Add level2_dexterous_from_gripper (suite transfer: level2_dexterous tasks from the final level2_gripper policy, 50k further steps; evaluation pending)

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multi_task/level2_dexterous_from_gripper/metadata.json

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+{
+ "suite": "level2_dexterous_from_gripper",
+ "suite_id": "x_gripper2dex",
+ "description": "level2_dexterous tasks, initialised from the final level2_gripper policy (suite transfer), 50k further steps",
+ "campaign": "pi05_lv2xfer_20261101",
+ "tasks": [
+  "GraspTwoBlocks-v1",
+  "ReorientPen-v1",
+  "DexOpenDoor-v1",
+  "HammerNailOut-v1",
+  "ClothWipe-v1",
+  "RollingPin-v1",
+  "RopeBridgeDex-v1",
+  "DualArmOpenLaptop-v1",
+  "DualArmThrowBlock-v1",
+  "DualArmJugglingBall-v1",
+  "DualArmOpenBottle-v1",
+  "DualArmPlaceRopeOverRod-v1",
+  "DualArmStuffCloth-v1",
+  "DualArmPouringTwoCups-v1"
+ ],
+ "experiment": "suite transfer: continue the finished level-2 subset policy of another grouping on this suite's tasks",
+ "method": "PI0.5 LoRA + trainable weights, multi-task (one policy for all tasks in the suite)",
+ "base_checkpoint": "gs://openpi-assets/checkpoints/pi05_base/params",
+ "init_from": {
+  "suite": "level2_gripper",
+  "campaign": "pi05_lv2sub_20261029",
+  "commit": "ec4b6e083f09412a55703bdf8acb2720494d19c3",
+  "npz": "multi_task/level2_gripper/lora_step_0050000.npz",
+  "npz_sha256": "33de9edb557df8fd9dbb569f7f4a97fb0e6b622ba55340543bd79a4cbe6ec62a",
+  "local_params": "/mnt1/Object_World_Dataset/gck_pi05_lv2sub/checkpoints/maniladder_pi05_lora/pi05_lora_l2gripper/50000/params",
+  "mean_success_rate_on_own_tasks": 0.1657142857142857,
+  "note": "training started from ALL parameters of the final level2_gripper checkpoint (= pi05_base + its lora_step_0050000.npz trainable tensors), i.e. LoRA and the trained vision/action layers continue from that policy; optimizer state and lr schedule restart"
+ },
+ "target_suite": "level2_dexterous",
+ "source_suite": "level2_gripper",
+ "checkpoints": [
+  {
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+   "step": 10000,
+   "sha256": "daedd8354841e9961c2eaa7124a9336d099310f4c569e9374cb70116ac81afcf",
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+ "evaluated_checkpoint": "lora_step_0050000.npz",
+ "tensor_count": 51,
+ "action_dim": 44,
+ "state_dim": 44,
+ "action_dim_note": "44 = union of all level-2 embodiments (dual-arm dexterous); narrower embodiments are zero-padded",
+ "action_horizon": 50,
+ "max_token_len": 200,
+ "image_size": 224,
+ "exec_steps": 16,
+ "sample_steps": 10,
+ "control_mode": "pd_ee_delta_pose",
+ "state_input": "zero vector",
+ "cameras": [
+  "front_camera",
+  "robot_camera",
+  "robot_camera_0",
+  "robot_camera_1"
+ ],
+ "missing_right_wrist_image": "zeros",
+ "num_demos_per_task": 20,
+ "train_episodes": 280,
+ "train_frames": 122192,
+ "train_steps": 50000,
+ "batch_size": 64,
+ "lr": 5e-05,
+ "warmup_steps": 1000,
+ "lr_schedule": "cosine decay over all 50000 steps to 5e-6 (fresh schedule, not a continuation of the source run)",
+ "data_parallel": "pure data parallel (fsdp_devices=1), 4-8 GPUs, global batch 64",
+ "norm_stats_file": "norm_stats.json",
+ "norm_stats_sha256": "9397d7156f3f5609f19545d375553f34f430b3fa44336d3e63d32035ff422ba7",
+ "norm_stats_note": "the level2_dexterous statistics of pi05_lv2sub_20261029 (same frames); padded dims repaired",
+ "training_data": "Linslab/ManiLadder_Dataset raw/<task>, 20 demos per task (14 tasks, 280 episodes, 122192 frames)",
+ "task_sources": {
+  "GraspTwoBlocks-v1": {
+   "path": "maniladder/envs/rigid_body/single_arm_dex/level_2/grasp_blocks.py",
+   "sha256": "5ca6052059d89129ea2053033b959eafe590e119664bbcf431143d371650d66e",
+   "level": "level_2",
+   "category": "rigid_body/single_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera",
+    null
+   ]
+  },
+  "ReorientPen-v1": {
+   "path": "maniladder/envs/rigid_body/single_arm_dex/level_2/reorient_pen.py",
+   "sha256": "cb46bbdf5dc53cc310e613a1556720d34b444b1333421682cd9b5133972aa386",
+   "level": "level_2",
+   "category": "rigid_body/single_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera",
+    null
+   ]
+  },
+  "DexOpenDoor-v1": {
+   "path": "maniladder/envs/rigid_body/single_arm_dex/level_2/open_door.py",
