fix(evo1): move LIBERO padding into policy processors

tests/envs/test_dispatch.py

@@ -13,7 +13,7 @@ from gymnasium.envs.registration import register, registry as gym_registry
 from lerobot.configs.types import PolicyFeature
 from lerobot.envs.configs import EnvConfig, LiberoEnv
 from lerobot.envs.factory import make_env, make_env_config, make_env_pre_post_processors
-from lerobot.processor import LiberoActionProcessorStep, LiberoProcessorStep
+from lerobot.processor import LiberoProcessorStep
 from lerobot.utils.constants import OBS_PREFIX, OBS_STATE
 
 logger = logging.getLogger(__name__)
@@ -86,38 +86,18 @@ def test_processors_delegation_supports_legacy_override_signature():
     assert isinstance(post, DataProcessorPipeline)
 
 
-def test_libero_evo1_processors_use_padded_state_and_env_action_dim():
-    """EVO1 uses padded LIBERO state features while env actions stay executable."""
-
-    class _Evo1Config:
-        type = "evo1"
-        max_state_dim = 24
-
+def test_libero_processors_are_policy_agnostic():
     cfg = LiberoEnv()
-    pre, post = make_env_pre_post_processors(cfg, policy_cfg=_Evo1Config())
+    pre, post = make_env_pre_post_processors(cfg, policy_cfg=object())
+
     assert isinstance(pre.steps[0], LiberoProcessorStep)
-    assert pre.steps[0].max_state_dim == 24
-    assert isinstance(post.steps[0], LiberoActionProcessorStep)
-    assert post.steps[0].action_dim == cfg.features["action"].shape[0] == 7
-    assert post.steps[0].binarize_gripper is True
-
-    class _OtherConfig:
-        type = "other"
-
-    pre_other, post_other = make_env_pre_post_processors(cfg, policy_cfg=_OtherConfig())
-    assert pre_other.steps[0].max_state_dim is None
-    assert post_other.steps[0].binarize_gripper is False
-
-    cfg.binarize_gripper = False
-    _, post_disabled = make_env_pre_post_processors(cfg, policy_cfg=_Evo1Config())
-    assert post_disabled.steps[0].binarize_gripper is False
+    assert len(post.steps) == 0
 
 
-def test_libero_processor_pads_state_to_max_dim():
-    step = LiberoProcessorStep(max_state_dim=24)
+def test_libero_processor_flattens_state_to_raw_8_dim():
+    step = LiberoProcessorStep()
     observation = {
-        OBS_PREFIX
-        + "robot_state": {
+        OBS_PREFIX + "robot_state": {
             "eef": {
                 "pos": torch.tensor([[1.0, 2.0, 3.0]]),
                 "quat": torch.tensor([[0.0, 0.0, 0.0, 1.0]]),
@@ -127,39 +107,8 @@ def test_libero_processor_pads_state_to_max_dim():
     }
 
     state = step.observation(observation)[OBS_STATE]
-    assert state.shape == (1, 24)
-    assert torch.allclose(state[:, :8], torch.tensor([[1.0, 2.0, 3.0, 0.0, 0.0, 0.0, 4.0, 5.0]]))
-    assert torch.count_nonzero(state[:, 8:]).item() == 0
-
-
-def test_libero_action_processor_slices_padded_action():
-    step = LiberoActionProcessorStep(action_dim=7)
-    action = torch.arange(2 * 3 * 24, dtype=torch.float32).reshape(2, 3, 24)
-
-    sliced = step.action(action)
-    assert sliced.shape == (2, 3, 7)
-    assert torch.equal(sliced, action[..., :7])
-
-    with pytest.raises(ValueError, match="smaller than action_dim=7"):
-        step.action(torch.zeros(2, 6))
-
-
-def test_libero_action_processor_can_binarize_gripper():
-    step = LiberoActionProcessorStep(action_dim=7, binarize_gripper=True)
-    action = torch.tensor(
-        [
-            [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 0.5, 7.0],
-            [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 0.6, 7.0],
-        ],
-        dtype=torch.float32,
-    )
-
-    processed = step.action(action)
-
-    assert processed.shape == (2, 7)
-    assert torch.equal(processed[:, :6], action[:, :6])
-    assert torch.equal(processed[:, 6], torch.tensor([1.0, -1.0]))
-    assert torch.equal(action[:, 6], torch.tensor([0.5, 0.6]))
+    assert state.shape == (1, 8)
+    assert torch.allclose(state, torch.tensor([[1.0, 2.0, 3.0, 0.0, 0.0, 0.0, 4.0, 5.0]]))
 
 
 def test_base_create_envs():