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: Create an endpoint with the specified target. By default, this method should block until
  creation completes (i.e. until it's possible to create a deployment within the endpoint).
  In the case of conflicts (e.g. if it's not possible to create the specified endpoint
  due to conflict with an existing endpoint), raises a
  :py:class:`mlflow.exceptions.MlflowException`. See target-specific plugin documentation
  for additional detail on support for asynchronous creation and other configuration.
  
  Args:
      name: Unique name to use for endpoint. If another endpoint exists with the same
          name, raises a :py:class:`mlflow.exceptions.MlflowException`.
      config: (optional) Dict containing target-specific configuration for the
          endpoint.
  
  Returns:
      Dict corresponding to created endpoint, which must contain the 'name' key.
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code: def create_endpoint(self, name, config=None):
      """
      Create an endpoint with the specified target. By default, this method should block until
      creation completes (i.e. until it's possible to create a deployment within the endpoint).
      In the case of conflicts (e.g. if it's not possible to create the specified endpoint
      due to conflict with an existing endpoint), raises a
      :py:class:`mlflow.exceptions.MlflowException`. See target-specific plugin documentation
      for additional detail on support for asynchronous creation and other configuration.
  
      Args:
          name: Unique name to use for endpoint. If another endpoint exists with the same
              name, raises a :py:class:`mlflow.exceptions.MlflowException`.
          config: (optional) Dict containing target-specific configuration for the
              endpoint.
  
      Returns:
          Dict corresponding to created endpoint, which must contain the 'name' key.
  
      """
      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 9 for calling the BaseDeploymentClient obj's underlying member method code with example usage: obj.create_endpoint(name, config) without return types