unable to test the learnt model because customed_goal_sampler is not loaded

Hi, when I was running run_goal_conditioned_policy.py, an error occurred saying custom_goal_sampler is None. And I checked that VAEWrappedEnv.__getstate__ ignored its _custom_goal_sampler. Then there is no data load while the object is loaded from .pkl file.

Is there any method to make the goal sampling work while testing the trained model?

[vitchyr]

Good question! Yeah, this part of the code is a bit “untyped”/undocumented. Based on VAEWrappedEnv.samples_goals, the signature should be

def goal_sampler_function(batch_size):
  return dict_of_goals

where dict_of_goals is something like:

{
  'desired_goals': NUMPY_ARRAY # shape (batch_size x latent_dim),
  'other_desired_goal: NUMPY_ARRAY # shape (batch_size x feature_dim),
}

[vitchyr]

Yes, so in that experiment, during autonomous exploration, we sample goals from the replay buffer since the policy doesn’t have access to any oracle sampler. However, for testing you might want to have some “oracle goal sampler” and you can implement that using the custom goal sampler.