def reset(self):
    """Reset the environment.

    Returns:
      Tensor of the current observation.
    """
    observ_dtype = self._parse_dtype(self._env.observation_space)
    observ = tf.py_func(self._env.reset, [], observ_dtype, name='reset')
    observ = tf.check_numerics(observ, 'observ')
    with tf.control_dependencies([
        self._observ.assign(observ),
        self._reward.assign(0),
        self._done.assign(False)]):
      return tf.identity(observ)
def reset ( self ) : observ_dtype = self . _parse_dtype ( self . _env . observation_space ) observ = tf . py_func ( self . _env . reset , [ ] , observ_dtype , name = 'reset' ) observ = tf . check_numerics ( observ , 'observ' ) with tf . control_dependencies ( [ self . _observ . assign ( observ ) , self . _reward . assign ( 0 ) , self . _done . assign ( False ) ] ) : return tf . identity ( observ )
Reset the environment.

    Returns:
      Tensor of the current observation.