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.



16664
16665
16666
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16664

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) 


16424
16425
16426
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16424

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:



16430
16431
16432
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16430

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:



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

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) 


16443
16444
16445
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16443

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:



16448
16449
16450
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16448

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) 


16453
16454
16455
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16453

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:



16459
16460
16461
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16459

def deployed_models
  @deployed_models
end

#description ⇒ String

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

Returns:

  • (String) 


16464
16465
16466
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16464

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) 


16470
16471
16472
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16470

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:



16476
16477
16478
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16476

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) 


16482
16483
16484
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16482

def etag
  @etag
end

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

Specification of Model explanation. Corresponds to the JSON property explanationSpec

Returns:



16487
16488
16489
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16487

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>) 


16496
16497
16498
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16496

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) 


16503
16504
16505
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16503

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) 


16511
16512
16513
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16511

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) 


16524
16525
16526
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16524

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:



16529
16530
16531
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16529

def model_source_info
  @model_source_info
end

#name ⇒ String

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

Returns:

  • (String) 


16534
16535
16536
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16534

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:



16539
16540
16541
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16539

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) 


16544
16545
16546
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16544

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:



16550
16551
16552
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16550

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) 


16555
16556
16557
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16555

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) 


16561
16562
16563
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16561

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>) 


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

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:



16581
16582
16583
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16581

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>) 


16600
16601
16602
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16600

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>) 


16618
16619
16620
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16618

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) 


16624
16625
16626
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16624

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) 


16629
16630
16631
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16629

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>) 


16640
16641
16642
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16640

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) 


16645
16646
16647
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16645

def version_create_time
  @version_create_time
end

#version_description ⇒ String

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

Returns:

  • (String) 


16650
16651
16652
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16650

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) 


16657
16658
16659
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16657

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) 


16662
16663
16664
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16662

def version_update_time
  @version_update_time
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



16669
16670
16671
16672
16673
16674
16675
16676
16677
16678
16679
16680
16681
16682
16683
16684
16685
16686
16687
16688
16689
16690
16691
16692
16693
16694
16695
16696
16697
16698
16699
16700
16701
16702
16703
16704
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16669

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