| |
| |
| |
| |
| @@ -4,24 +4,26 @@ from .base_config import ObservationConfig, StateActionConfig, RobotConfig, regi |
| # R1Pro Robot Configuration |
| # Dual-arm mobile manipulator with base, torso, and multiple camera views |
| R1Pro = RobotConfig( |
| - name="robot", |
| + # BEHAVIOR-1K v3.9.2 eval names the robot "robot_r1" (see OmniGibson/omnigibson/eval/r1pro.yaml), |
| + # so the flattened observation keys the eval client streams are prefixed "robot_r1::". |
| + name="robot_r1", |
| robot_type="R1Pro", |
| observations={ |
| "image_0": ObservationConfig( |
| name="head", |
| - obs_key="robot::robot:zed_link:Camera:0::rgb", |
| + obs_key="robot_r1::robot_r1:zed_link:Camera:0::rgb", |
| dataset_key="observation.rgb.zed_link_camera_0", |
| resolution=[240, 240] |
| ), |
| "image_1": ObservationConfig( |
| name="left_wrist", |
| - obs_key="robot::robot:left_realsense_link:Camera:0::rgb", |
| + obs_key="robot_r1::robot_r1:left_realsense_link:Camera:0::rgb", |
| dataset_key="observation.rgb.left_realsense_link_camera_0", |
| resolution=[240, 240] |
| ), |
| "image_2": ObservationConfig( |
| name="right_wrist", |
| - obs_key="robot::robot:right_realsense_link:Camera:0::rgb", |
| + obs_key="robot_r1::robot_r1:right_realsense_link:Camera:0::rgb", |
| dataset_key="observation.rgb.right_realsense_link_camera_0", |
| resolution=[240, 240] |
| ), |
| |
| |
| |
| |
| @@ -3,6 +3,13 @@ from . import TASK_REGISTRY |
| # i3l task prompts |
| TASKS = { |
| "turning_on_radio": "Turn on the radio receiver that's on the table in the living room.", |
| + # Task 22 in the 2026 BEHAVIOR Challenge task list. The policy was fine-tuned with |
| + # prompt_from_task=True, so the training prompt was the raw LeRobot task string |
| + # "putting_shoes_on_rack" (the PaliGemma tokenizer lowercases it and turns "_" into " "). |
| + "putting_shoes_on_rack": "putting shoes on rack", |
| + # Task 38 in the 2026 BEHAVIOR Challenge. Same convention: prompt_from_task=True during |
| + # fine-tuning, so the training prompt is the raw LeRobot task string. |
| + "spraying_for_bugs": "spraying for bugs", |
| } |
| |
| # Register in global registry |
| |
| |
| |
| |
| @@ -772,6 +772,61 @@ _CONFIGS = [ |
| assets_base_dir="./outputs/assets", |
| checkpoint_base_dir="./outputs/checkpoints", |
| ), |
| + # Task 38 (spraying_for_bugs) -- full fine-tune, mirror of pi05_b1k. Needs multi-GPU (FSDP) |
| + # or a large single GPU; use the _lora variant below to fit on one ~46 GB card. |
| + TrainConfig( |
| + name="pi05_b1k_spraying_for_bugs", |
| + model=pi0_config.Pi0Config(action_horizon=32, pi05=True), |
| + data=LeRobotB1KDataConfig( |
| + repo_id="spraying_for_bugs", |
| + base_config=DataConfig( |
| + data_cls=_lerobot_compat.LeRobotDataset, |
| + dataset_root="/opt/b1k/datasets/spraying_for_bugs", |
| + prompt_from_task=True, |
| + dataset_kwargs={"tolerance_s": 5e-4}, |
| + ), |
| + robot_config_name="b1k/R1Pro", |
| + ), |
| + weight_loader=weight_loaders.CheckpointWeightLoader("gs://openpi-assets/checkpoints/pi05_base/params"), |
| + save_interval=10_000, |
| + num_train_steps=50_000, |
| + assets_base_dir="./outputs/assets", |
| + checkpoint_base_dir="./outputs/checkpoints", |
| + ), |
| + # Task 38 (spraying_for_bugs) -- LoRA fine-tune. Fits on a single L40S (~46 GB), even alongside |
| + # the eval policy server. Lower ceiling than the full fine-tune above. |
| + TrainConfig( |
| + name="pi05_b1k_spraying_for_bugs_lora", |
| + model=pi0_config.Pi0Config( |
| + action_horizon=32, |
| + pi05=True, |
| + paligemma_variant="gemma_2b_lora", |
| + action_expert_variant="gemma_300m_lora", |
| + ), |
| + data=LeRobotB1KDataConfig( |
| + repo_id="spraying_for_bugs", |
| + base_config=DataConfig( |
| + data_cls=_lerobot_compat.LeRobotDataset, |
| + dataset_root="/opt/b1k/datasets/spraying_for_bugs", |
| + prompt_from_task=True, |
| + dataset_kwargs={"tolerance_s": 5e-4}, |
| + ), |
| + robot_config_name="b1k/R1Pro", |
| + ), |
| + weight_loader=weight_loaders.CheckpointWeightLoader("gs://openpi-assets/checkpoints/pi05_base/params"), |
| + freeze_filter=pi0_config.Pi0Config( |
| + action_horizon=32, |
| + pi05=True, |
| + paligemma_variant="gemma_2b_lora", |
| + action_expert_variant="gemma_300m_lora", |
| + ).get_freeze_filter(), |
| + ema_decay=None, |
| + save_interval=10_000, |
| + num_train_steps=50_000, |
| + batch_size=16, |
| + assets_base_dir="./outputs/assets", |
| + checkpoint_base_dir="./outputs/checkpoints", |
| + ), |
| # |
| # Fine-tuning Libero configs. |
| # |
|
|
