Files
lerobot/examples/annotations/run_hf_job.py
T
Pepijn 7454b4c993 annotate: remove action-record subtask-text replacement entirely
Drops the replace_subtask_text option and the
_render_action_record_to_subtask_text renderer. Action records are now
strictly additive: when action_records.enabled=True the module emits
style='action_record' rows (the typed {verb,object,arm,grasp,dest,
mistake} schema) and NEVER rewrites the subtask text the policy
conditions on.

The render-back-to-text path was the source of corrupted subtasks
(navigation tasks produced 'move stove to stove', manipulation tasks
got spurious 'with left arm using pinch grip' suffixes). Reconstructing
natural-language subtasks from hallucinated structured fields is
inherently fragile, so the capability is removed rather than guarded.

Removed:
  * ActionRecordsConfig.replace_subtask_text field
  * PlanSubtasksMemoryModule._render_action_record_to_subtask_text
  * the span['text'] = canonical_text overwrite in run_episode

Updated docstrings + run_hf_job.py comment accordingly. emit_record_row
(default True) is now the feature's only output.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-02 14:42:36 +02:00

96 lines
3.9 KiB
Python

#!/usr/bin/env python
"""Launch ``lerobot-annotate`` on a Hugging Face job (vllm + Qwen3.6 MoE).
Spawns one ``h200x2`` job that:
1. installs this branch of ``lerobot`` plus the annotation extras,
2. boots two vllm servers (one per GPU) with Qwen3.6-35B-A3B-FP8,
3. runs the plan / interjections / vqa modules across the dataset
in free-form mode (each episode generates its own subtasks +
memory),
4. uploads the annotated dataset to ``--dest_repo_id`` (when set)
or back to ``--repo_id``.
Usage:
HF_TOKEN=hf_... uv run python examples/annotations/run_hf_job.py
Adjust ``CMD`` below to point at your own dataset / target hub repo.
"""
import os
from huggingface_hub import get_token, run_job
token = os.environ.get("HF_TOKEN") or get_token()
if not token:
raise RuntimeError("No HF token. Run `huggingface-cli login` or `export HF_TOKEN=hf_...`")
CMD = (
"apt-get update -qq && apt-get install -y -qq git ffmpeg && "
"pip install --no-deps "
"'lerobot @ git+https://github.com/huggingface/lerobot.git@feat/language-annotation-pipeline' && "
"pip install --upgrade-strategy only-if-needed "
"datasets pyarrow av jsonlines draccus gymnasium torchcodec mergedeep pyyaml-include toml typing-inspect "
"openai && "
"export VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS=0 && "
"export VLLM_VIDEO_BACKEND=pyav && "
"lerobot-annotate "
"--repo_id=pepijn223/robocasa_smoke_2atomic_v3 "
"--dest_repo_id=pepijn223/robocasa_smoke_2atomic_v3_ann "
"--push_to_hub=true "
"--vlm.backend=openai "
"--vlm.model_id=Qwen/Qwen3.6-35B-A3B-FP8 "
"--vlm.parallel_servers=2 "
"--vlm.num_gpus=2 "
'--vlm.serve_command="vllm serve Qwen/Qwen3.6-35B-A3B-FP8 '
"--tensor-parallel-size 1 --max-model-len 32768 "
'--gpu-memory-utilization 0.8 --uvicorn-log-level warning --port {port}" '
"--vlm.serve_ready_timeout_s=1800 "
"--vlm.client_concurrency=128 "
"--vlm.max_new_tokens=512 "
"--vlm.temperature=0.7 "
"--executor.episode_parallelism=16 "
"--vlm.chat_template_kwargs='{\"enable_thinking\": false}' "
"--vlm.camera_key=observation.images.robot0_agentview_right "
# Phase 1 — plan module (subtasks + plan + memory).
"--plan.frames_per_second=1.0 "
"--plan.use_video_url=true "
"--plan.use_video_url_fps=1.0 "
# IMPORTANT for RoboCasa: the dataset's task string ("Navigate to the
# stove", "Pick the mug...") is authoritative and is what eval uses.
# ``derive_task_from_video=off`` keeps that canonical task driving
# subtask generation. Do NOT use ``always`` here — it throws the real
# task away, asks the VLM "what is this video about?" with no hint,
# and the hallucinated task then poisons every subtask + plan row.
"--plan.derive_task_from_video=off "
# NO task augmentation for RoboCasa: eval conditions on the exact task
# strings, so synthetic rephrasings are unused at best and (when they
# drift, e.g. "wander around the kitchen") harmful. 0 rephrasings +
# axes disabled = the policy only ever sees the canonical task.
"--plan.n_task_rephrasings=0 "
# action_records OFF: the structured {verb,object,arm,grasp,dest}
# schema is a manipulation schema; RoboCasa navigation / atomic tasks
# don't fit it and the VLM hallucinates. When on, records are purely
# additive (emitted as style="action_record" rows) and never touch
# the subtask text — useful only for long composite manipulation
# tasks. Leave off for RoboCasa atomic / navigation.
# Keep subtask decomposition tight for atomic tasks:
"--plan.plan_max_steps=6 "
# Phase 2 — interjections + speech.
"--interjections.max_interjections_per_episode=6 "
# Phase 4 — general VQA.
"--vqa.K=1 "
"--vqa.vqa_emission_hz=1.0"
)
job = run_job(
image="vllm/vllm-openai:latest",
command=["bash", "-c", CMD],
flavor="h200x2",
secrets={"HF_TOKEN": token},
timeout="2h",
)
print(f"Job URL: {job.url}")
print(f"Job ID: {job.id}")