Error when running the Single Item Recommender System Notebook

[Daniel Ávila Vera]

Hi, I'm trying to run the notebook on how to use Pearl for recommender systems, but when I run the online_learning() function I keep getting the same error, which I copy below:

    [161](Pearl/pearl/pearl_agent.py:161) if isinstance(safe_action_space, DiscreteActionSpace):
--> [162](Pearl/pearl/pearl_agent.py:162)     self._latest_action = safe_action_space.actions_batch[int(action.item())]
    [163](Pearl/pearl/pearl_agent.py:163) else:
    [164](Pearl/pearl/pearl_agent.py:164)     self._latest_action = action

RuntimeError: a Tensor with 100 elements cannot be converted to Scalar

On the other hand, I'm having a hard time understanding how the environment is being built. Could someone please explain further how they are creating the RecEnv object?

[rodrigodesalvobraz]

I am debugging this and will let you know as soon as possible.

[rodrigodesalvobraz]

Update: we've identified the bug and are currently working on a solution. Should be out today or tomorrow.

[rodrigodesalvobraz]

Update: started the fix but it had a wider range than initially expected. It might take a few days to get everything set correctly.

[rodrigodesalvobraz]

Update: we've fixed the bug but we don't see the same learning behavior as previously observed, so now we are working on identifying the cause of that.

[rodrigodesalvobraz]

Glad to let you know this has been finally fixed! It took a few iterations and the removal of a couple of issues.