Genearative Adversarial Imitation Learning Project

I have some code that attempts to imitate the optimal policy for an agent using GAIL (Generative Adversarial Imitation Learning) . The observations are a 1-D floating-point number and the action space is a 0,1 variable. My current code is not generating the correct policy. I need you to either rework my code or write your own new code so that the imitation policy correctly imitates my expert policy. It should take 20-30 minutes for someone that knows what they are doing in stable baselines and GAIL in general as the code is already written, I just can't figure out why the training is not converging to the correct policy. I'm happy to pay 100 to 200 dollars if you can figure it out. The uploaded file is a numpy save file detailing the expert policy (observations are first then actions I believe).