cleaning up to keep changes minimal

tests/test_rollout.py

@@ -252,93 +252,10 @@ def test_create_inference_engine_sync():
 
 
 # ---------------------------------------------------------------------------
-# Observation feature-spec consistency (sync vs RTC)
-#
-# ``build_dataset_frame`` orders the ``observation.state`` vector by the ``names``
-# list of the feature spec it is handed. Sync uses ``dataset_features`` (joint
-# layout AFTER ``robot_observation_processor``); RTC must use the SAME spec, not the
-# raw-hardware layout, or its state vector desyncs from sync — corrupting both the
-# normalizer's per-joint stats and the relative-action anchor, which sends the arm
-# to systematically wrong absolute targets.
+# RTC action-key ordering and prefix padding
 # ---------------------------------------------------------------------------
 
 
-def test_build_dataset_frame_state_layout_depends_on_feature_spec():
-    """A reordered feature spec yields a reordered ``observation.state`` vector."""
-    import numpy as np
-
-    from lerobot.utils.feature_utils import build_dataset_frame, hw_to_dataset_features
-
-    # Raw hardware joint order.
-    obs_hw = {"shoulder.pos": float, "elbow.pos": float, "wrist.pos": float, "gripper.pos": float}
-    hw_features = hw_to_dataset_features(obs_hw, "observation")
-
-    # What a ``robot_observation_processor`` that reorders state keys would produce
-    # (e.g. gripper moved to the front). Same keys, different order.
-    dataset_features = {
-        "observation.state": {
-            "dtype": "float32",
-            "shape": (4,),
-            "names": ["gripper.pos", "shoulder.pos", "elbow.pos", "wrist.pos"],
-        }
-    }
-
-    values = {"shoulder.pos": 10.0, "elbow.pos": 20.0, "wrist.pos": 30.0, "gripper.pos": 40.0}
-
-    hw_state = build_dataset_frame(hw_features, values, prefix="observation")["observation.state"]
-    ds_state = build_dataset_frame(dataset_features, values, prefix="observation")["observation.state"]
-
-    np.testing.assert_array_equal(hw_state, [10.0, 20.0, 30.0, 40.0])
-    np.testing.assert_array_equal(ds_state, [40.0, 10.0, 20.0, 30.0])
-    # The two layouts genuinely differ: this is the sync/RTC divergence the fix removes.
-    assert not np.array_equal(hw_state, ds_state)
-
-
-def test_create_inference_engine_rtc_uses_dataset_features():
-    """The RTC engine must build observations from ``dataset_features`` (sync's spec),
-    not the raw-hardware ``hw_features`` — so its ``observation.state`` matches sync."""
-    from lerobot.rollout import RTCInferenceConfig, RTCInferenceEngine, create_inference_engine
-
-    dataset_features = {
-        "observation.state": {
-            "dtype": "float32",
-            "shape": (4,),
-            "names": ["gripper.pos", "shoulder.pos", "elbow.pos", "wrist.pos"],
-        }
-    }
-    # Deliberately different order to prove the engine ignores it.
-    hw_features = {
-        "observation.state": {
-            "dtype": "float32",
-            "shape": (4,),
-            "names": ["shoulder.pos", "elbow.pos", "wrist.pos", "gripper.pos"],
-        }
-    }
-
-    engine = create_inference_engine(
-        RTCInferenceConfig(),
-        policy=MagicMock(),
-        # No relative/normalizer steps => __init__ introspection stays trivial.
-        preprocessor=MagicMock(steps=[]),
-        postprocessor=MagicMock(steps=[]),
-        robot_wrapper=MagicMock(robot_type="mock"),
-        hw_features=hw_features,
-        dataset_features=dataset_features,
-        ordered_action_keys=["k"],
-        task="test",
-        fps=30.0,
-        device="cpu",
-    )
-    assert isinstance(engine, RTCInferenceEngine)
-    assert engine._obs_features is dataset_features
-    assert engine._obs_features["observation.state"]["names"] == [
-        "gripper.pos",
-        "shoulder.pos",
-        "elbow.pos",
-        "wrist.pos",
-    ]
-
-
 def test_rtc_get_action_remaps_model_order_to_ordered_action_keys():
     """RTC must remap the model-order action vector to ``ordered_action_keys`` by NAME
     before returning — matching sync. Otherwise the strategy maps model outputs onto the