Instructions to use Dimios45/pickblock_bspline_act with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use Dimios45/pickblock_bspline_act with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- README.md +255 -0
- checkpoints/010000/pretrained_model/config.json +83 -0
- checkpoints/010000/pretrained_model/model.safetensors +3 -0
- checkpoints/010000/pretrained_model/policy_postprocessor.json +12 -0
- checkpoints/010000/pretrained_model/policy_preprocessor.json +64 -0
- checkpoints/010000/pretrained_model/policy_preprocessor_step_3_normalizer_processor.safetensors +3 -0
- checkpoints/010000/pretrained_model/train_config.json +230 -0
- checkpoints/020000/pretrained_model/config.json +83 -0
- checkpoints/020000/pretrained_model/model.safetensors +3 -0
- checkpoints/020000/pretrained_model/policy_postprocessor.json +12 -0
- checkpoints/020000/pretrained_model/policy_preprocessor.json +64 -0
- checkpoints/020000/pretrained_model/policy_preprocessor_step_3_normalizer_processor.safetensors +3 -0
- checkpoints/020000/pretrained_model/train_config.json +230 -0
- checkpoints/030000/pretrained_model/config.json +83 -0
- checkpoints/030000/pretrained_model/model.safetensors +3 -0
- checkpoints/030000/pretrained_model/policy_postprocessor.json +12 -0
- checkpoints/030000/pretrained_model/policy_preprocessor.json +64 -0
- checkpoints/030000/pretrained_model/policy_preprocessor_step_3_normalizer_processor.safetensors +3 -0
- checkpoints/030000/pretrained_model/train_config.json +230 -0
- checkpoints/040000/pretrained_model/config.json +83 -0
- checkpoints/040000/pretrained_model/model.safetensors +3 -0
- checkpoints/040000/pretrained_model/policy_postprocessor.json +12 -0
- checkpoints/040000/pretrained_model/policy_preprocessor.json +64 -0
- checkpoints/040000/pretrained_model/policy_preprocessor_step_3_normalizer_processor.safetensors +3 -0
- checkpoints/040000/pretrained_model/train_config.json +230 -0
- config.json +83 -0
- model.safetensors +3 -0
- policy_postprocessor.json +12 -0
- policy_preprocessor.json +64 -0
- policy_preprocessor_step_3_normalizer_processor.safetensors +3 -0
- train_config.json +230 -0
README.md
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|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
library_name: lerobot
|
| 4 |
+
pipeline_tag: robotics
|
| 5 |
+
tags:
|
| 6 |
+
- robotics
|
| 7 |
+
- lerobot
|
| 8 |
+
- imitation-learning
|
| 9 |
+
- act
|
| 10 |
+
- b-spline
|
| 11 |
+
- so101
|
| 12 |
+
- bspline_act
|
| 13 |
+
datasets:
|
| 14 |
+
- atharva-pantheon/pick_block_bowl
|
| 15 |
+
model_name: pickblock_bspline_act
|
| 16 |
+
---
|
| 17 |
+
|
| 18 |
+
# pickblock_bspline_act
|
| 19 |
+
|
| 20 |
+
An [ACT](https://huggingface.co/papers/2304.13705) policy that predicts **B-spline
|
| 21 |
+
trajectory segments** instead of discrete action chunks, trained on SO-101 black-cube
|
| 22 |
+
picking. This is the "Reg.+BSP" variant from
|
| 23 |
+
[B-spline Policy: Accelerating Manipulation Policies via B-spline Action Representations](https://arxiv.org/abs/2607.09648).
|
| 24 |
+
|
| 25 |
+
The policy outputs a curve, so executing `a(n·t)` replays the same trajectory geometry
|
| 26 |
+
n times faster without retraining. Speed-up is an inference flag, verified exact to
|
| 27 |
+
0.000e+00 deviation at 2× and 4×.
|
| 28 |
+
|
| 29 |
+
> [!WARNING]
|
| 30 |
+
> **This model is trained on 13 episodes and does not generalize well.** Held-out error
|
| 31 |
+
> is 22.8° against 6.2° on training data — a 3.7× gap that never closed across 40,000
|
| 32 |
+
> steps. It has never been run on hardware. Treat it as a pipeline validation artifact,
|
| 33 |
+
> not a working policy. See [Evaluation](#evaluation) and [Limitations](#limitations).
|
| 34 |
+
|
| 35 |
+
## Download
|
| 36 |
+
|
| 37 |
+
```bash
|
| 38 |
+
hf download Dimios45/pickblock_bspline_act --local-dir ./pickblock_bspline_act
|
| 39 |
+
```
|
| 40 |
+
|
| 41 |
+
The repository root holds the recommended checkpoint, so `--policy.path` also accepts
|
| 42 |
+
the repo id directly. Individual checkpoints live under `checkpoints/<step>/`.
