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  1. README.md +147 -1
  2. nd/uniskill_policy/config.json +321 -0
  3. nd/vid2robot/action_codec.json +23 -0
  4. nd/vid2robot/train_config.json +41 -0
  5. nd/vid_cond_pi05_keyframes/demonstration_config.txt +1 -0
  6. nd/vid_cond_pi05_keyframes/train_config.json +44 -0
  7. nd/vid_cond_pi05_uniform/49999/_CHECKPOINT_METADATA +1 -0
  8. nd/vid_cond_pi05_uniform/49999/params/_METADATA +1 -0
  9. nd/vid_cond_pi05_uniform/49999/params/_sharding +1 -0
  10. nd/vid_cond_pi05_uniform/49999/params/array_metadatas/process_0 +1 -0
  11. nd/vid_cond_pi05_uniform/49999/params/d/d32119b3d2dfd382389d3f2c90d8a90d +0 -0
  12. nd/vid_cond_pi05_uniform/49999/params/manifest.ocdbt +0 -0
  13. nd/vid_cond_pi05_uniform/49999/params/ocdbt.process_0/d/42b48d5f4d05f66fc27364ca84387fc2 +0 -0
  14. nd/vid_cond_pi05_uniform/49999/params/ocdbt.process_0/manifest.ocdbt +0 -0
  15. nd/vid_cond_pi05_uniform/demonstration_config.txt +1 -0
  16. nd/vid_cond_pi05_uniform/train_config.json +42 -0
  17. nd/vlm_pi05/norm_stats.json +126 -0
  18. nd/vlm_pi05/train_config.json +32 -0
  19. wd/uniskill_policy/config.json +321 -0
  20. wd/vid2robot/action_codec.json +23 -0
  21. wd/vid2robot/train_config.json +41 -0
  22. wd/vid_cond_pi05_keyframes/20000/_CHECKPOINT_METADATA +1 -0
  23. wd/vid_cond_pi05_keyframes/20000/params/_METADATA +1 -0
  24. wd/vid_cond_pi05_keyframes/20000/params/_sharding +1 -0
  25. wd/vid_cond_pi05_keyframes/20000/params/array_metadatas/process_0 +1 -0
  26. wd/vid_cond_pi05_keyframes/20000/params/d/acaf3a3ab0bc7e3801ea16ae3b828fbf +0 -0
  27. wd/vid_cond_pi05_keyframes/20000/params/manifest.ocdbt +0 -0
  28. wd/vid_cond_pi05_keyframes/20000/params/ocdbt.process_0/d/39ff046da2d1e741a6f124a57b6f570c +0 -0
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  30. wd/vid_cond_pi05_keyframes/20000/params/ocdbt.process_0/d/ba0b2c40dd775359d0c1a2e0ab3e28bb +0 -0
  31. wd/vid_cond_pi05_keyframes/20000/params/ocdbt.process_0/d/d5a1594446627af3630d303ec7375581 +0 -0
  32. wd/vid_cond_pi05_keyframes/20000/params/ocdbt.process_0/manifest.ocdbt +0 -0
  33. wd/vid_cond_pi05_keyframes/demonstration_config.txt +1 -0
  34. wd/vid_cond_pi05_keyframes/train_config.json +44 -0
  35. wd/vid_cond_pi05_uniform/49999/_CHECKPOINT_METADATA +1 -0
  36. wd/vid_cond_pi05_uniform/49999/params/_METADATA +1 -0
  37. wd/vid_cond_pi05_uniform/49999/params/_sharding +1 -0
  38. wd/vid_cond_pi05_uniform/49999/params/array_metadatas/process_0 +1 -0
  39. wd/vid_cond_pi05_uniform/49999/params/d/cddaa6bc8c53d6d22814e861ddb32dbc +0 -0
  40. wd/vid_cond_pi05_uniform/49999/params/manifest.ocdbt +0 -0
  41. wd/vid_cond_pi05_uniform/49999/params/ocdbt.process_0/d/7aad8273dd3d2723c9a2a0a5ac05c925 +0 -0
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  46. wd/vid_cond_pi05_uniform/demonstration_config.txt +1 -0
  47. wd/vid_cond_pi05_uniform/train_config.json +43 -0
