fix(recipes): low_level_execution needs if_present:subtask guard too

Same bug we fixed for high_level_subtask, just on the other
subtask-supervised sub-recipe. ``low_level_execution`` targets
``${subtask}`` (the current active span) but had no
``if_present`` guard. When ``active_at(t, style=subtask)`` returned
None at a frame (gaps in the annotation, or the very first/last
frames of an episode if the annotator's spans don't fully tile),
the assistant message rendered with empty content. The chat
tokenizer still included it in ``target_message_indices`` → text CE
supervised whatever the chat-template's empty assistant turn
decoded to (usually a single ``\n``). That trains the LM head's
prior at the first generation position toward ``\n``, the same
collapse we observed with the original ``${next_subtask}`` target.

Fix: ``if_present: subtask`` on the assistant target in
``low_level_execution`` for both ``smolvla2_hirobot.yaml`` and
``pi052_hirobot.yaml``.

Side effect: frames without an active subtask span no longer
contribute to the flow loss either (the only ``low_level`` target
is skipped, ``predict_actions = bool(targets_by_stream.get("low_level"))``
becomes False). For a well-annotated dataset where subtask spans
tile the whole episode this is a no-op. For datasets with gaps,
those gap frames lose flow supervision — strictly better than the
degenerate text-CE alternative.

Sub-recipe audit summary (no other changes needed):

  * memory_update                 — all if_present guards present, OK
  * user_interjection_response    — all if_present guards present, OK
  * high_level_subtask            — fixed earlier, OK
  * low_level_execution           — fixed by this commit
  * ask_vqa_top / ask_vqa_wrist   — query+answer both guarded, OK

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

src/lerobot/configs/recipes/pi052_hirobot.yaml

@@ -57,11 +57,15 @@ blend:
       - {role: user, content: "${task}\nPlan: ${plan}\nMemory: ${memory}", stream: high_level}
       - {role: assistant, content: "${subtask}", stream: high_level, target: true, if_present: subtask}
 
+  # Same ``if_present: subtask`` guard as high_level_subtask above —
+  # see smolvla2_hirobot.yaml for the full rationale. Skips the
+  # action-loss supervision on frames without an active subtask span
+  # rather than emitting a degenerate empty target.
   low_level_execution:
     weight: 0.35
     messages:
       - {role: user, content: "${task}\nPlan: ${plan}\nMemory: ${memory}", stream: high_level}
-      - {role: assistant, content: "${subtask}", stream: low_level, target: true}
+      - {role: assistant, content: "${subtask}", stream: low_level, target: true, if_present: subtask}
 
   ask_vqa_top:
     weight: 0.10

src/lerobot/configs/recipes/smolvla2_hirobot.yaml

@@ -69,11 +69,28 @@ blend:
       - {role: user, content: "${task}\nPlan: ${plan}\nMemory: ${memory}", stream: high_level}
       - {role: assistant, content: "${subtask}", stream: high_level, target: true, if_present: subtask}
 
+  # PR3 fix: same ``if_present: subtask`` guard as high_level_subtask
+  # above. Without it, frames where ``active_at(t, style=subtask)``
+  # returns None render the assistant turn with empty content, which
+  # the chat tokenizer still includes in target_message_indices →
+  # text-CE supervises predicting ``\n`` (the chat template's
+  # structural newline) and the LM head collapses to that prior.
+  # The same bug we fixed for high_level_subtask, just on a
+  # different sub-recipe.
+  #
+  # Trade-off of adding the guard: frames without an active subtask
+  # span no longer contribute to the flow loss either (because
+  # ``predict_actions = bool(targets_by_stream.get("low_level"))``
+  # and the only low_level target message is now skipped). For a
+  # well-annotated dataset where subtask spans tile the whole
+  # episode this is a no-op. For datasets with gaps, those gap
+  # frames lose flow supervision — which is strictly better than
+  # the degenerate alternative.
   low_level_execution:
     weight: 0.35
     messages:
       - {role: user, content: "${task}\nPlan: ${plan}\nMemory: ${memory}", stream: high_level}
-      - {role: assistant, content: "${subtask}", stream: low_level, target: true}
+      - {role: assistant, content: "${subtask}", stream: low_level, target: true, if_present: subtask}
 
   # Per-camera VQA sub-recipes (PR 1's view-dependent style routing).
   # Adjust the camera keys (and add more sub-recipes) to match the