Can't restore trained model when training a new one

Hi all,

I successfully trained a PPO agent (let’s call the agent Jerry) for part of my task and the other was handled by computation heavy simulator (Scenario 1).
Now I want to use Jerry (weights frozen) for the first part of the task and train a PPO agent for the second half of the task (Scenario 2). Note that both parts happen at single time-step.

The problem is that when I run for Scenario 2, in the init of the custom model I try to restore Jerry. When the line agent = ppo.PPOTrainer(env=Grid_Gym, config = config_params) is encountered everything freezes.

My hypothesis is that the number of workers are at the heart of the issue. For Scenario 2 I supply a certainnum_workers but then there are no available workers to restore Jerry.

Help would be greatly appreciated as it blocks me from using Ray to solve the task and I cannot find a way around it cc. @sven1977.