|
| 43 |
+
|
| 44 |
+
## Run it
|
| 45 |
+
|
| 46 |
+
```bash
|
| 47 |
+
lerobot-rollout \
|
| 48 |
+
--strategy.type=base \
|
| 49 |
+
--policy.path=./pickblock_bspline_act/checkpoints/010000/pretrained_model \
|
| 50 |
+
--policy.speed_up=1.0 \
|
| 51 |
+
--device=cuda \
|
| 52 |
+
--robot.type=so101_follower \
|
| 53 |
+
--robot.port=/dev/ttyACM0 --robot.id=FOLLOWER \
|
| 54 |
+
--robot.cameras='{front: {type: opencv, index_or_path: 0, width: 640, height: 360, fps: 30}, ee: {type: opencv, index_or_path: 4, width: 640, height: 360, fps: 30}}' \
|
| 55 |
+
--task="Grab the black cube" \
|
| 56 |
+
--fps=30 --duration=60
|
| 57 |
+
```
|
| 58 |
+
|
| 59 |
+
`--policy.path` takes either a Hub repo id (`namespace/name`) or a **local directory
|
| 60 |
+
containing `config.json`** — which is the `pretrained_model/` subdirectory, not the
|
| 61 |
+
step directory above it. There is no `--policy.subfolder` flag.
|
| 62 |
+
|
| 63 |
+
### Two things differ from the cup-stacking model — check both
|
| 64 |
+
|
| 65 |
+
**Resolution is 640×360, not 640×480.** The source demonstrations were recorded at
|
| 66 |
+
1920×1080; they were downscaled to 640×360 for training, preserving the 16:9 aspect
|
| 67 |
+
ratio. Your cameras must be configured to match.
|
| 68 |
+
|
| 69 |
+
**The cameras are `front` and `ee`**, not `front` and `gripper`:
|
| 70 |
+
|
| 71 |
+
| Key | Shape |
|
| 72 |
+
|---|---|
|
| 73 |
+
| `observation.images.front` | `(3, 360, 640)` |
|
| 74 |
+
| `observation.images.ee` | `(3, 360, 640)` |
|
| 75 |
+
| `observation.state` | `(6,)` |
|
| 76 |
+
|
| 77 |
+
Joint order is `shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper`,
|
| 78 |
+
in degrees. Swapping the two cameras produces confident but wrong behaviour rather than
|
| 79 |
+
an error.
|
| 80 |
+
|
| 81 |
+
To try the speed-up, raise `--policy.speed_up` to 2.0 or 4.0. The paper reaches 4× on
|
| 82 |
+
cube picking specifically, so this task should tolerate it better than precise-placement
|
| 83 |
+
tasks — but validate at 1× first, and note this policy has not been shown to complete
|
| 84 |
+
the task at any speed.
|
| 85 |
+
|
| 86 |
+
### Requirements
|
| 87 |
+
|
| 88 |
+
This policy type is not in upstream LeRobot. You need a checkout containing the
|
| 89 |
+
`bspline_act` policy, installed with the scipy extra:
|
| 90 |
+
|
| 91 |
+
```bash
|
| 92 |
+
uv pip install -e ".[feetech,bspline]"
|
| 93 |
+
```
|
| 94 |
+
|
| 95 |
+
`scipy>=1.15` is required for `interpolate.generate_knots`.
|
| 96 |
+
|
| 97 |
+
Unnormalization statistics are stored as buffers inside `model.safetensors`, so each
|
| 98 |
+
checkpoint is self-contained — you do not need the training dataset on the robot machine.
|
| 99 |
+
|
| 100 |
+
## Checkpoints
|
| 101 |
+
|
| 102 |
+
| Step | Epoch | Train error | **Held-out error** | Eval loss | |
|
| 103 |
+
|---|---|---|---|---|---|
|
| 104 |
+
| **10000** | 58 | 6.19° | **22.81°** | **0.3903** | **recommended — best** |
|
| 105 |
+
| 20000 | 116 | 4.67° | 24.15° | 0.3986 | |
|
| 106 |
+
| 30000 | 174 | 3.90° | 24.77° | 0.3996 | |
|
| 107 |
+
| 40000 | 234 | 3.44° | 26.22° | 0.4030 | final, worst held-out |
|
| 108 |
+
|
| 109 |
+
Held-out error gets **monotonically worse** after step 10,000 while training error keeps
|
| 110 |
+
falling. Use 10000. Later checkpoints are included only for reproducibility — they are
|
| 111 |
+
strictly worse policies.
|
| 112 |
+
|
| 113 |
+
Error is mean absolute joint error in degrees, worst joint, over each predicted
|
| 114 |
+
segment's horizon (~0.76 s), measured by decoding the spline and comparing against
|
| 115 |
+
ground-truth actions.
