following highlighted lines this code starts your computation by computing (safor all to make q_current and ( ' 'for all ato make q_target/ataribot/bot_ _q_network py rew_ph tf placeholder(shape=()dtype=tf float q_target_ph tf placeholder(shape=[ n_actions]dtype=tf float setup computation graph tf variable(tf random_uniform([n_obsn_actions] )q_current tf matmul(obs_t_phwq_target tf matmul(obs_tp _phwq np zeros((env observation_space nenv action_space )for episode in range( num_episodes )again directly beneath the last line you addedinsert the following higlighted code the first two lines are equivalent to the line added in step that computes qtargetwhere qtarget reward discount_factor np max( [state :]the next two lines set up your losswhile the last line computes the action that maximizes your -value/ataribot/bot_ _q_network py