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","."]
code: def softmax(self, a):
      a = np.nan_to_num(
          a, copy=False, nan=-1e20, posinf=1e20, neginf=-1e20
      )
      probabilities = np.exp(a - max(a))
      probabilities = probabilities / sum(probabilities)
      return probabilities
  
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 6 for calling the GymMulti obj's underlying member method code with example usage: obj.softmax(a) and returns: probabilities