code: def conformant_planning(
      seed: tp.Optional[int] = None,
  ) -> tp.Iterator[Experiment]:
      # You might modify this problem by specifying an environment variable.
      specific_problem = "EnergySavingsGym-v0"
  
      return gym_problem(
          seed,
          specific_problem=gym_problem_modifier(specific_problem),
          conformant=True,
          big_noise=False,
      )
  
imports: import os
  import typing
  from nevergrad.functions import gym
  from .xpbase import registry
  from .xpbase import create_seed_generator
  from .xpbase import Experiment
  from .optgroups import get_optimizers
label_desc: Use image node_id 16 for calling a global function with example usage: conformant_planning(seed) and returns: gym_problem