  48. wd/vlm_pi05/050000/config.json +92 -0
  49. wd/vlm_pi05/norm_stats.json +126 -0
  50. wd/vlm_pi05/train_config.json +32 -0
README.md CHANGED
@@ -1,3 +1,149 @@
1
  ---
2
- license: mit
 
 
 
 
 
 
 
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ license: other
3
+ license_name: see-model-card
4
+ license_link: https://huggingface.co/LogosRoboticsLab/roboreel_models#licensing
5
+ pipeline_tag: robotics
6
+ tags:
7
+ - robotics
8
+ - imitation-learning
9
+ - learning-from-observation
10
+ - manipulation
11
+ - benchmark
12
  ---
13
+
14
+ # RoboReel — evaluated policy checkpoints
15
+
16
+ Policy checkpoints for **"Monkey See, Can Monkey Do? A Benchmark for Evaluating
17
+ Robot Skill Learning by Observation"** ([arXiv:2609.08209](https://arxiv.org/abs/2609.08209)),
18
+ benchmark **RoboReel** · [project page](https://roboreel.github.io).
19
+
20
+ Each folder holds **exactly the checkpoint the paper's numbers were computed
21
+ from** — not the last checkpoint a run happened to write. Training code,
22
+ evaluation harness and configs live in the `roboreel_models` repository; the
23
+ simulation environments live in the benchmark environment repository.
24
+
25
+ ## Layout
26
+
27
+ ```
28
+ <condition>/<method>/
29
+ ├── train_config.json # the run's own config (see "Paths" below)
30
+ ├── <sidecar> # norm_stats.json | action_codec.json | demonstration_config.txt
31
+ └── <step>/ # the evaluated checkpoint
32
+ ```
33
+
34
+ `<condition>` is the training suite, and it is the **top** level: **`nd/`** = no
35
+ distraction (clean scenes), **`wd/`** = with distraction (distractors in both
36
+ train and eval). So the keyframe policy trained with distractors is
37
+ `wd/vid_cond_pi05_keyframes/20000/`.
38
+
39
+ The paper's third suite, **ED** (clean training, distracted evaluation), needs
40
+ no extra weights — it evaluates everything under `nd/` against the WD scene
41
+ bank.
42
+
43
+ ## Checkpoints
44
+
45
+ | Paper label | Method dir | ND step (`nd/`) | WD step (`wd/`) | Size each |
46
+ |---|---|---|---|---|
47
+ | VLM + π0.5 | `vlm_pi05` | `050000` | `050000` | 9.35 GB |
48
+ | Vid. Cond. π0.5 (Uniform) | `vid_cond_pi05_uniform` | `49999` | `49999` | 6.20 GB |
49
+ | Vid. Cond. π0.5 (Keyframes) | `vid_cond_pi05_keyframes` | `49999` | **`20000`** | 6.20 GB |
50
+ | Vid2Robot | `vid2robot` | `vid2robot_step50000.pt` | `vid2robot_step50000.pt` | 2.37 GB |
51
+ | UniSkill | `uniskill_policy` | `models/model_epoch_1000.pth` | `models/model_epoch_1000.pth` | 0.74 GB |
52
+
53
+ Two things about the step numbers that are easy to misread:
54
+
55
+ - **openpi/orbax saves at `num_train_steps - 1`**, so a 50k-step run ends at
56
+ `49999`, unpadded. The LeRobot trainer saves at `num_train_steps` and
57
+ zero-pads, so the same run length ends at `050000`.
58
+ - **WD keyframes is step `20000`, not `49999`.** That run reached 20k steps;
59
+ it is the checkpoint the reported WD keyframe numbers come from.
