Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1Model

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 trained machine learning Model.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1Model

Returns a new instance of GoogleCloudAiplatformV1beta1Model.



11644
11645
11646
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11644

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 present for AutoML Models or Large Models. Corresponds to the JSON property artifactUri

Returns:

  • (String) 


11437
11438
11439
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11437

def artifact_uri
  @artifact_uri
end

#container_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelContainerSpec

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:



11445
11446
11447
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11445

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) 


11450
11451
11452
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11450

def create_time
  @create_time
end

#deployed_models ⇒ Array<Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1DeployedModelRef>

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:



11456
11457
11458
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11456

def deployed_models
  @deployed_models
end

#description ⇒ String

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

Returns:

  • (String) 


11461
11462
11463
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11461

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) 


11467
11468
11469
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11467

def display_name
  @display_name
end

#encryption_spec ⇒ Google::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

Returns:



11473
11474
11475
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11473

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) 


11479
11480
11481
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11479

def etag
  @etag
end

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

Specification of Model explanation. Corresponds to the JSON property explanationSpec

Returns:



11484
11485
11486
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11484

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>) 


11493
11494
11495
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11493

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) 


11500
11501
11502
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11500

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) 


11508
11509
11510
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11508

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) 


11521
11522
11523
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11521

def metadata_schema_uri
  @metadata_schema_uri
end

#model_source_info ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelSourceInfo

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

Returns:



11526
11527
11528
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11526

def model_source_info
  @model_source_info
end

#name ⇒ String

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

Returns:

  • (String) 


11531
11532
11533
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11531

def name
  @name
end

#original_model_info ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelOriginalModelInfo

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

Returns:



11536
11537
11538
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11536

def original_model_info
  @original_model_info
end

#predict_schemata ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1PredictSchemata

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

Returns:



11542
11543
11544
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11542

def predict_schemata
  @predict_schemata
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>) 


11555
11556
11557
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11555

def supported_deployment_resources_types
  @supported_deployment_resources_types
end

#supported_export_formats ⇒ Array<Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelExportFormat>

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:



11561
11562
11563
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11561

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>) 


11580
11581
11582
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11580

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>) 


11598
11599
11600
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11598

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) 


11604
11605
11606
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11604

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) 


11609
11610
11611
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11609

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>) 


11620
11621
11622
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11620

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) 


11625
11626
11627
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11625

def version_create_time
  @version_create_time
end

#version_description ⇒ String

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

Returns:

  • (String) 


11630
11631
11632
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11630

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) 


11637
11638
11639
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11637

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) 


11642
11643
11644
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11642

def version_update_time
  @version_update_time
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



11649
11650
11651
11652
11653
11654
11655
11656
11657
11658
11659
11660
11661
11662
11663
11664
11665
11666
11667
11668
11669
11670
11671
11672
11673
11674
11675
11676
11677
11678
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 11649

def update!(**args)
  @artifact_uri = args[:artifact_uri] if args.key?(:artifact_uri)
  @container_spec = args[:container_spec] if args.key?(:container_spec)
  @create_time = args[:create_time] if args.key?(:create_time)
  @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)
  @predict_schemata = args[:predict_schemata] if args.key?(:predict_schemata)
  @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