Distribution wrapper with dict space

My environment have a spaces.Dict for the action spaces.

I wrote a custom DistributionWrapper, returning a dict, and it looks all fine :

class CustomDistribution(TorchDistributionWrapper):
   def sample(self):
        idx_dist = self._idx_distribution()
        idx = idx_dist.sample()

        type_dists = self._type_distribution(idx)
        actions = [d.sample() for d in type_dists]
        self._action_logp = idx_dist.logp(idx) + sum(d.logp(a) for d, a in zip(type_dists, actions))

        return {
            "idx": idx,
            "p1": actions[0],
            "p2": actions[1],
            "p3": actions[2],

But I’m having a problem for the implementation of logp() method… This method takes actions as input, and it’s a Tensor format, not a dictionary. The tensor has shape [batch, 4] (which is normal, I have 4 actions).

Does someone know where I can find the code dicttensor ?

Because I’m having the following error :

ValueError: The value argument must be within the support

Which means the order of my action is messed up !

I think gym sorts Dict actions alphabetically by key (OrderedDict). Could that be the reason?

Thank you for the answer !
I checked and indeed the keys seems to be reordered alphabetically.

Is there any way to get a dict of Tensor instead of just a tensor ?