class_docstr: Handle for optimizer settings (name, num_workers etc)
  Optimizers can be instantiated through this class, providing the optimization space dimension.
  
  Note
  ----
  Eventually, this class should be moved to be directly used for defining experiments.
code: def __eq__(self, other: tp.Any) -> bool:
      if isinstance(other, self.__class__):
          for attr in self._setting_names:
              x, y = (
                  getattr(settings, attr) for settings in [self, other]
              )
              if x != y:
                  return False
          return True
      return False
  
imports: import sys
  import time
  import random
  import numbers
  import warnings
  import traceback
  import nevergrad.common.typing
  import typing
  import numpy
  from nevergrad.parametrization import parameter
  from nevergrad.common import decorators
  from nevergrad.common import errors
  from ..functions import base
  from ..optimization import base
  from ..optimization.optimizerlib import registry
  from .None import execution
label_desc: Use image node_id 9 for calling the OptimizerSettings obj's underlying member method code with example usage: obj.__eq__(other) and returns: False, True, False