|
| 116 |
+
|
| 117 |
+
## Training
|
| 118 |
+
|
| 119 |
+
| | |
|
| 120 |
+
|---|---|
|
| 121 |
+
| Steps | 40,000 |
|
| 122 |
+
| Batch size | 32 |
|
| 123 |
+
| Epochs | 234 |
|
| 124 |
+
| Dataset | [`atharva-pantheon/pick_block_bowl`](https://huggingface.co/datasets/atharva-pantheon/pick_block_bowl) → downscaled → idle-trimmed → B-spline converted |
|
| 125 |
+
| Episodes | **13 train / 3 held out** |
|
| 126 |
+
| Frames | 6,422 (from 10,342; 37.9% boundary idle removed) |
|
| 127 |
+
| Optimizer | AdamW, lr 2e-5 (backbone 1e-5), wd 1e-3 |
|
| 128 |
+
| Precision | bf16 autocast + `channels_last` |
|
| 129 |
+
| Augmentation | ColorJitter (brightness/contrast/saturation/hue/sharpness), up to 3 per frame |
|
| 130 |
+
| Hardware | 1× RTX 4090, ~2 h 45 min total |
|
| 131 |
+
| Seed | 1000 |
|
| 132 |
+
|
| 133 |
+
Augmentation and 10× weight decay were added specifically to combat overfitting. They
|
| 134 |
+
slowed the fit to training data and **moved held-out loss by 0.0003**. An unaugmented
|
| 135 |
+
control run is available on request; the two are indistinguishable on unseen data.
|
| 136 |
+
|
| 137 |
+
### Preprocessing
|
| 138 |
+
|
| 139 |
+
Source video is 1920×1080 AV1, which is unusable for ACT directly — a ResNet18
|
| 140 |
+
stride-32 feature map is 34×60, putting over 4,000 tokens into the transformer encoder
|
| 141 |
+
across two cameras. Transcoded to 640×360 H.264, which also sped up random-access
|
| 142 |
+
decode from 40 to 183 frames/s per worker.
|
| 143 |
+
|
| 144 |
+
Leading and trailing motionless frames were then removed: 46 s of lead-in and 27 s of
|
| 145 |
+
trailing idle. This dataset is unusually idle-heavy — 37.9% of frames — including
|
| 146 |
+
20 s and 32 s dead stretches at the ends of two episodes where recording continued
|
| 147 |
+
after the task finished.
|
| 148 |
+
|
| 149 |
+
Motion is measured as peak-to-peak joint range over a ±0.5 s window rather than
|
| 150 |
+
frame-to-frame delta, because isolated jitter samples inside a dead stretch defeat a
|
| 151 |
+
delta test and silently leave the idle in.
|
| 152 |
+
|
| 153 |
+
## Architecture
|
| 154 |
+
|
| 155 |
+
Standard ACT with one change: the decoder emits a B-spline **parameter matrix** rather
|
| 156 |
+
than an action chunk.
|
| 157 |
+
|
| 158 |
+
```
|
| 159 |
+
(n_knots, 1 + action_dim) = (16, 7) = 112 values per prediction
|
| 160 |
+
column 0 knot vector, in source-frame units, 0 = "now"
|
| 161 |
+
columns 1: control points, one per joint
|
| 162 |
+
```
|
| 163 |
+
|
| 164 |
+
| | |
|
| 165 |
+
|---|---|
|
| 166 |
+
| Params | 51.6 M |
|
| 167 |
+
| Vision backbone | ResNet18 (ImageNet init, fine-tuned) |
|
| 168 |
+
| dim_model / chunk_size | 512 / 16 |
|
| 169 |
+
| VAE | enabled, kl_weight 10.0 |
|
| 170 |
+
| B-spline degree | 3 (cubic, C² continuous) |
|
| 171 |
+
| bspline_chunk_size | 10 |
|
| 172 |
+
| Fitting tolerance ε | 0.2 (degrees) |
|
| 173 |
+
| Max knot span | 6 frames |
|
| 174 |
+
|
| 175 |
+
The paper uses a DINOv2 encoder for its regression variant; this port uses LeRobot's
|
| 176 |
+
ResNet18, which is what LeRobot's ACT supports. The paper reports no backbone ablation,
|
| 177 |
+
and holds the encoder fixed between its baseline and its B-spline variant, so none of
|
| 178 |
+
its claims depend on that choice.
|
| 179 |
+
|
| 180 |
+
Segments span 0.50–1.10 s (0.76 s mean). The network runs only when a segment is
|
| 181 |
+
exhausted, which decouples policy rate from control rate.
|
| 182 |
+
|
| 183 |
+
### On `max_knot_span`
|
| 184 |
+
|
| 185 |
+
This dataset is why the flag exists. Adaptive knot fitting covers a motionless stretch
|
| 186 |
+
with one enormous knot span, and uncapped fitting here produced segments with a **p95
|
| 187 |
+
of 18.4 seconds** — the policy would commit to eighteen seconds of open-loop motion
|
| 188 |
+
without looking at a camera. Capping span width at 6 frames bounds that at
|
| 189 |
+
`chunk_size × 6` = 2 s, costing 0.04× compression.
