class_docstr: Callback to control the verbosity.
  
  Parameters
  ----------
  n_init : int, optional
      Number of points provided by the user which are yet to be
      evaluated. This is equal to `len(x0)` when `y0` is None
  
  n_random : int, optional
      Number of points randomly chosen.
  
  n_total : int
      Total number of func calls.
  
  Attributes
  ----------
  iter_no : int
      Number of iterations of the optimization routine.
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docstr: Parameters
  ----------
  res : `OptimizeResult`, scipy object
      The optimization as a OptimizeResult object.
docstr_tok: ["Parameters","--","--","--","--","--","res",":","`","OptimizeResult","`",",","scipy","object","The","optimization","as","a","OptimizeResult","object","."]
code: def __call__(self, res):
      """
      Parameters
      ----------
      res : `OptimizeResult`, scipy object
          The optimization as a OptimizeResult object.
      """
      time_taken = time() - self._start_time
      self._print_info(start=False)
  
      curr_y = res.func_vals[-1]
      curr_min = res.fun
  
      print("Time taken: %0.4f" % time_taken)
      print("Function value obtained: %0.4f" % curr_y)
      print("Current minimum: %0.4f" % curr_min)
  
      self.iter_no += 1
      if self.iter_no <= self.n_total:
          self._print_info(start=True)
          self._start_time = time()
  
imports: from time import time
  import numpy
  from guild._skopt.utils import dump
label_desc: Use image node_id 3 for calling the VerboseCallback obj's underlying member method code with example usage: obj.__call__(res) without return types