Class Model (2.32.0)

Model(model_ref)

Model represents a machine learning model resource.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/models

Parameter

NameDescription
model_ref Union[google.cloud.bigquery.model.ModelReference, str]

A pointer to a model. If model_ref is a string, it must included a project ID, dataset ID, and model ID, each separated by ..

Inheritance

builtins.object > Model

Properties

created

Union[datetime.datetime, None]: Datetime at which the model was created (:data:None until set from the server).

Read-only.

dataset_id

str: ID of dataset containing the model.

description

Optional[str]: Description of the model (defaults to :data:None).

encryption_configuration

Optional[google.cloud.bigquery.encryption_configuration.EncryptionConfiguration]: Custom encryption configuration for the model.

Custom encryption configuration (e.g., Cloud KMS keys) or :data:None if using default encryption.

See protecting data with Cloud KMS keys <https://cloud.google.com/bigquery/docs/customer-managed-encryption>;_ in the BigQuery documentation.

etag

str: ETag for the model resource (:data:None until set from the server).

Read-only.

expires

Union[datetime.datetime, None]: The datetime when this model expires. If not present, the model will persist indefinitely. Expired models will be deleted and their storage reclaimed.

feature_columns

Sequence[google.cloud.bigquery_v2.types.StandardSqlField]: Input feature columns that were used to train this model.

Read-only.

An iterable of StandardSqlField.

friendly_name

Optional[str]: Title of the table (defaults to :data:None).

Exceptions
TypeDescription
ValueErrorFor invalid value types.

label_columns

Sequence[google.cloud.bigquery_v2.types.StandardSqlField]: Label columns that were used to train this model. The output of the model will have a predicted_ prefix to these columns.

Read-only.

An iterable of StandardSqlField.

labels

Optional[Dict[str, str]]: Labels for the table.

This method always returns a dict. To change a model's labels, modify the dict, then call Client.update_model. To delete a label, set its value to :data:None before updating.

location

str: The geographic location where the model resides. This value is inherited from the dataset.

Read-only.

model_id

str: The model ID.

model_type

google.cloud.bigquery_v2.types.Model.ModelType: Type of the model resource.

Read-only.

The value is one of elements of the ModelType enumeration.

modified

Union[datetime.datetime, None]: Datetime at which the model was last modified (:data:None until set from the server).

Read-only.

path

str: URL path for the model's APIs.

project

str: Project bound to the model

reference

A xref_ModelReference pointing to this model.

Read-only.

Returns
TypeDescription
google.cloud.bigquery.model.ModelReferencepointer to this model.

training_runs

Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun]: Information for all training runs in increasing order of start time.

Read-only.

An iterable of TrainingRun.

Methods

from_api_repr

from_api_repr(resource: dict)

Factory: construct a model resource given its API representation

Parameter
NameDescription
resource Dict[str, object]

Model resource representation from the API

Returns
TypeDescription
google.cloud.bigquery.model.ModelModel parsed from ``resource``.

to_api_repr

to_api_repr()

Construct the API resource representation of this model.

Returns
TypeDescription
Dict[str, object]Model reference represented as an API resource

__init__

__init__(model_ref)

Initialize self. See help(type(self)) for accurate signature.

Model

Model(model_ref)

Model represents a machine learning model resource.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/models

Parameter
NameDescription
model_ref Union[google.cloud.bigquery.model.ModelReference, str]

A pointer to a model. If model_ref is a string, it must included a project ID, dataset ID, and model ID, each separated by ..