|
| 190 |
+
|
| 191 |
+
After correct idle-trimming the uncapped p95 drops to 1.17 s on its own, so the dead
|
| 192 |
+
recording time was the real cause. The cap remains as a cheap safety rail.
|
| 193 |
+
|
| 194 |
+
## Evaluation
|
| 195 |
+
|
| 196 |
+
**Offline only. No hardware evaluation has been performed.**
|
| 197 |
+
|
| 198 |
+
| | Train (13 eps) | **Held-out (3 eps)** |
|
| 199 |
+
|---|---|---|
|
| 200 |
+
| Best checkpoint (10k) | 6.19° | **22.81°** |
|
| 201 |
+
| Final (40k) | 3.44° | 26.22° |
|
| 202 |
+
|
| 203 |
+
Reference points:
|
| 204 |
+
|
| 205 |
+
- **Inter-demonstration spread: 54.83°** — how far apart two human demonstrations of
|
| 206 |
+
this task are, phase-aligned. At 22.8° the policy is well inside that, so it is
|
| 207 |
+
extracting real per-episode information from the cameras rather than replaying an
|
| 208 |
+
average trajectory. This is the one genuinely positive result.
|
| 209 |
+
- **Hold-still baseline: 16.23°.** The policy scores worse than this. Over a 0.76 s
|
| 210 |
+
horizon on a slow task, "don't move" is a decent short-horizon *predictor* while
|
| 211 |
+
being a useless *policy*, so this is not the damning comparison it looks like — but
|
| 212 |
+
combined with the widening train/eval gap it is not encouraging either.
|
| 213 |
+
|
| 214 |
+
Held-out loss plateaued at ~0.39 by step 2,000 and never improved across the remaining
|
| 215 |
+
38,000 steps.
|
| 216 |
+
|
| 217 |
+
### Why the held-out number is a pessimistic bound
|
| 218 |
+
|
| 219 |
+
The split holds out the last 3 of 16 episodes. Inspecting the raw recording:
|
| 220 |
+
|
| 221 |
+
- 8 of 15 episode boundaries are contiguous to under 1° (several to exactly 0.00°), so
|
| 222 |
+
episodes were largely cut from a continuous teleoperation stream. Adjacent episodes
|
| 223 |
+
are correlated, meaning an interleaved split would leak.
|
| 224 |
+
- There is a 97.67° discontinuity between episodes 9 and 10, and episodes 10, 13, 14
|
| 225 |
+
and 15 all end with the gripper open (8–16°) while the other twelve end closed (~2°).
|
| 226 |
+
- **All three held-out episodes sit after that change point**, and two of them *start*
|
| 227 |
+
with the gripper open — a state the model never sees at t=0 in training.
|
| 228 |
+
|
| 229 |
+
So the tail split is biased pessimistic and an interleaved split would be biased
|
| 230 |
+
optimistic. With 16 semi-continuous episodes there is no clean holdout. 22.8° is a
|
| 231 |
+
lower bound on quality, not a verdict.
|
| 232 |
+
|
| 233 |
+
## Limitations
|
| 234 |
+
|
| 235 |
+
- **13 training episodes is too few for this task.** This is the dominant limitation and
|
| 236 |
+
no hyperparameter fixed it. 40–50 demonstrations with varied cube placement and an
|
| 237 |
+
**independent reset between takes** would address both the training and the
|
| 238 |
+
measurement problem.
|
| 239 |
+
- **No hardware evaluation.** Task success rate is unknown, and given the above it
|
| 240 |
+
should not be assumed to be non-zero.
|
| 241 |
+
- **Held-out split is confounded** — see above.
|
| 242 |
+
- **Resolution and camera names differ** from the cup-stacking model. Check both.
