azure_ml_sdk.utils.asset_manager
================================

.. py:module:: azure_ml_sdk.utils.asset_manager


Classes
-------

.. autoapisummary::

   azure_ml_sdk.utils.asset_manager.AssetManager


Module Contents
---------------

.. py:class:: AssetManager(ml_client: azure.ai.ml.MLClient, config_dir: str)

   Manage Azure Machine Learning assets for experiments.


   .. py:attribute:: ml_client


   .. py:attribute:: config_dir


   .. py:attribute:: asset_manager_map


   .. py:method:: _check_existing_asset(asset_type: str, name: str, version: Optional[str] = 'latest')

      Check if an asset exists in the workspace.

      :param asset_type: The type of the asset.
      :type asset_type: str
      :param name: The name of the asset.
      :type name: str
      :param version: The version of the asset. Defaults to "latest".
      :type version: str, optional

      :raises ValueError: If the asset or version does not exist.



   .. py:method:: _build_environment_from_config(name: str)

      Build an environment from a config file.

      :param name: The name of the environment.
      :type name: str



   .. py:method:: _build_compute_from_config(name: str)

      Build a compute from a configuration file.

      :param name: The name of the compute.
      :type name: str



   .. py:method:: check_environment(name: str, version: str = 'latest', build: bool = False)

      Check an existing environment in the workspace or build a new one from a config.

      :param name: The name of the environment.
      :type name: str
      :param version: The version of the environment. Defaults to 'latest'.
      :type version: str, optional
      :param build: If true, builds a new environment using a configuration file. Defaults to False.
      :type build: bool, optional

      :raises ValueError: If the specified environment or version does not exist.



   .. py:method:: check_compute(name: str, build: bool = False)

      Check an existing compute in the workspace or build a new one from a config.

      :param name: The name of the compute
      :type name: str
      :param build: If true, build a new compute using a configuration file. Defaults to False.
      :type build: bool, optional

      :raises ValueError: If the specified compute does not exist.



   .. py:method:: check_model(name: str, version: str = 'latest')

      Check an existing model in the workspace.

      :param name: The name of the model.
      :type name: str
      :param version: The version of the model. Defaults to 'latest'.
      :type version: str

      :raises ValueError: If the specified model or version does not exist.



   .. py:method:: check_dataset(name: str, version: str = 'latest')

      Check an existing dataset in the workspace.

      :param name: The name of the dataset.
      :type name: str
      :param version: The version of the model. Defaults to 'latest'.
      :type version: str, optional

      :raises ValueError: If the specified dataset or version does not exist.



   .. py:method:: validate_assets(assets_dict: dict, build_env: bool, build_compute: bool)

      Validate a list of assets. Build new ones from config if demanded.

      :param assets_dict: The dictionary of assets.
      :type assets_dict: dict
      :param build_env: If True, build environments from config file.
      :type build_env: bool
      :param build_compute: If True, build computes from config file.
      :type build_compute: bool