code: def __init__(
      self,
      *,
      buffer_observe=False,
      create_debug_assertions=False,
      create_tf_assertions=True,
      device="CPU",
      eager_mode=False,
      enable_int_action_masking=True,
      name="agent",
      seed=None,
      tf_log_level=40,
  ):
      assert (
          buffer_observe is False
          or buffer_observe == "episode"
          or isinstance(buffer_observe, int)
          and buffer_observe >= 1
      )
      if buffer_observe is False:
          buffer_observe = 1
      super().__setattr__("buffer_observe", buffer_observe)
  
      assert isinstance(create_debug_assertions, bool)
      super().__setattr__(
          "create_debug_assertions", create_debug_assertions
      )
  
      assert isinstance(create_tf_assertions, bool)
      super().__setattr__("create_tf_assertions", create_tf_assertions)
  
      assert isinstance(eager_mode, bool)
      super().__setattr__("eager_mode", eager_mode)
  
      assert isinstance(enable_int_action_masking, bool)
      super().__setattr__(
          "enable_int_action_masking", enable_int_action_masking
      )
  
      assert device is None or isinstance(device, str)  # more specific?
      super().__setattr__("device", device)
  
      assert isinstance(name, str)
      super().__setattr__("name", name)
  
      assert seed is None or isinstance(seed, int)
      super().__setattr__("seed", seed)
  
      assert isinstance(tf_log_level, int) and tf_log_level >= 0
      super().__setattr__("tf_log_level", tf_log_level)
  
label_desc: Use image node_id 1 to create a new TensorforceConfig object from inherited base classes: object with example: obj = TensorforceConfig()