class_docstr: Samples data from linearly parameterized arms.
  
  The reward for context X and arm i is given by X^T * theta_i, for some
  latent set of parameters {theta_i : i = 1, ..., k}.
  The thetas are sampled uniformly at random, the contexts are Gaussian,
  and Gaussian noise is added to the rewards.
class_docstr_tok: ["Samples","data","from","linearly","parameterized","arms",".","The","reward","for","context","X","and","arm","i","is","given","by","X^T","*","theta_i",",","for","some","latent","set","of","parameters","{","theta_i",":","i","=","1",",","...",",","k","}",".","The","thetas","are","sampled","uniformly","at","random",",","the","contexts","are","Gaussian",",","and","Gaussian","noise","is","added","to","the","rewards","."]
code: def render(self, mode="human"):
      raise NotImplementedError
  
imports: import copy
  import random
  import gymnasium
  import numpy
  from gymnasium.spaces import Box, Discrete
label_desc: Use image node_id 5 for calling the LinearDiscreteEnv obj's underlying member method code with example usage: obj.render(mode) without return types