Model class final

A trained machine learning Model.

Inheritance

Constructors

Model({String name = '', String versionId = '', List<String> versionAliases = const [], Timestamp? versionCreateTime, Timestamp? versionUpdateTime, required String displayName, String description = '', String versionDescription = '', String defaultCheckpointId = '', PredictSchemata? predictSchemata, String metadataSchemaUri = '', Value? metadata, List<Model_ExportFormat> supportedExportFormats = const [], String trainingPipeline = '', ModelContainerSpec? containerSpec, String artifactUri = '', List<Model_DeploymentResourcesType> supportedDeploymentResourcesTypes = const [], List<String> supportedInputStorageFormats = const [], List<String> supportedOutputStorageFormats = const [], Timestamp? createTime, Timestamp? updateTime, List<DeployedModelRef> deployedModels = const [], ExplanationSpec? explanationSpec, String etag = '', Map<String, String> labels = const {}, EncryptionSpec? encryptionSpec, ModelSourceInfo? modelSourceInfo, Model_OriginalModelInfo? originalModelInfo, String metadataArtifact = '', Model_BaseModelSource? baseModelSource, bool satisfiesPzs = false, bool satisfiesPzi = false, List<Checkpoint> checkpoints = const []})
Model.fromJson(Object? j)
factory

Properties

artifactUri → String
Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not required for AutoML Models.
final
baseModelSource → Model_BaseModelSource?
Optional. User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models.
final
checkpoints → List<Checkpoint>
Optional. Output only. The checkpoints of the model.
final
containerSpec → ModelContainerSpec?
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.
final
createTime → Timestamp?
Output only. Timestamp when this Model was uploaded into Vertex AI.
final
defaultCheckpointId → String
The default checkpoint id of a model version.
final
deployedModels → List<DeployedModelRef>
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
final
description → String
The description of the Model.
final
displayName → 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.
final
encryptionSpec → EncryptionSpec?
Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
final
etag → String
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
final
explanationSpec → ExplanationSpec?
The default explanation specification for this Model.
final
hashCode → int
The hash code for this object.
no setterinherited
labels → Map<String, String>
The labels with user-defined metadata to organize your Models.
final
metadata → Value?
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.
final
metadataArtifact → 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}.
final
metadataSchemaUri → 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.
final
modelSourceInfo → ModelSourceInfo?
Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden.
final
name → String
The resource name of the Model.
final
originalModelInfo → Model_OriginalModelInfo?
Output only. If this Model is a copy of another Model, this contains info about the original.
final
predictSchemata → PredictSchemata?
The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
final
qualifiedName → String
The fully qualified name of this message, i.e., google.protobuf.Duration or google.rpc.ErrorInfo.
finalinherited
runtimeType → Type
A representation of the runtime type of the object.
no setterinherited
satisfiesPzi → bool
Output only. Reserved for future use.
final
satisfiesPzs → bool
Output only. Reserved for future use.
final
supportedDeploymentResourcesTypes → List<Model_DeploymentResourcesType>
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.
final
supportedExportFormats → List<Model_ExportFormat>
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
final
supportedInputStorageFormats → List<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.
final
supportedOutputStorageFormats → List<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).
final
trainingPipeline → String
Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.
final
updateTime → Timestamp?
Output only. Timestamp when this Model was most recently updated.
final
versionAliases → List<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-zA-Z0-9-{0,126}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.
final
versionCreateTime → Timestamp?
Output only. Timestamp when this version was created.
final
versionDescription → String
The description of this version.
final
versionId → 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.
final
versionUpdateTime → Timestamp?
Output only. Timestamp when this version was most recently updated.
final

Methods

noSuchMethod(Invocation invocation) → dynamic
Invoked when a nonexistent method or property is accessed.
inherited
toJson() → Object
override
toString() → String
A string representation of this object.
override

Operators

operator ==(Object other) → bool
The equality operator.
inherited

Constants

fullyQualifiedName → const String