class_docstr: Base class exposing Python model deployment APIs.
  
  Plugin implementors should define target-specific deployment logic via a subclass of
  ``BaseDeploymentClient`` within the plugin module, and customize method docstrings with
  target-specific information.
  
  .. Note::
      Subclasses should raise :py:class:`mlflow.exceptions.MlflowException` in error cases (e.g.
      on failure to deploy a model).
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docstr: Returns a dictionary describing the specified deployment, throwing a
  :py:class:`mlflow.exceptions.MlflowException` if no deployment exists with the provided
  ID.
  The dict is guaranteed to contain an 'name' key containing the deployment name.
  The other fields of the returned dictionary and their types may vary across
  deployment targets.
  
  Args:
      name: ID of deployment to fetch.
      endpoint: (optional) Endpoint containing the deployment to get. May not be
          supported by all targets.
  
  Returns:
      A dict corresponding to the retrieved deployment. The dict is guaranteed to
      contain a 'name' key corresponding to the deployment name. The other fields of
      the returned dictionary and their types may vary across targets.
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code: def get_deployment(self, name, endpoint=None):
      """
      Returns a dictionary describing the specified deployment, throwing a
      :py:class:`mlflow.exceptions.MlflowException` if no deployment exists with the provided
      ID.
      The dict is guaranteed to contain an 'name' key containing the deployment name.
      The other fields of the returned dictionary and their types may vary across
      deployment targets.
  
      Args:
          name: ID of deployment to fetch.
          endpoint: (optional) Endpoint containing the deployment to get. May not be
              supported by all targets.
  
      Returns:
          A dict corresponding to the retrieved deployment. The dict is guaranteed to
          contain a 'name' key corresponding to the deployment name. The other fields of
          the returned dictionary and their types may vary across targets.
      """
      pass
  
file_path: mlflow/mlflow/deployments/base.py
imports: import abc
  from mlflow.exceptions import MlflowException
  from mlflow.utils.annotations import developer_stable
label_desc: Use image node_id 6 for calling the BaseDeploymentClient obj's underlying member method code with example usage: obj.get_deployment(name, endpoint) without return types