60
+
61
+ UniSkill is a Robomimic diffusion policy over skill representations produced by
62
+ an **off-the-shelf, un-finetuned UniSkill inverse-skill-dynamics model**. That
63
+ ISD is deliberately *not* redistributed here — take it from the UniSkill
64
+ authors' own release and use it unmodified.
65
+
66
+ ## Training setup
67
+
68
+ Common to all runs: 10 tasks (`bowl_in_plate`, `close_drawer`, `empty_basket`,
69
+ `open_lid`, `pick_cube`, `press_toaster`, `push_cube`, `stack_cups`,
70
+ `toys_in_basket`, `toys_in_drawer`), 80 demonstrations per task
71
+ (`max_demo_index: 79`), 8-D state and action.
72
+
73
+ | Method | Setup |
74
+ |---|---|
75
+ | VLM + π0.5 | π0.5 full fine-tune from `lerobot/pi05_base`, expert-only; AdamW, peak LR 2.5e-5 cosine→0.1×, batch 32, bf16, gradient checkpointing, 50k steps, action chunk 20, seed 42. Instructions generated by Qwen3-VL-4B from the human video. |
76
+ | Vid. Cond. π0.5 (Uniform) | openpi π0.5 from `pi05_base`, JAX FSDP; AdamW (β 0.9/0.95, ε 1e-8, wd 1e-10), grad clip 1.0, peak LR 5e-5, 1k warmup, EMA 0.999, batch 64, 50k steps, seed 42. Demonstration tokens: 512 tokens / 32 frames / 16 tokens per frame, uniform frame sampling. Demo camera `front`, robot cameras `base_camera` + `hand_camera`. |
77
+ | Vid. Cond. π0.5 (Keyframes) | Identical to Uniform — **only frame selection differs**: GPT-5.4-mini best-point-prompt keyframes over the human video downsampled to 2 fps. |
78
+ | Vid2Robot | ViT-B/16 encoders, 2-layer Perceiver Resamplers (64 latents), 4-layer decoders d=768, 16 prompt / 8 state frames, action chunk 4 over 256 bins; AdamW peak 3e-4 → 1e-6, wd 0.05, 2k warmup, batch 32, 50k steps, seed 42. |
79
+ | UniSkill | Robomimic diffusion policy only; Adam 1e-4, batch 256, 1000 epochs × 100 iters = 100k steps, EMA power 0.75, 100 DDPM train / 10 DDIM inference steps, `skill_aug` aug_num 5, seed 0. |
80
+
81
+ Every value above is also recorded verbatim in each folder's
82
+ `train_config.json`.
83
+
84
+ ## Paths
85
+
86
+ `train_config.json` and the UniSkill `config.json` are the configs the runs
87
+ were actually launched with, with one edit: **host-specific absolute paths were
88
+ rewritten to placeholders**, since they pointed at cluster mounts that nobody
89
+ else has. Everything else is untouched.
90
+
91
+ | Placeholder | Set it to |
92
+ |---|---|
93
+ | `${ROBOREEL_DATA}` | your RoboReel dataset root |
94
+ | `${ROBOREEL_CKPT}` | where you downloaded this repo |
95
+ | `${OPENPI_DATA_HOME}` | your openpi asset cache (holds `openpi-assets/checkpoints/pi05_base`) |
96
+
97
+ The evaluation harness reads `data_root` / `data_dir` out of
98
+ `train_config.json` to locate the human demonstration videos, so these must be
99
+ pointed at a real dataset root before evaluating.
