def tf_observe_timestep(self, states, internals, actions, terminal, reward):
raise NotImplementedError<EOL>
Creates the TensorFlow operations for processing a batch of observations coming in from our buffer (state,
action, internals) as well as from the agent's python-batch (terminal-signals and rewards from the env).

Args:
    states (dict): Dict of state tensors (each key represents one state space component).
    internals (dict): Dict of prior internal state tensors (each key represents one internal state component).
    actions (dict): Dict of action tensors (each key represents one action space component).
    terminal: 1D (bool) tensor of terminal signals.
    reward: 1D (float) tensor of rewards.

Returns:
    The observation operation depending on the model type.