Removes hardcoded policy obs group for symmetry (#111)

Author: ClemensSchwarke

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "rsl-rl-lib"
-version = "3.0.0"
+version = "3.0.1"
 keywords = ["reinforcement-learning", "isaac", "leggedrobotics", "rl-pytorch"]
 maintainers = [
   { name="Clemens Schwarke", email="cschwarke@ethz.ch" },

rsl_rl/algorithms/ppo.py

@@ -215,7 +215,7 @@ def update(self):  # noqa: C901
             num_aug = 1
             # original batch size
             # we assume policy group is always there and needs augmentation
-            original_batch_size = obs_batch["policy"].shape[0]
+            original_batch_size = obs_batch.batch_size[0]
 
             # check if we should normalize advantages per mini batch
             if self.normalize_advantage_per_mini_batch:
@@ -227,14 +227,14 @@ def update(self):  # noqa: C901
                 # augmentation using symmetry
                 data_augmentation_func = self.symmetry["data_augmentation_func"]
                 # returned shape: [batch_size * num_aug, ...]
-                obs_batch, actions_batch = data_augmentation_func(  # TODO: needs changes on the isaac lab side
+                obs_batch, actions_batch = data_augmentation_func(
                     obs=obs_batch,
                     actions=actions_batch,
                     env=self.symmetry["_env"],
                 )
                 # compute number of augmentations per sample
                 # we assume policy group is always there and needs augmentation
-                num_aug = int(obs_batch["policy"].shape[0] / original_batch_size)
+                num_aug = int(obs_batch.batch_size[0] / original_batch_size)
                 # repeat the rest of the batch
                 # -- actor
                 old_actions_log_prob_batch = old_actions_log_prob_batch.repeat(num_aug, 1)