100
+
101
+ ## Download
102
+
103
+ ```bash
104
+ pip install -U huggingface_hub
105
+
106
+ # one method + condition
107
+ hf download LogosRoboticsLab/roboreel_models \
108
+ --include "nd/vid_cond_pi05_keyframes/*" --local-dir ./roboreel_ckpt
109
+
110
+ # one condition, all five methods
111
+ hf download LogosRoboticsLab/roboreel_models \
112
+ --include "nd/*" --local-dir ./roboreel_ckpt
113
+
114
+ # everything (≈50 GB)
115
+ hf download LogosRoboticsLab/roboreel_models --local-dir ./roboreel_ckpt
116
+ ```
117
+
118
+ ## Not in this repo
119
+
120
+ - **The RoboReel dataset** (human videos, robot trajectories, keyframe
121
+ annotations, skill representations) — released separately.
122
+ - **SeeDo** and **PointPolicy** checkpoints — two of the paper's seven methods,
123
+ to be added.
124
+ - **BC-Z** — discussed in related work only, never evaluated.
125
+ - Base/pretrained weights that are not ours to redistribute: `pi05_base`,
126
+ PaliGemma, CLIP, Depth-Anything-V2, and the UniSkill ISD.
127
+
128
+ ## Licensing
129
+
130
+ Mixed, because the checkpoints are derived from different base models:
131
+
132
+ - `vlm_pi05`, `vid_cond_pi05_uniform` and `vid_cond_pi05_keyframes` are
133
+ fine-tunes of **π0.5** (openpi, Apache-2.0), whose backbone is **PaliGemma /
134
+ Gemma** — these weights are therefore also subject to the
135
+ [Gemma Terms of Use](https://ai.google.dev/gemma/terms).
136
+ - `uniskill_policy` is a Robomimic diffusion policy trained on
137
+ representations from **UniSkill**; see the UniSkill release for its terms.
138
+ - `vid2robot` is trained from scratch on the RoboReel dataset apart from its
139
+ ImageNet-pretrained ViT-B/16 and SigLIP text encoder.
140
+
141
+ ## Citation
142
+
143
+ ```bibtex
144
+ @article{roboreel2026,
145
+ title = {Monkey See, Can Monkey Do? A Benchmark for Evaluating Robot Skill Learning by Observation},
146
+ journal = {arXiv preprint arXiv:2609.08209},
147
+ year = {2026}
148
+ }
149
+ ```
nd/uniskill_policy/config.json ADDED
@@ -0,0 +1,321 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "algo_name": "diffusion_policy",
3
+ "experiment": {
4
+ "name": "exp3_uniskill_policy_pretrained_isd/seed_0",
5
+ "validate": false,
6
+ "logging": {
7
+ "terminal_output_to_txt": true,
8
+ "log_tb": true,
9
+ "log_wandb": false,
10
+ "wandb_proj_name": "uniskill"
11
+ },
12
+ "mse": {
13
+ "enabled": false,
14
+ "every_n_epochs": 50,
15
+ "on_save_ckpt": true,
16
+ "num_samples": 20,
17
+ "visualize": true
18
+ },
19
+ "save": {
20
+ "enabled": true,
21
+ "every_n_seconds": null,
22
+ "every_n_epochs": 100,
23
+ "epochs": [],
24
+ "on_best_validation": false,
25
+ "on_best_rollout_return": false,
26
+ "on_best_rollout_success_rate": false
27
+ },
28
+ "epoch_every_n_steps": 100,
29
+ "validation_epoch_every_n_steps": 10,
30
+ "env": null,
31
+ "additional_envs": null,
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+ "render": false,
33
+ "render_video": true,
34
+ "keep_all_videos": false,
35
+ "video_skip": 5,
36
+ "rollout": {
37
+ "enabled": false,
38
+ "n": 10,
39
+ "horizon": 200,
40
+ "rate": 100,
41
+ "warmstart": 0,
42
+ "terminate_on_success": true,
43
+ "batched": false,
44
+ "num_batch_envs": 5,
45
+ "idm_path": null
46
+ },
47
+ "env_meta_update_dict": {},
48
+ "ckpt_path": null
49
+ },
50
+ "train": {
