class_docstr: Class for converting a gym environment, a controller style, and others into a black-box optimization benchmark.
class_docstr_tok: ["Class","for","converting","a","gym","environment",",","a","controller","style",",","and","others","into","a","black-box","optimization","benchmark","."]
docstr: Apply an action.
  
  We have a step on top of Gym's step for possibly storing some statistics.
docstr_tok: ["Apply","an","action",".","We","have","a","step","on","top","of","Gym","'s","step","for","possibly","storing","some","statistics","."]
code: def step(self, a, env):
      """Apply an action.
  
      We have a step on top of Gym's step for possibly storing some statistics.
      """
      o, r, done, info = env.step(
          a
      )  # We work on env... we can not have two threads working on the same function.
      return o, r, done, info
  
imports: import os
  import copy
  import scipy.stats
  import typing
  import numpy
  import gym
  import nevergrad
  from nevergrad.parametrization import parameter
  from ..base import ExperimentFunction
label_desc: Use image node_id 12 for calling the GymMulti obj's underlying member method code with example usage: obj.step(a, env) and returns: o,  r,  done,  info