import tensorflow as tf

        step_model: (DQNPolicy) Policy for evaluation
    """
    n_actions = ac_space.nvec if isinstance(ac_space, MultiDiscrete) else ac_space.n
    with tf.variable_scope("input", reuse=reuse):
        stochastic_ph = tf.placeholder(tf.bool, (), name="stochastic")
        update_eps_ph = tf.placeholder(tf.float32, (), name="update_eps")

    with tf.variable_scope(scope, reuse=reuse):
        if param_noise:
            act_f, obs_phs = build_act_with_param_noise(q_func, ob_space, ac_space, stochastic_ph, update_eps_ph, sess,
