Corresponds to the JSON property supportedOutputStorageFormats

Returns:

  • (Array<String>) 


16569
16570
16571
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16569

def supported_output_storage_formats
  @supported_output_storage_formats
end

#training_pipeline ⇒ String

Output only. The resource name of the TrainingPipeline that uploaded this Model, if any. Corresponds to the JSON property trainingPipeline

Returns:

  • (String) 


16575
16576
16577
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16575

def training_pipeline
  @training_pipeline
end

#update_time ⇒ String

Output only. Timestamp when this Model was most recently updated. Corresponds to the JSON property updateTime

Returns:

  • (String) 


16580
16581
16582
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16580

def update_time
  @update_time
end

#version_aliases ⇒ Array<String>

User provided version aliases so that a model version can be referenced via alias (i.e. projects/project/locations/location/models/model_id@ version_alias`instead of auto-generated version id (i.e.projects/project/ locations/location/models/model_id@version_id). The format is a-z0,126 [a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model. Corresponds to the JSON propertyversionAliases`

Returns:

  • (Array<String>) 


16591
16592
16593
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16591

def version_aliases
  @version_aliases
end

#version_create_time ⇒ String

Output only. Timestamp when this version was created. Corresponds to the JSON property versionCreateTime

Returns:

  • (String) 


16596
16597
16598
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16596

def version_create_time
  @version_create_time
end

#version_description ⇒ String

The description of this version. Corresponds to the JSON property versionDescription

Returns:

  • (String) 


16601
16602
16603
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16601

def version_description
  @version_description
end

#version_id ⇒ String

Output only. Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation. Corresponds to the JSON property versionId

Returns:

  • (String) 


16608
16609
16610
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16608

def version_id
  @version_id
end

#version_update_time ⇒ String

Output only. Timestamp when this version was most recently updated. Corresponds to the JSON property versionUpdateTime

Returns:

  • (String) 


16613
16614
16615
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16613

def version_update_time
  @version_update_time
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



16620
16621
16622
16623
16624
16625
16626
16627
16628
16629
16630
16631
16632
16633
16634
16635
16636
16637
16638
16639
16640
16641
16642
16643
16644
16645
16646
16647
16648
16649
16650
16651
16652
16653
16654
16655
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16620

def update!(**args)
  @artifact_uri = args[:artifact_uri] if args.key?(:artifact_uri)
  @base_model_source = args[:base_model_source] if args.key?(:base_model_source)
  @container_spec = args[:container_spec] if args.key?(:container_spec)
  @create_time = args[:create_time] if args.key?(:create_time)
  @data_stats = args[:data_stats] if args.key?(:data_stats)
  @default_checkpoint_id = args[:default_checkpoint_id] if args.key?(:default_checkpoint_id)
  @deployed_models = args[:deployed_models] if args.key?(:deployed_models)
  @description = args[:description] if args.key?(:description)
  @display_name = args[:display_name] if args.key?(:display_name)
  @encryption_spec = args[:encryption_spec] if args.key?(:encryption_spec)
  @etag = args[:etag] if args.key?(:etag)
  @explanation_spec = args[:explanation_spec] if args.key?(:explanation_spec)
  @labels = args[:labels] if args.key?(:labels)
  @metadata = args[:metadata] if args.key?(:metadata)
  @metadata_artifact = args[:metadata_artifact] if args.key?(:metadata_artifact)
  @metadata_schema_uri = args[:metadata_schema_uri] if args.key?(:metadata_schema_uri)
  @model_source_info = args[:model_source_info] if args.key?(:model_source_info)
  @name = args[:name] if args.key?(:name)
  @original_model_info = args[:original_model_info] if args.key?(:original_model_info)
  @pipeline_job = args[:pipeline_job] if args.key?(:pipeline_job)
  @predict_schemata = args[:predict_schemata] if args.key?(:predict_schemata)
  @satisfies_pzi = args[:satisfies_pzi] if args.key?(:satisfies_pzi)
  @satisfies_pzs = args[:satisfies_pzs] if args.key?(:satisfies_pzs)
  @supported_deployment_resources_types = args[:supported_deployment_resources_types] if args.key?(:supported_deployment_resources_types)
  @supported_export_formats = args[:supported_export_formats] if args.key?(:supported_export_formats)
  @supported_input_storage_formats = args[:supported_input_storage_formats] if args.key?(:supported_input_storage_formats)
  @supported_output_storage_formats = args[:supported_output_storage_formats] if args.key?(:supported_output_storage_formats)
  @training_pipeline = args[:training_pipeline] if args.key?(:training_pipeline)
  @update_time = args[:update_time] if args.key?(:update_time)
  @version_aliases = args[:version_aliases] if args.key?(:version_aliases)
  @version_create_time = args[:version_create_time] if args.key?(:version_create_time)
  @version_description = args[:version_description] if args.key?(:version_description)
  @version_id = args[:version_id] if args.key?(:version_id)
  @version_update_time = args[:version_update_time] if args.key?(:version_update_time)
end