|
| 243 |
+
- **Camera assignment is silent when wrong.**
|
| 244 |
+
|
| 245 |
+
## Citation
|
| 246 |
+
|
| 247 |
+
```bibtex
|
| 248 |
+
@article{han2026b,
|
| 249 |
+
title={B-spline Policy: Accelerating Manipulation Policies via B-spline Action Representations},
|
| 250 |
+
author={Han, Xiaoshen and Xiong, Haoyu and Chen, Haonan and Liu, Chaoqi and
|
| 251 |
+
Torralba, Antonio and Zhu, Yuke and Du, Yilun},
|
| 252 |
+
journal={arXiv preprint arXiv:2607.09648},
|
| 253 |
+
year={2026}
|
| 254 |
+
}
|
| 255 |
+
```
|
checkpoints/010000/pretrained_model/config.json
ADDED
|
@@ -0,0 +1,83 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"type": "bspline_act",
|
| 3 |
+
"n_obs_steps": 1,
|
| 4 |
+
"input_features": {
|
| 5 |
+
"observation.state": {
|
| 6 |
+
"type": "STATE",
|
| 7 |
+
"shape": [
|
| 8 |
+
6
|
| 9 |
+
]
|
| 10 |
+
},
|
| 11 |
+
"observation.images.ee": {
|
| 12 |
+
"type": "VISUAL",
|
| 13 |
+
"shape": [
|
| 14 |
+
3,
|
| 15 |
+
360,
|
| 16 |
+
640
|
| 17 |
+
]
|
| 18 |
+
},
|
| 19 |
+
"observation.images.front": {
|
| 20 |
+
"type": "VISUAL",
|
| 21 |
+
"shape": [
|
| 22 |
+
3,
|
| 23 |
+
360,
|
| 24 |
+
640
|
| 25 |
+
]
|
| 26 |
+
}
|
| 27 |
+
},
|
| 28 |
+
"output_features": {
|
| 29 |
+
"action": {
|
| 30 |
+
"type": "ACTION",
|
| 31 |
+
"shape": [
|
| 32 |
+
112
|
| 33 |
+
]
|
| 34 |
+
}
|
| 35 |
+
},
|
| 36 |
+
"device": "cuda",
|
| 37 |
+
"use_amp": false,
|
| 38 |
+
"use_peft": false,
|
| 39 |
+
"push_to_hub": false,
|
| 40 |
+
"repo_id": null,
|
| 41 |
+
"private": null,
|
| 42 |
+
"tags": null,
|
| 43 |
+
"license": null,
|
| 44 |
+
"pretrained_path": "outputs/pickblock_bspline_act_aug/checkpoints/last/pretrained_model",
|
| 45 |
+
"pretrained_revision": null,
|
| 46 |
+
"chunk_size": 16,
|
| 47 |
+
"n_action_steps": 16,
|
| 48 |
+
"normalization_mapping": {
|
| 49 |
+
"VISUAL": "MEAN_STD",
|
| 50 |
+
"STATE": "MEAN_STD",
|
| 51 |
+
"ACTION": "MEAN_STD"
|
| 52 |
+
},
|
| 53 |
+
"vision_backbone": "resnet18",
|
| 54 |
+
"pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
|
| 55 |
+
"replace_final_stride_with_dilation": 0,
|
| 56 |
+
"pre_norm": false,
|
| 57 |
+
"dim_model": 512,
|
| 58 |
+
"n_heads": 8,
|
| 59 |
+
"dim_feedforward": 3200,
|
| 60 |
+
"feedforward_activation": "relu",
|
| 61 |
+
"n_encoder_layers": 4,
|
| 62 |
+
"n_decoder_layers": 1,
|
| 63 |
+
"use_vae": true,
|
| 64 |
+
"latent_dim": 32,
|
| 65 |
+
"n_vae_encoder_layers": 4,
|
| 66 |
+
"temporal_ensemble_coeff": null,
|
| 67 |
+
"dropout": 0.1,
|
| 68 |
+
"kl_weight": 10.0,
|
| 69 |
+
"optimizer_lr": 2e-05,
|
| 70 |
+
"optimizer_weight_decay": 0.001,
|
| 71 |
+
"optimizer_lr_backbone": 1e-05,
|
| 72 |
+
"bspline_degree": 3,
|
| 73 |
+
"bspline_chunk_size": 10,
|
| 74 |
+
"relative_knots": false,
|
| 75 |
+
"speed_up": 1.0,
|
| 76 |
+
"n_decoded_steps": 32,
|
| 77 |
+
"align_segments": true,
|
| 78 |
+
"align_error_threshold": 0.5,
|
| 79 |
+
"align_max_fraction": 0.2,
|
| 80 |
+
"align_exclude_last_dims": 1,
|
| 81 |
+
"replan_margin": 1.0,
|
| 82 |
+
"channels_last": true
|
| 83 |
+
}
|
checkpoints/010000/pretrained_model/model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4e16d5b72180ba0ecf13a77f9a81b69b3f252d9ca457941ff211c19b65859d85
|
| 3 |
+
size 206360820
|
checkpoints/010000/pretrained_model/policy_postprocessor.json
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"name": "policy_postprocessor",
|
| 3 |
+
"steps": [
|
| 4 |
+
{
|
| 5 |
+
"registry_name": "device_processor",
|
| 6 |
+
"config": {
|
| 7 |
+
"device": "cpu",
|
| 8 |
+
"float_dtype": null
|
| 9 |
+
}
|
| 10 |
+
}
|
| 11 |
+
]
|
| 12 |
+
}
|
checkpoints/010000/pretrained_model/policy_preprocessor.json
ADDED
|
@@ -0,0 +1,64 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"name": "policy_preprocessor",
|
| 3 |
+
"steps": [
|
| 4 |
+
{
|
| 5 |
+
"registry_name": "rename_observations_processor",
|
| 6 |
+
"config": {
|
| 7 |
+
"rename_map": {}
|
| 8 |
+
}
|
| 9 |
+
},
|
| 10 |
+
{
|
| 11 |
+
"registry_name": "to_batch_processor",
|
| 12 |
+
"config": {}
|
| 13 |
+
},
|
| 14 |
+
{
|
| 15 |
+
"registry_name": "device_processor",
|
| 16 |
+
"config": {
|
| 17 |
+
"device": "cuda",
|
| 18 |
+
"float_dtype": null
|
| 19 |
+
}
|
| 20 |
+
},
|
| 21 |
+
{
|
| 22 |
+
"registry_name": "normalizer_processor",
|
| 23 |
+
"config": {
|
| 24 |
+
"eps": 1e-08,
|
| 25 |
+
"features": {
|
| 26 |
+
"observation.state": {
|
| 27 |
+
"type": "STATE",
|
| 28 |
+
"shape": [
|
| 29 |
+
6
|
| 30 |
+
]
|
| 31 |
+
},
|
| 32 |
+
"observation.images.ee": {
|
| 33 |
+
"type": "VISUAL",
|
| 34 |
+
"shape": [
|
| 35 |
+
3,
|
| 36 |
+
360,
|
| 37 |
+
640
|
| 38 |
+
]
|
| 39 |
+
},
|
| 40 |
+
"observation.images.front": {
|
| 41 |
+
"type": "VISUAL",
|
| 42 |
+
"shape": [
|
| 43 |
+
3,
|
| 44 |
+
360,
|
| 45 |
+
640
|
| 46 |
+
]
|
| 47 |
+
},
|
| 48 |
+
"action": {
|
| 49 |
+
"type": "ACTION",
|
| 50 |
+
"shape": [
|
| 51 |
+
112
|
| 52 |
+
]
|
| 53 |
+
}
|
| 54 |
+
},
|
| 55 |
+
"norm_map": {
|
| 56 |
+
"VISUAL": "MEAN_STD",
|
| 57 |
+
"STATE": "MEAN_STD",
|
| 58 |
+
"ACTION": "MEAN_STD"
|
| 59 |
+
}
|
| 60 |
+
},
|
| 61 |
+
"state_file": "policy_preprocessor_step_3_normalizer_processor.safetensors"
|
| 62 |
+
}
|
| 63 |
+
]
|
| 64 |
+
}
|
checkpoints/010000/pretrained_model/policy_preprocessor_step_3_normalizer_processor.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:7b1863e4f75643077d48e73b9a90b50bec2e8a27fb3cb5d60195ac41d06ef48e
|
| 3 |
+
size 11544
|
checkpoints/010000/pretrained_model/train_config.json
ADDED
|
@@ -0,0 +1,230 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"dataset": {
|
| 3 |
+
"repo_id": "aryankakad/pick_block_bowl_bspline",
|
| 4 |
+
"root": null,
|
| 5 |
+
"episodes": null,
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checkpoints/020000/pretrained_model/config.json
ADDED
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@@ -0,0 +1,83 @@
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|
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|
| 83 |
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checkpoints/020000/pretrained_model/model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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checkpoints/020000/pretrained_model/policy_postprocessor.json
ADDED
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@@ -0,0 +1,12 @@
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| 12 |
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|
checkpoints/020000/pretrained_model/policy_preprocessor.json
ADDED
|
@@ -0,0 +1,64 @@
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| 17 |
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| 20 |
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| 21 |
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| 23 |