+   "sha256": "6c21f64c2a98c359f1d01c67743cd590799b763ba3e1b933b7204d798312d062",
+   "level": "level_2",
+   "category": "rigid_body/single_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera",
+    null
+   ]
+  },
+  "HammerNailOut-v1": {
+   "path": "maniladder/envs/rigid_body/single_arm_dex/level_2/hammer_nail_out.py",
+   "sha256": "f524116a35ee681f0573ed934a47914d71d1ab9ca9cfd610f7d43a574cb8bac4",
+   "level": "level_2",
+   "category": "rigid_body/single_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera",
+    null
+   ]
+  },
+  "ClothWipe-v1": {
+   "path": "maniladder/envs/deformable/single_arm_dex/level_2/cloth_wipe.py",
+   "sha256": "45ce8bb2815accba3fae96c9411bc24a4c176607691392b121c31c75ebf6d9e4",
+   "level": "level_2",
+   "category": "deformable/single_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera",
+    null
+   ]
+  },
+  "RollingPin-v1": {
+   "path": "maniladder/envs/deformable/single_arm_dex/level_2/rooling_pin.py",
+   "sha256": "b8d9b39ad2753b9e8f97b8d9117ba1c1c6c16005d90cbab3c8fa30505b4fb62f",
+   "level": "level_2",
+   "category": "deformable/single_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera",
+    null
+   ]
+  },
+  "RopeBridgeDex-v1": {
+   "path": "maniladder/envs/deformable/single_arm_dex/level_2/rope_bridge.py",
+   "sha256": "bdae492d46519fea218838c421eb3217df1dea4ecd0ec2358df099f4dfc2765f",
+   "level": "level_2",
+   "category": "deformable/single_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera",
+    null
+   ]
+  },
+  "DualArmOpenLaptop-v1": {
+   "path": "maniladder/envs/rigid_body/dual_arm_dex/level_2/open_laptop.py",
+   "sha256": "e2c3c0714da9a484ed7a7ac3dc6374f61c7e1867167f50b37dca9845534faf93",
+   "level": "level_2",
+   "category": "rigid_body/dual_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera_0",
+    "robot_camera_1"
+   ]
+  },
+  "DualArmThrowBlock-v1": {
+   "path": "maniladder/envs/rigid_body/dual_arm_dex/level_2/throw_ball.py",
+   "sha256": "0a00a7e724272b98eb42cd58fb57f6e15756a6e115f19f320febda6dda6d7680",
+   "level": "level_2",
+   "category": "rigid_body/dual_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera_0",
+    "robot_camera_1"
+   ]
+  },
+  "DualArmJugglingBall-v1": {
+   "path": "maniladder/envs/rigid_body/dual_arm_dex/level_2/juggle_ball.py",
+   "sha256": "f5a65ccfa2d7aa379f131628849315ce1840b5e11620e5f6a86c6a3451706ed1",
+   "level": "level_2",
+   "category": "rigid_body/dual_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera_0",
+    "robot_camera_1"
+   ]
+  },
+  "DualArmOpenBottle-v1": {
+   "path": "maniladder/envs/rigid_body/dual_arm_dex/level_2/open_bottle.py",
+   "sha256": "6c492aff17adfba725a0f605df5394f4fe93e04ef122cf473a210e4a2cf84e2f",
+   "level": "level_2",
+   "category": "rigid_body/dual_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera_0",
+    "robot_camera_1"
+   ]
+  },
+  "DualArmPlaceRopeOverRod-v1": {
+   "path": "maniladder/envs/deformable/dual_arm_dex/level_2/drape_rope.py",
+   "sha256": "670f1e36c3cd79cbce17b8e6a6fd5edd57816b15dcd8aad748be5a669b8fe14c",
+   "level": "level_2",
+   "category": "deformable/dual_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera_0",
+    "robot_camera_1"
+   ]
+  },
+  "DualArmStuffCloth-v1": {
+   "path": "maniladder/envs/deformable/dual_arm_dex/level_2/stuff_cloth.py",
+   "sha256": "5b93ca100fb7b035fa07f9c334e1dce162baf7915a1bbf56cae0f1d78f5d56f8",
+   "level": "level_2",
+   "category": "deformable/dual_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera_0",
+    "robot_camera_1"
+   ]
+  },
+  "DualArmPouringTwoCups-v1": {
+   "path": "maniladder/envs/deformable/dual_arm_dex/level_2/water_cup.py",
+   "sha256": "4ac7b0bf11eecec6703389831a8711f66875b4dbfedbe6ab8a5faf04ceb9281d",
+   "level": "level_2",
+   "category": "deformable/dual_arm_dex",
+   "cameras": [
+    "front_camera",
+    "robot_camera_0",
+    "robot_camera_1"
+   ]
+  }
+ },
+ "eval_episodes": 50,
+ "eval_seed_base": 1000,
+ "evaluated_steps": [
+  50000
+ ],
+ "selection": "final checkpoint only (no checkpoint selection)",
+ "eval_status": "pending (eval_result.json and eval_reports/ are added when the 50-episode sweep finishes)"
+}

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