class_docstr: Ackley function 
  
  :param sd: standard deviation, to generate noisy evaluations of the function.
code: def __init__(self, input_dim, bounds=None, sd=None):
      self.input_dim = input_dim
  
      if bounds is None:
          self.bounds = [(-32.768, 32.768)] * self.input_dim
      else:
          self.bounds = bounds
  
      self.min = [(0.0) * self.input_dim]
      self.fmin = 0
  
      if sd == None:
          self.sd = 0
      else:
          self.sd = sd
  
file_path: GPyOpt/GPyOpt/objective_examples/experimentsNd.py
imports: import numpy
  from ..util.general import reshape
label_desc: Use image node_id 1 to create a new ackley object  with example: obj = ackley(input_dim, bounds, sd)