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| 24 |
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|
| 25 |
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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|
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|
| 63 |
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|
| 64 |
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|
checkpoints/020000/pretrained_model/policy_preprocessor_step_3_normalizer_processor.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 11544
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checkpoints/020000/pretrained_model/train_config.json
ADDED
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@@ -0,0 +1,230 @@
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|
checkpoints/030000/pretrained_model/config.json
ADDED
|
@@ -0,0 +1,83 @@
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|
|
|
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|
|
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checkpoints/030000/pretrained_model/policy_postprocessor.json
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|
| 188 |
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|
| 190 |
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|
| 191 |
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|
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|
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| 199 |
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| 200 |
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| 212 |
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| 217 |
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| 218 |
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| 220 |
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| 222 |
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| 223 |
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| 224 |
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|
| 230 |
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|
checkpoints/040000/pretrained_model/config.json
ADDED
|
@@ -0,0 +1,83 @@
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|
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|
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|
| 3 |
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| 4 |
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| 7 |
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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| 30 |
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|
| 31 |
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| 32 |
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| 33 |
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| 34 |
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| 35 |
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| 36 |
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|
| 37 |
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|
| 38 |
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| 39 |
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| 40 |
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| 41 |
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| 42 |
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| 43 |
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| 44 |
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| 46 |
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| 49 |
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| 50 |
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|
| 51 |
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|
| 52 |
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| 54 |
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| 61 |
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| 63 |
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|
| 65 |
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|
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|
checkpoints/040000/pretrained_model/model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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size 206360820
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checkpoints/040000/pretrained_model/policy_postprocessor.json
ADDED
|
@@ -0,0 +1,12 @@
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|
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|
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|
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|
|
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|
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|
| 1 |
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{
|
| 2 |
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"name": "policy_postprocessor",
|
| 3 |
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|
| 4 |
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{
|
| 5 |
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|
| 6 |
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| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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|
| 11 |
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|
| 12 |
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|
checkpoints/040000/pretrained_model/policy_preprocessor.json
ADDED
|
@@ -0,0 +1,64 @@
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|
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| 5 |
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|
| 6 |
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| 9 |
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| 10 |
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| 11 |
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|
| 12 |
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| 13 |
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|
| 14 |
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{
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| 15 |
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|
| 16 |
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|
| 17 |
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| 18 |
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| 19 |
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| 20 |
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| 21 |
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{
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| 22 |
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|
| 23 |
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"config": {
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| 24 |
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"eps": 1e-08,
|
| 25 |
