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refactor(pi052): trim PR — remove say tool, debug gates, dead code; move runtime
Cleanup pass over the language-support PR to cut LOC and scope creep. Removals: - SayTool + tools/ package (registry, Tool protocol, [tools] extra) and the runtime's tool-dispatch path. Kept <say> training supervision and inference stripping so speech-annotated datasets still train. - WeightedEpisodeAwareSampler + VQA oversampling wiring (_build_vqa_oversample_weights, vqa_target_fraction) — training uses plain EpisodeAwareSampler again. - Debug env-gates PI052_DEBUG_TENSORS, PI052_SUBTASK_USE_TASK, EVAL_TASK_OVERRIDE. - Dead code: broken _tp._DUMP_BUDGET block, unused imports (copy/Tensor, RevisionNotFoundError, LeRobotDataset, os), messages_for_vqa, steps.py shim (modeling imports pi052_adapter directly), duplicated _emit, builtins.type[T]. Moves: - Policy-agnostic runtime -> src/lerobot/runtime/ (LanguageConditionedRuntime + adapter Protocol + state); pi052 keeps only its adapter + CLI. Tests -> tests/runtime/. Other: - Compacted verbose AI-authored comments/docstrings across pi052 (kept the hard-won DDP / barrier-timeout / reduce-max / VQA-routing notes). - Relocated LM-head prediction debug helper to pi052/debug_utils.py. - Fixed test_render_messages: assert task-fallback render (current behavior) instead of the stale no-op expectation. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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@@ -12,7 +12,9 @@ from lerobot.processor.render_messages_processor import RenderMessagesStep # no
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from lerobot.types import TransitionKey # noqa: E402
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def test_render_messages_step_noops_without_language_columns():
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def test_render_messages_step_renders_task_fallback_without_language_columns():
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"""No language columns + a task string → low-level task fallback render,
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matching what the policy sees at eval time on unannotated observations."""
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recipe = TrainingRecipe(
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messages=[
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MessageTurn(role="user", content="${task}", stream="high_level"),
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@@ -21,6 +23,24 @@ def test_render_messages_step_noops_without_language_columns():
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)
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transition = create_transition(complementary_data={"task": "do it"})
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out = RenderMessagesStep(recipe)(transition)
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data = out[TransitionKey.COMPLEMENTARY_DATA]
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assert data["messages"] == [{"role": "user", "content": "do it"}]
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assert data["message_streams"] == ["low_level"]
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assert data["target_message_indices"] == []
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assert data["task"] == "do it"
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def test_render_messages_step_noops_without_language_columns_or_task():
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recipe = TrainingRecipe(
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messages=[
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MessageTurn(role="user", content="${task}", stream="high_level"),
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MessageTurn(role="assistant", content="${subtask}", stream="low_level", target=True),
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]
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)
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transition = create_transition(complementary_data={})
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assert RenderMessagesStep(recipe)(transition) == transition
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