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 endpoint, throwing a
  py:class:`mlflow.exception.MlflowException` if no endpoint exists with the provided
  name.
  The dict is guaranteed to contain an 'name' key containing the endpoint name.
  The other fields of the returned dictionary and their types may vary across targets.
  
  Args:
      endpoint: Name of endpoint to fetch
  
  Returns:
      A dict corresponding to the retrieved endpoint. The dict is guaranteed to
      contain a 'name' key corresponding to the endpoint name. The other fields of
      the returned dictionary and their types may vary across targets.
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code: def get_endpoint(self, endpoint):
      """
      Returns a dictionary describing the specified endpoint, throwing a
      py:class:`mlflow.exception.MlflowException` if no endpoint exists with the provided
      name.
      The dict is guaranteed to contain an 'name' key containing the endpoint name.
      The other fields of the returned dictionary and their types may vary across targets.
  
      Args:
          endpoint: Name of endpoint to fetch
  
      Returns:
          A dict corresponding to the retrieved endpoint. The dict is guaranteed to
          contain a 'name' key corresponding to the endpoint name. The other fields of
          the returned dictionary and their types may vary across targets.
      """
      raise MlflowException(
          "Method is unimplemented in base client. Implementation should be "
          "provided by specific target plugins."
      )
  
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 13 for calling the BaseDeploymentClient obj's underlying member method code with example usage: obj.get_endpoint(endpoint) without return types