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| 26 |
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| 27 |
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|
| 28 |
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| 29 |
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| 30 |
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| 31 |
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| 32 |
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|
| 33 |
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|
| 34 |
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| 35 |
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|
| 36 |
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|
| 37 |
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| 38 |
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|
| 39 |
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| 40 |
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|
| 41 |
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|
| 42 |
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| 43 |
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|
| 44 |
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360,
|
| 45 |
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640
|
| 46 |
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|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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| 51 |
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| 52 |
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| 53 |
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| 54 |
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| 55 |
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| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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| 61 |
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"state_file": "policy_preprocessor_step_3_normalizer_processor.safetensors"
|
| 62 |
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}
|
| 63 |
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]
|
| 64 |
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}
|
checkpoints/040000/pretrained_model/policy_preprocessor_step_3_normalizer_processor.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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size 11544
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checkpoints/040000/pretrained_model/train_config.json
ADDED
|
@@ -0,0 +1,230 @@
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|
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|
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|
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|
|
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|
|
|
|
|
|
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|
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|
|
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|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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0.8,
|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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"weight": 1.0,
|
| 43 |
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"type": "ColorJitter",
|
| 44 |
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"kwargs": {
|
| 45 |
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"hue": [
|
| 46 |
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-0.05,
|
| 47 |
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0.05
|
| 48 |
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|
| 49 |
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|
| 50 |
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|
| 51 |
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"sharpness": {
|
| 52 |
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|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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|
| 64 |
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|
| 65 |
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"degrees": [
|
| 66 |
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-5.0,
|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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0.05,
|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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"n_obs_steps": 1,
|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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"shape": [
|
| 99 |
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|
| 100 |
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360,
|
| 101 |
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640
|
| 102 |
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|
| 103 |
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|
| 104 |
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"observation.images.front": {
|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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640
|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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"output_features": {
|
| 114 |
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"action": {
|
| 115 |
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"type": "ACTION",
|
| 116 |
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"shape": [
|
| 117 |
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112
|
| 118 |
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]
|
| 119 |
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}
|
| 120 |
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},
|
| 121 |
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"device": "cuda",
|
| 122 |
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|
| 123 |
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|
| 124 |
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|
| 125 |
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|
| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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|
| 131 |
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|
| 132 |
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"n_action_steps": 16,
|
| 133 |
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|
| 134 |
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"VISUAL": "MEAN_STD",
|
| 135 |
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"STATE": "MEAN_STD",
|
| 136 |
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"ACTION": "MEAN_STD"
|
| 137 |
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},
|
| 138 |
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"vision_backbone": "resnet18",
