FeatureStore 類別
- 繼承
-
azure.ai.ml.entities._workspace.workspace.WorkspaceFeatureStore
建構函式
FeatureStore(*, name: str, compute_runtime: ComputeRuntime | None = None, offline_store: MaterializationStore | None = None, online_store: MaterializationStore | None = None, materialization_identity: ManagedIdentityConfiguration | None = None, description: str | None = None, tags: Dict[str, str] | None = None, display_name: str | None = None, location: str | None = None, resource_group: str | None = None, hbi_workspace: bool = False, storage_account: str | None = None, container_registry: str | None = None, key_vault: str | None = None, application_insights: str | None = None, customer_managed_key: CustomerManagedKey | None = None, image_build_compute: str | None = None, public_network_access: str | None = None, identity: IdentityConfiguration | None = None, primary_user_assigned_identity: str | None = None, managed_network: ManagedNetwork | None = None, **kwargs)
參數
- hbi_workspace
- bool
必要
客戶資料是否為高度業務衝擊 (HBI),包含敏感性商務資訊。 如需詳細資訊,請參閱https://docs.microsoft.com/azure/machine-learning/concept-data-encryption#encryption-at-rest。
方法
dump |
以 yaml 格式將工作區規格傾印到檔案中。 |
dump
以 yaml 格式將工作區規格傾印到檔案中。
dump(dest: str | PathLike | IO, **kwargs) -> None
參數
屬性
base_path
creation_context
discovery_url
id
mlflow_tracking_uri
意見反應
https://aka.ms/ContentUserFeedback。
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