class_docstr: A fake environment with a given spec.
class_docstr_tok: ["A","fake","environment","with","a","given","spec","."]
code: def step(self, action) -> dm_env.TimeStep:
      # Return a reset timestep if we haven't touched the environment yet.
      if not self._step:
          return self.reset()
  
      _validate_spec(self._spec.actions, action)
  
      observation = self._generate_fake_observation()
      reward = self._generate_fake_reward()
      discount = self._generate_fake_discount()
  
      if self._episode_length and (self._step == self._episode_length):
          self._step = 0
          # We can't use dm_env.termination directly because then the discount
          # wouldn't necessarily conform to the spec (if eg. we want float32).
          return dm_env.TimeStep(
              dm_env.StepType.LAST, reward, discount, observation
          )
      else:
          self._step += 1
          return dm_env.transition(
              reward=reward, observation=observation, discount=discount
          )
  
imports: import threading
  from typing import List, Mapping, Optional, Sequence, Callable, Iterator
  from acme import core
  from acme import specs
  from acme import types
  from acme import wrappers
  import dm_env
  import numpy
  import reverb
  from rlds import rlds_types
  import tensorflow
  import tree
label_desc: Use image node_id 6 for calling the Environment obj's underlying member method code with example usage: obj.step(action) and returns: self, dm_env, dm_env