• I have marked all applicable categories:
  • exception-raising bug
  • RL algorithm bug
  • documentation request (i.e. "X is missing from the documentation.")
  • new feature request
  • design request (i.e. "X should be changed to Y.")
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• I have searched through the issue tracker for duplicates
• I have mentioned version numbers, operating system and environment, where applicable:

I have noticed that in the implementation of the PPOPolicy, the computation of the old log probabilities logp_old is performed without using minibatch:

with torch.no_grad():
   batch.logp_old = self(batch).dist.log_prob(batch.act)

This makes this algorithm unusable in situations where the batch is too large, with no possibility of controlling it via batch_size.
I simply suggest to add support for minibatch:

logp_old = []
with torch.no_grad():
    for minibatch in batch.split(self._batch, shuffle=False, merge_last=True):
        logp_old.append(self(minibatch).dist.log_prob(minibatch.act))
    batch.logp_old = torch.cat(logp_old, dim=0).flatten()

The version of Tianshou that I'm using is 1.0.0.