abstractions before doing thatthoughyou'll need to first create placeholders for your data in your main functiondirectly beneath rewards=[]insert the following highlighted content hereyou define placeholders for your observation at time (as obs_t_phand time + (as obs_tp _ph)as well as placeholders for your actionrewardand target/ataribot/bot_ _q_network py def main()env gym make('frozenlake- 'create the game env seed( make results reproducible rewards [ setup placeholders n_obsn_actions env observation_space nenv action_space obs_t_ph tf placeholder(shape=[ n_obs]dtype=tf float obs_tp _ph tf placeholder(shape=[ n_obs]dtype=tf float act_ph tf placeholder(tf int shape=()rew_ph tf placeholder(shape=()dtype=tf float q_target_ph tf placeholder(shape=[ n_actions]dtype=tf float np zeros((env observation_space nenv action_space )for episode in range( num_episodes )