import tensorflow as tf


    with tf.variable_scope(scope, reuse=reuse):
        # set up placeholders
        obs_t_input = make_obs_ph("obs_t")
        act_t_ph = tf.placeholder(tf.int32, [None], name="action")
        rew_t_ph = tf.placeholder(tf.float32, [None], name="reward")
        obs_tp1_input = make_obs_ph("obs_tp1")
        done_mask_ph = tf.placeholder(tf.float32, [None], name="done")
        importance_weights_ph = tf.placeholder(tf.float32, [None], name="weight")

        # q network evaluation
        q_t = q_func(obs_t_input.get(), num_actions, scope="q_func", reuse=True)  # reuse parameters from act
        q_func_vars = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope=tf.get_variable_scope().name + "/q_func")

