class_docstr: Wrapper over Pymoo optimizer implementations, in standard ask and tell format.
  This is actually an import from Pymoo Optimize.
  
  Parameters
  ----------
  algorithm: str
  
      Use "algorithm-name" with following names to access algorithm classes:
      Single-Objective
      -"de"
      -'ga'
      -"brkga"
      -"nelder-mead"
      -"pattern-search"
      -"cmaes"
      Multi-Objective
      -"nsga2"
      Multi-Objective requiring reference directions, points or lines
      -"rnsga2"
      -"nsga3"
      -"unsga3"
      -"rnsga3"
      -"moead"
      -"ctaea"
  
  Note
  ----
  These optimizers do not support asking several candidates in a row
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code: def __init__(self, *, algorithm: str) -> None:
      super().__init__(_PymooBatchMinimizeBase, locals())
  
imports: import functools
  import math
  import warnings
  import weakref
  import numpy
  from scipy import optimize
  import nevergrad.common.typing
  from nevergrad.parametrization import parameter
  from nevergrad.common import errors
  from .None import base
  from .base import IntOrParameter
  from .None import recaster
label_desc: Use image node_id 1 to create a new PymooBatch object from inherited base classes: base with example: obj = PymooBatch()