refactor: implement NotImplementedError for abstract methods in RLAlgorithm and DataMixer

src/lerobot/rl/algorithms/base.py

@@ -44,7 +44,7 @@ class RLAlgorithm(abc.ABC):
         The iterator is owned by the trainer; the algorithm just consumes
         from it.
         """
-        ...
+        raise NotImplementedError
 
     def configure_data_iterator(
         self,
@@ -65,13 +65,13 @@ class RLAlgorithm(abc.ABC):
             queue_size=queue_size,
         )
 
+    @abc.abstractmethod
     def make_optimizers_and_scheduler(self) -> dict[str, Optimizer]:
-        """Create, store, and return the optimizers needed for training.
+        """Build and return the optimizers used during training.
 
-        Called on the **learner** side after construction.  Subclasses must
+        Called once on the learner side after construction.
-        override this with algorithm-specific optimizer setup.
         """
-        return {}
+        raise NotImplementedError
 
     def get_optimizers(self) -> dict[str, Optimizer]:
         """Return optimizers for checkpointing / external scheduling."""
@@ -97,3 +97,4 @@ class RLAlgorithm(abc.ABC):
     @abc.abstractmethod
     def load_weights(self, weights: dict[str, Any], device: str | torch.device = "cpu") -> None:
         """Load policy state-dict received from the learner."""
+        raise NotImplementedError

src/lerobot/rl/data_sources/data_mixer.py

@@ -27,7 +27,7 @@ class DataMixer(abc.ABC):
     @abc.abstractmethod
     def sample(self, batch_size: int) -> BatchType:
         """Draw one batch of ``batch_size`` transitions."""
-        ...
+        raise NotImplementedError
 
     def get_iterator(
         self,