docstr: Branin function
  
  Parameters
  ----------
  config : Configuration
      Contains two continuous hyperparameters, x0 and x1
  seed : int, optional
      Not used, by default 0
  
  Returns
  -------
  float
      Branin function value
docstr_tok: ["Branin","function","Parameters","--","--","--","--","--","config",":","Configuration","Contains","two","continuous","hyperparameters",",","x0","and","x1","seed",":","int",",","optional","Not","used",",","by","default","0","Returns","--","--","--","-","float","Branin","function","value"]
code: def train(self, config: Configuration, seed: int = 0) -> float:
      """Branin function
  
      Parameters
      ----------
      config : Configuration
          Contains two continuous hyperparameters, x0 and x1
      seed : int, optional
          Not used, by default 0
  
      Returns
      -------
      float
          Branin function value
      """
      x0 = config["x0"]
      x1 = config["x1"]
      a = 1.0
      b = 5.1 / (4.0 * np.pi**2)
      c = 5.0 / np.pi
      r = 6.0
      s = 10.0
      t = 1.0 / (8.0 * np.pi)
      ret = (
          a * (x1 - b * x0**2 + c * x0 - r) ** 2
          + s * (1 - t) * np.cos(x0)
          + s
      )
  
      return ret
  
file_path: SMAC3/examples/1_basics/7_parallelization_cluster.py
imports: import numpy
  from ConfigSpace import Configuration, ConfigurationSpace, Float
  from dask.distributed import Client
  from dask_jobqueue import SLURMCluster
  from smac import BlackBoxFacade, Scenario
label_desc: Use image node_id 2 for calling the Branin obj's underlying member method code with example usage: obj.train(config, seed) and returns: ret