51
+ "data": [
52
+ {
53
+ "path": "${ROBOREEL_DATA}/robomimic_hdf5/without_distraction/bowl_in_plate.hdf5",
54
+ "horizon": 500,
55
+ "do_eval": false
56
+ },
57
+ {
58
+ "path": "${ROBOREEL_DATA}/robomimic_hdf5/without_distraction/close_drawer.hdf5",
59
+ "horizon": 500,
60
+ "do_eval": false
61
+ },
62
+ {
63
+ "path": "${ROBOREEL_DATA}/robomimic_hdf5/without_distraction/empty_basket.hdf5",
64
+ "horizon": 500,
65
+ "do_eval": false
66
+ },
67
+ {
68
+ "path": "${ROBOREEL_DATA}/robomimic_hdf5/without_distraction/open_lid.hdf5",
69
+ "horizon": 500,
70
+ "do_eval": false
71
+ },
72
+ {
73
+ "path": "${ROBOREEL_DATA}/robomimic_hdf5/without_distraction/pick_cube.hdf5",
74
+ "horizon": 500,
75
+ "do_eval": false
76
+ },
77
+ {
78
+ "path": "${ROBOREEL_DATA}/robomimic_hdf5/without_distraction/press_toaster.hdf5",
79
+ "horizon": 500,
80
+ "do_eval": false
81
+ },
82
+ {
83
+ "path": "${ROBOREEL_DATA}/robomimic_hdf5/without_distraction/push_cube.hdf5",
84
+ "horizon": 500,
85
+ "do_eval": false
86
+ },
87
+ {
88
+ "path": "${ROBOREEL_DATA}/robomimic_hdf5/without_distraction/stack_cups.hdf5",
89
+ "horizon": 500,
90
+ "do_eval": false
91
+ },
92
+ {
93
+ "path": "${ROBOREEL_DATA}/robomimic_hdf5/without_distraction/toys_in_basket.hdf5",
94
+ "horizon": 500,
95
+ "do_eval": false
96
+ },
97
+ {
98
+ "path": "${ROBOREEL_DATA}/robomimic_hdf5/without_distraction/toys_in_drawer.hdf5",
99
+ "horizon": 500,
100
+ "do_eval": false
101
+ }
102
+ ],
103
+ "output_dir": "${ROBOREEL_CKPT}/nd/uniskill_idm_policy_pretrained_isd/train",
104
+ "num_data_workers": 16,
105
+ "hdf5_cache_mode": "low_dim",
106
+ "hdf5_use_swmr": true,
107
+ "hdf5_load_next_obs": false,
108
+ "hdf5_normalize_obs": false,
109
+ "hdf5_filter_key": null,
110
+ "hdf5_validation_filter_key": null,
111
+ "seq_length": 15,
112
+ "pad_seq_length": true,
113
+ "frame_stack": 2,
114
+ "pad_frame_stack": true,
115
+ "dataset_keys": [
116
+ "actions"
117
+ ],
118
+ "action_keys": [
119
+ "actions"
120
+ ],
121
+ "action_config": {
122
+ "actions": {
123
+ "normalization": "min_max"
124
+ },
125
+ "action_dict/abs_pos": {
126
+ "normalization": "min_max"
127
+ },
128
+ "action_dict/abs_rot_axis_angle": {
129
+ "normalization": "min_max",
130
+ "format": "rot_axis_angle"
131
+ },
132
+ "action_dict/abs_rot_6d": {
133
+ "normalization": null,
134
+ "format": "rot_6d"
135
+ },
136
+ "action_dict/rel_pos": {
137
+ "normalization": null
138
+ },
139
+ "action_dict/rel_rot_axis_angle": {
140
+ "normalization": null,
141
+ "format": "rot_axis_angle"
142
+ },
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+ "action_dict/rel_rot_6d": {
144
+ "normalization": null,
145
+ "format": "rot_6d"
146
+ },
147
+ "action_dict/gripper": {
148
+ "normalization": null
149
+ },
150
+ "action_dict/base_mode": {
151
+ "normalization": null
152
+ }
153
+ },
154
+ "goal_mode": "skill",
155
+ "skill_dir": "${ROBOREEL_DATA}/UniSkill_skill_representations/pretrained_robot/without_distraction",
156
+ "skill_aug": true,
157
+ "aug_num": 5,
158
+ "cuda": true,
159
+ "batch_size": 256,
160
+ "num_epochs": 1000,
161
+ "seed": 0,
162
+ "max_grad_norm": null,
163
+ "data_format": "robomimic",
164
+ "shuffled_obs_key_groups": null
165
+ },
166
+ "algo": {
167
+ "optim_params": {
168
+ "policy": {
169
+ "learning_rate": {
170
+ "initial": 0.0001,
171
