class_docstr: Unit-test mock environment.
  
  Args:
      states: States specification.
      actions: Actions specification.
      min_timesteps: Minimum number of timesteps.
code: def execute(self, actions):
      if not self.is_valid_actions(actions, self._states):
          print(actions, self._states, self.actions_spec)
          raise TensorforceError.value(
              name="execute", argument="actions", value=actions
          )
  
      self.timestep += 1
      self._states = self.random_states()
      terminal = self.timestep >= self.min_timesteps and random() < 0.25
      reward = -1.0 + 2.0 * random()
  
      return self._states, terminal, reward
  
file_path: tensorforce/test/unittest_environment.py
imports: from collections import OrderedDict
  from random import random
  import numpy
  from tensorforce import Environment, TensorforceError, util
label_desc: Use image node_id 10 for calling the UnittestEnvironment obj's underlying member method code with example usage: obj.execute(actions) and returns: self,  terminal,  reward