class_docstr: Creates optimizer-like instances with configuration.
  
  Parameters
  ----------
  OptimizerClass: type
      class of the optimizer to configure, or another ConfiguredOptimizer (config will then be ignored
      except for the optimizer name/representation)
  config: dict
      dictionnary of all the configurations
  as_config: bool
      whether to provide all config as kwargs to the optimizer instantiation (default, see ConfiguredCMA for an example),
      or through a config kwarg referencing self. (if True, see EvolutionStrategy for an example)
  
  Note
  ----
  This provides a default repr which can be bypassed through set_name
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docstr: Loads a pickle and checks that it is an Optimizer.
docstr_tok: ["Loads","a","pickle","and","checks","that","it","is","an","Optimizer","."]
code: def load(self, filepath: tp.Union[str, Path]) -> "Optimizer":
      """Loads a pickle and checks that it is an Optimizer."""
      return self._OptimizerClass.load(filepath)
  
imports: import pickle
  import warnings
  from pathlib import Path
  from numbers import Real
  from collections import deque
  import numpy
  import nevergrad.common.typing
  from nevergrad.parametrization import parameter
  from nevergrad.common import tools
  from nevergrad.common import errors
  from nevergrad.common.decorators import Registry
  from .None import utils
  from .None import multiobjective
label_desc: Use image node_id 6 for calling the ConfiguredOptimizer obj's underlying member method code with example usage: obj.load(filepath) and returns: self