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: Compute predictions on inputs using the specified deployment or model endpoint.
  
  Note that the input/output types of this method match those of `mlflow pyfunc predict`.
  
  Args:
      deployment_name: Name of deployment to predict against.
      inputs: Input data (or arguments) to pass to the deployment or model endpoint for
          inference.
      endpoint: Endpoint to predict against. May not be supported by all targets.
  
  Returns:
      A :py:class:`mlflow.deployments.PredictionsResponse` instance representing the
      predictions and associated Model Server response metadata.
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code: def predict(self, deployment_name=None, inputs=None, endpoint=None):
      """Compute predictions on inputs using the specified deployment or model endpoint.
  
      Note that the input/output types of this method match those of `mlflow pyfunc predict`.
  
      Args:
          deployment_name: Name of deployment to predict against.
          inputs: Input data (or arguments) to pass to the deployment or model endpoint for
              inference.
          endpoint: Endpoint to predict against. May not be supported by all targets.
  
      Returns:
          A :py:class:`mlflow.deployments.PredictionsResponse` instance representing the
          predictions and associated Model Server response metadata.
  
      """
      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 7 for calling the BaseDeploymentClient obj's underlying member method code with example usage: obj.predict(deployment_name, inputs, endpoint) without return types