code: def reset(self, *, seed=None, options=None):
      self.state = self.observation_space.sample()
      self.steps = 0
      return self.state, {}
  
imports: import gymnasium
  from gymnasium.spaces import Box, Dict, Discrete, Tuple
  import numpy
  import re
  import unittest
  import ray
  from ray.rllib.algorithms import sac
  from ray.rllib.algorithms.sac.sac_tf_policy import sac_actor_critic_loss
  from ray.rllib.algorithms.sac.sac_torch_policy import actor_critic_loss
  from ray.rllib.examples.env.random_env import RandomEnv
  from ray.rllib.examples.models.batch_norm_model import KerasBatchNormModel, TorchBatchNormModel
  from ray.rllib.models.catalog import ModelCatalog
  from ray.rllib.models.tf.tf_action_dist import Dirichlet
  from ray.rllib.models.torch.torch_action_dist import TorchDirichlet
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.framework import try_import_tf, try_import_torch
  from ray.rllib.utils.numpy import fc, huber_loss, relu
  from ray.rllib.utils.spaces.simplex import Simplex
  from ray.rllib.utils.test_utils import check, check_compute_single_action, check_train_results, framework_iterator
  from ray.rllib.utils.torch_utils import convert_to_torch_tensor
  from ray import tune
  from ray.rllib.utils.replay_buffers.utils import patch_buffer_with_fake_sampling_method
label_desc: Use image node_id 2 for calling the SimpleEnv obj's underlying member method code with example usage: obj.reset() and returns: self,  dict