code: def run_local(target, name, model_uri, flavor=None, config=None):
      """Deploys the specified model locally, for testing. Note that models deployed locally cannot
      be managed by other deployment APIs (e.g. ``update_deployment``, ``delete_deployment``, etc).
  
      Args:
          target: Target to deploy to.
          name: Name to use for deployment
          model_uri: URI of model to deploy
          flavor: (optional) Model flavor to deploy. If unspecified, a default flavor
              will be chosen.
          config: (optional) Dict containing updated target-specific configuration for
              the deployment
  
      Returns:
          None
      """
      return plugin_store[target].run_local(
          name, model_uri, flavor, config
      )
  
file_path: mlflow/mlflow/deployments/interface.py
imports: import inspect
  from logging import Logger
  from mlflow.deployments.base import BaseDeploymentClient
  from mlflow.deployments.plugin_manager import DeploymentPlugins
  from mlflow.deployments.utils import get_deployments_target, parse_target_uri
  from mlflow.exceptions import MlflowException
label_desc: Use image node_id 2 for calling a global function with example usage: run_local(target, name, model_uri, flavor, config) and returns: plugin_store