Handle option masking correctly when computing TD targets.

[Ueva]

BaRL-SimpleOptions/simpleoptions/function_approximation/agents/macro_dqn_options_agent.py

Lines 121 to 125 in f82e945

	# Compute TD targets.
	next_state_values = torch.zeros(self.batch_size, dtype=torch.float32)
	with torch.no_grad():
	next_state_values[non_terminal_mask] = self.target(non_terminal_next_states).max(1).values
	targets = reward_batch + self.gamma * next_state_values

Currently, the value of masked options is not ignored when computing TD targets for Macro-DQN updates.

We need a function that produces an option mask for given states, which can be used here and elsewhere where option masking is needed. Ideally, this should be able to take batches of states and produce batches of option masks. This function will be called potentially many times per time step, so it should be performant.