Struct google_cloud_bigquery::http::model::Model

pub struct Model {

    pub etag: String,
    pub model_reference: ModelReference,
    pub creation_time: i64,
    pub last_modified_time: u64,
    pub description: Option<String>,
    pub friendly_name: Option<String>,
    pub labels: Option<HashMap<String, String>>,
    pub expiration_time: Option<i64>,
    pub location: Option<String>,
    pub encryption_configuration: Option<EncryptionConfiguration>,
    pub model_type: Option<ModelType>,
    pub training_runs: Option<Vec<TrainingRun>>,
    pub feature_columns: Option<Vec<StandardSqlField>>,
    pub label_columns: Option<Vec<StandardSqlField>>,
    pub hparam_search_spaces: Option<HparamSearchSpaces>,
    pub default_trial_id: Option<i64>,
    pub hparam_trials: Option<Vec<HparamTuningTrial>>,
    pub optimal_trial_ids: Option<Vec<i64>>,
    pub remote_model_info: Option<RemoteModelInfo>,
}

Fields

etag: String

Output only. A hash of this resource.

model_reference: ModelReference

Required. Unique identifier for this model.

creation_time: i64

Output only. The time when this model was created, in millisecs since the epoch.

last_modified_time: u64

Output only. The time when this model was last modified, in millisecs since the epoch.

description: Option<String>

Optional. A user-friendly description of this model.

friendly_name: Option<String>

Optional. A descriptive name for this model.

labels: Option<HashMap<String, String>>

The labels associated with this model. You can use these to organize and group your models. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key. An object containing a list of “key”: value pairs. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

expiration_time: Option<i64>

Optional. The time when this model expires, in milliseconds since the epoch. If not present, the model will persist indefinitely. Expired models will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created models.

location: Option<String>

Output only. The geographic location where the model resides. This value is inherited from the dataset.

encryption_configuration: Option<EncryptionConfiguration>

Custom encryption configuration (e.g., Cloud KMS keys). This shows the encryption configuration of the model data while stored in BigQuery storage. This field can be used with models.patch to update encryption key for an already encrypted model.

model_type: Option<ModelType>

Output only. Type of the model resource.

training_runs: Option<Vec<TrainingRun>>

Information for all training runs in increasing order of startTime.

feature_columns: Option<Vec<StandardSqlField>>

Output only. Input feature columns that were used to train this model.

label_columns: Option<Vec<StandardSqlField>>

Output only. Label columns that were used to train this model. The output of the model will have a “predicted_” prefix to these columns.

hparam_search_spaces: Option<HparamSearchSpaces>

Output only. All hyperparameter search spaces in this model.

default_trial_id: Option<i64>

Output only. The default trialId to use in TVFs when the trialId is not passed in. For single-objective hyperparameter tuning models, this is the best trial ID. For multi-objective hyperparameter tuning models, this is the smallest trial ID among all Pareto optimal trials.

hparam_trials: Option<Vec<HparamTuningTrial>>

Output only. Trials of a hyperparameter tuning model sorted by trialId.

optimal_trial_ids: Option<Vec<i64>>

Output only. For single-objective hyperparameter tuning models, it only contains the best trial. For multi-objective hyperparameter tuning models, it contains all Pareto optimal trials sorted by trialId.

remote_model_info: Option<RemoteModelInfo>

Output only. Remote model info

Trait Implementations

impl Clone for Model

fn clone(&self) -> Model

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Model

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for Model

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq<Model> for Model

fn eq(&self, other: &Model) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for Model

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for Model