+ "decay_factor": 0.1,
172
+ "epoch_schedule": [],
173
+ "scheduler_type": "constant"
174
+ },
175
+ "regularization": {
176
+ "L2": 0.0
177
+ }
178
+ }
179
+ },
180
+ "horizon": {
181
+ "observation_horizon": 2,
182
+ "action_horizon": 8,
183
+ "prediction_horizon": 16
184
+ },
185
+ "subgoal": {
186
+ "enabled": false,
187
+ "subgoal_dim": 64
188
+ },
189
+ "skill": {
190
+ "enabled": true,
191
+ "skill_dim": 64,
192
+ "dropout": false,
193
+ "dropout_rate": 0.2
194
+ },
195
+ "lang": {
196
+ "enabled": false,
197
+ "lang_dim": 512
198
+ },
199
+ "unet": {
200
+ "enabled": true,
201
+ "diffusion_step_embed_dim": 256,
202
+ "down_dims": [
203
+ 256,
204
+ 512,
205
+ 1024
206
+ ],
207
+ "kernel_size": 5,
208
+ "n_groups": 8
209
+ },
210
+ "ema": {
211
+ "enabled": true,
212
+ "power": 0.75
213
+ },
214
+ "language_conditioned": false,
215
+ "ddpm": {
216
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wd/vid_cond_pi05_keyframes/demonstration_config.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ perceptual-keyframe-context.yaml
wd/vid_cond_pi05_keyframes/train_config.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "demonstration_config": "perceptual-keyframe-context.yaml",
3
+ "use_demonstration": true,
4
+ "prompt": "complete the task",
5
+ "batch_size": 64,
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+ "num_train_steps": 50000,
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+ "peak_lr": 5e-05,
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+ "warmup_steps": 1000,
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+ "ema_decay": 0.999,
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+ "grad_clip": 1.0,
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+ "seed": 43,
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+ "fsdp_devices": 1,
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+ "log_interval": 50,
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+ "save_interval": 5000,
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+ "wandb": false,
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+ "lfo_max_demo_index": 79,
17
+ "include_video_types": [
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+ "with_distraction"
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+ ],
20
+ "paired_sampling": null,
21
+ "keyframe_annotation_dir": "${ROBOREEL_DATA}/bpp_keyframe_annotations",
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+ "demo_cameras": [
23
+ "front"
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+ ],
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+ "robot_cameras": [
26
+ "base_camera",
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+ "hand_camera"
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+ ],
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+ "output_dir": "${ROBOREEL_CKPT}/wd/pi05_video_perceptual_context_bpp",
30
+ "checkpoint_dir": "${OPENPI_DATA_HOME}/openpi-assets/checkpoints/pi05_base",
31
+ "data_dir": "${ROBOREEL_DATA}",
32
+ "tasks": [
33
+ "bowl_in_plate",
34
+ "close_drawer",
35
+ "empty_basket",
36
+ "open_lid",
37
+ "pick_cube",
38
+ "press_toaster",
39
+ "push_cube",
40
+ "stack_cups",
41
+ "toys_in_basket",
42
+ "toys_in_drawer"
43
+ ]
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+ }
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