code: def bounds_to_space(bounds):
      
      space = []
      for k in range(len(bounds)):
          space += [{'name': 'var_'+str(k+1), 'type': 'continuous', 'domain':bounds[k], 'dimensionality':1}]
      return space
docs: Takes as input a list of tuples with bounds, and create a dictionary to be processed by the class Design_space. This function
      us used to keep the compatibility with previous versions of GPyOpt in which only bounded continuous optimization was possible
      (and the optimization domain passed as a list of tuples).