feat(batch_processor): Add task field processing to ToBatchProcessor

- Enhanced ToBatchProcessor to wrap string tasks in a list, adding batch dimensions for compatibility with model inference.
- Implemented a new method for processing complementary data, ensuring that task values are correctly handled as either strings or lists of strings.
- Added comprehensive unit tests to validate task processing, including edge cases and in-place mutation of complementary data.

src/lerobot/processor/batch_processor.py

@@ -37,6 +37,10 @@ class ToBatchProcessor:
     - For actions:
       Adds batch dimension (unsqueeze at dim=0) if tensor is 1-dimensional
 
+    - For task field in complementary data:
+      Wraps string task in a list to add batch dimension
+      (task must be a string or list of strings)
+
     This is useful when processing single transitions that need to be batched for
     model inference or when converting from unbatched environment outputs to
     batched model inputs.
@@ -49,6 +53,7 @@ class ToBatchProcessor:
         # State: (7,) -> (1, 7)
         # Image: (224, 224, 3) -> (1, 224, 224, 3)
         # Action: (4,) -> (1, 4)
+        # Task: "pick_cube" -> ["pick_cube"]
         # Already batched: (1, 7) -> (1, 7) [unchanged]
         ```
     """
@@ -56,6 +61,7 @@ class ToBatchProcessor:
     def __call__(self, transition: EnvTransition) -> EnvTransition:
         self._process_observation(transition)
         self._process_action(transition)
+        self._process_complementary_data(transition)
         return transition
 
     def _process_observation(self, transition: EnvTransition) -> None:
@@ -88,6 +94,18 @@ class ToBatchProcessor:
         if action is not None and isinstance(action, Tensor) and action.dim() == 1:
             transition[TransitionKey.ACTION] = action.unsqueeze(0)
 
+    def _process_complementary_data(self, transition: EnvTransition) -> None:
+        """Process complementary data in-place, handling task field batching."""
+        complementary_data = transition.get(TransitionKey.COMPLEMENTARY_DATA)
+        if complementary_data is None:
+            return
+
+        # Process task field - wrap string in list to add batch dimension
+        if "task" in complementary_data:
+            task_value = complementary_data["task"]
+            if isinstance(task_value, str):
+                complementary_data["task"] = [task_value]
+
     def get_config(self) -> dict[str, Any]:
         """Return configuration for serialization."""
         return {}