Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1Model
- Inherits:
-
Object
- Object
- Google::Apis::AiplatformV1::GoogleCloudAiplatformV1Model
- 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 more...
Overview
A trained machine learning Model.
Instance Attribute Summary collapse
-
#artifact_uri ⇒ String
Immutable.
-
#base_model_source ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelBaseModelSource
User input field to specify the base model source.
-
#container_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelContainerSpec
Specification of a container for serving predictions.
-
#create_time ⇒ String
Output only.
-
#data_stats ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelDataStats
Stats of data used for train or evaluate the Model.
-
#deployed_models ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1DeployedModelRef>
Output only.
-
#description ⇒ String
The description of the Model.
-
#display_name ⇒ String
Required.
-
#encryption_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1EncryptionSpec
Represents a customer-managed encryption key spec that can be applied to a top- level resource.
-
#etag ⇒ String
Used to perform consistent read-modify-write updates.
-
#explanation_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ExplanationSpec
Specification of Model explanation.
-
#labels ⇒ Hash<String,String>
The labels with user-defined metadata to organize your Models.
-
#metadata ⇒ Object
Immutable.
-
#metadata_artifact ⇒ String
Output only.
-
#metadata_schema_uri ⇒ String
Immutable.
-
#model_source_info ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelSourceInfo
Detail description of the source information of the model.
-
#name ⇒ String
The resource name of the Model.
-
#original_model_info ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelOriginalModelInfo
Contains information about the original Model if this Model is a copy.
-
#pipeline_job ⇒ String
Optional.
-
#predict_schemata ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1PredictSchemata
Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.
-
#satisfies_pzi ⇒ Boolean
(also: #satisfies_pzi?)
Output only.
-
#satisfies_pzs ⇒ Boolean
(also: #satisfies_pzs?)
Output only.
-
#supported_deployment_resources_types ⇒ Array<String>
Output only.
-
#supported_export_formats ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelExportFormat>
Output only.
-
#supported_input_storage_formats ⇒ Array<String>
Output only.
-
#supported_output_storage_formats ⇒ Array<String>
Output only.
-
#training_pipeline ⇒ String
Output only.
-
#update_time ⇒ String
Output only.
-
#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-z
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. Corresponds to the JSON property
versionAliases`. -
#version_create_time ⇒ String
Output only.
-
#version_description ⇒ String
The description of this version.
-
#version_id ⇒ String
Output only.
-
#version_update_time ⇒ String
Output only.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudAiplatformV1Model
constructor
A new instance of GoogleCloudAiplatformV1Model.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudAiplatformV1Model
Returns a new instance of GoogleCloudAiplatformV1Model.
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14402 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14167 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14173 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14181 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14186 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14191 def data_stats @data_stats 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14197 def deployed_models @deployed_models end |
#description ⇒ String
The description of the Model.
Corresponds to the JSON property description
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14202 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14208 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14214 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14220 def etag @etag end |
#explanation_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ExplanationSpec
Specification of Model explanation.
Corresponds to the JSON property explanationSpec
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14225 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14234 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14241 def @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 property
metadataArtifact`
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14249 def @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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14262 def @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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14267 def model_source_info @model_source_info end |
#name ⇒ String
The resource name of the Model.
Corresponds to the JSON property name
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14272 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14277 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14282 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14288 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14293 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14299 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14313 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14319 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14338 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14356 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14362 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14367 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-z
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.
Corresponds to the JSON property
versionAliases`
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14378 def version_aliases @version_aliases end |
#version_create_time ⇒ String
Output only. Timestamp when this version was created.
Corresponds to the JSON property versionCreateTime
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14383 def version_create_time @version_create_time end |
#version_description ⇒ String
The description of this version.
Corresponds to the JSON property versionDescription
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14388 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14395 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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14400 def version_update_time @version_update_time end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 14407 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) @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 |