'Get initializer for RNN.'

def get_initializer(self, batch_size, initial_state, initial_actions):

    logits_init = []
    log_probs_init = []
    for (act_dim, act_type) in self.env_spec.act_dims_and_types:
        sampling_dim = self.env_spec.sampling_dim(act_dim, act_type)
        logits_init.append(tf.zeros([batch_size, sampling_dim]))
        log_probs_init.append(tf.zeros([batch_size]))
    entropy_init = [tf.zeros([batch_size]) for _ in self.env_spec.act_dims]
    self_kl_init = [tf.zeros([batch_size]) for _ in self.env_spec.act_dims]
    return (initial_state, tuple(initial_actions), tuple(logits_init), tuple(log_probs_init), tuple(entropy_init), tuple(self_kl_init))