|
| 139 |
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"pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
|
| 140 |
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"replace_final_stride_with_dilation": 0,
|
| 141 |
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"pre_norm": false,
|
| 142 |
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"dim_model": 512,
|
| 143 |
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"n_heads": 8,
|
| 144 |
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"dim_feedforward": 3200,
|
| 145 |
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|
| 146 |
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"n_encoder_layers": 4,
|
| 147 |
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"n_decoder_layers": 1,
|
| 148 |
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|
| 149 |
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"latent_dim": 32,
|
| 150 |
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|
| 151 |
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"temporal_ensemble_coeff": null,
|
| 152 |
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|
| 153 |
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|
| 154 |
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"optimizer_lr": 2e-05,
|
| 155 |
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|
| 156 |
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|
| 157 |
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|
| 158 |
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|
| 159 |
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|
| 160 |
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|
| 161 |
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|
| 162 |
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|
| 163 |
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|
| 164 |
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|
| 165 |
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|
| 166 |
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|
| 167 |
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|
| 168 |
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},
|
| 169 |
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"reward_model": null,
|
| 170 |
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"output_dir": "outputs/pickblock_bspline_act_aug",
|
| 171 |
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"job_name": "bspline_act",
|
| 172 |
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"resume": true,
|
| 173 |
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"seed": 1000,
|
| 174 |
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"cudnn_deterministic": false,
|
| 175 |
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"num_workers": 8,
|
| 176 |
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"batch_size": 32,
|
| 177 |
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"prefetch_factor": 4,
|
| 178 |
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"persistent_workers": true,
|
| 179 |
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"steps": 40000,
|
| 180 |
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"env_eval_freq": 20000,
|
| 181 |
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"log_freq": 250,
|
| 182 |
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"eval_steps": 1000,
|
| 183 |
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"max_eval_samples": 512,
|
| 184 |
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"tolerance_s": 0.0001,
|
| 185 |
+
"save_checkpoint": true,
|
| 186 |
+
"save_freq": 5000,
|
| 187 |
+
"use_policy_training_preset": true,
|
| 188 |
+
"optimizer": {
|
| 189 |
+
"type": "adamw",
|
| 190 |
+
"lr": 2e-05,
|
| 191 |
+
"weight_decay": 0.001,
|
| 192 |
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"grad_clip_norm": 10.0,
|
| 193 |
+
"betas": [
|
| 194 |
+
0.9,
|
| 195 |
+
0.999
|
| 196 |
+
],
|
| 197 |
+
"eps": 1e-08
|
| 198 |
+
},
|
| 199 |
+
"scheduler": null,
|
| 200 |
+
"eval": {
|
| 201 |
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"n_episodes": 50,
|
| 202 |
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"batch_size": 22,
|
| 203 |
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"use_async_envs": true,
|
| 204 |
+
"recording": false,
|
| 205 |
+
"recording_repo_id": null,
|
| 206 |
+
"recording_private": false
|
| 207 |
+
},
|
| 208 |
+
"wandb": {
|
| 209 |
+
"enable": false,
|
| 210 |
+
"disable_artifact": false,
|
| 211 |
+
"project": "lerobot",
|
| 212 |
+
"entity": null,
|
| 213 |
+
"notes": null,
|
| 214 |
+
"run_id": null,
|
| 215 |
+
"mode": null,
|
| 216 |
+
"add_tags": true
|
| 217 |
+
},
|
| 218 |
+
"peft": null,
|
| 219 |
+
"job": {
|
| 220 |
+
"target": null,
|
| 221 |
+
"image": "huggingface/lerobot-gpu:latest",
|
| 222 |
+
"timeout": "2d",
|
| 223 |
+
"detach": false,
|
| 224 |
+
"tags": []
|
| 225 |
+
},
|
| 226 |
+
"save_checkpoint_to_hub": false,
|
| 227 |
+
"sample_weighting": null,
|
| 228 |
+
"rename_map": {},
|
| 229 |
+
"checkpoint_path": "outputs/pickblock_bspline_act_aug/checkpoints/last"
|
| 230 |
+
}
|
config.json
ADDED
|
@@ -0,0 +1,83 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"type": "bspline_act",
|
| 3 |
+
"n_obs_steps": 1,
|
| 4 |
+
"input_features": {
|
| 5 |
+
"observation.state": {
|
| 6 |
+
"type": "STATE",
|
| 7 |
+
"shape": [
|
| 8 |
+
6
|
| 9 |
+
]
|
| 10 |
+
},
|
| 11 |
+
"observation.images.ee": {
|
| 12 |
+
"type": "VISUAL",
|
| 13 |
+
"shape": [
|
| 14 |
+
3,
|
| 15 |
+
360,
|
| 16 |
+
640
|
| 17 |
+
]
|
| 18 |
+
},
|
| 19 |
+
"observation.images.front": {
|
| 20 |
+
"type": "VISUAL",
|
| 21 |
+
"shape": [
|
| 22 |
+
3,
|
| 23 |
+
360,
|
| 24 |
+
640
|
| 25 |
+
]
|
| 26 |
+
}
|
| 27 |
+
},
|
| 28 |
+
"output_features": {
|
| 29 |
+
"action": {
|
| 30 |
+
"type": "ACTION",
|
| 31 |
+
"shape": [
|
| 32 |
+
112
|
| 33 |
+
]
|
| 34 |
+
}
|
| 35 |
+
},
|
| 36 |
+
"device": "cuda",
|
| 37 |
+
"use_amp": false,
|
| 38 |
+
"use_peft": false,
|
| 39 |
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"push_to_hub": false,
|
| 40 |
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"repo_id": null,
|
| 41 |
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"private": null,
|
| 42 |
+
"tags": null,
|
| 43 |
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|
| 44 |
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"pretrained_path": "outputs/pickblock_bspline_act_aug/checkpoints/last/pretrained_model",
|
| 45 |
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|
| 46 |
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|
| 47 |
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"n_action_steps": 16,
|
| 48 |
+
"normalization_mapping": {
|
| 49 |
+
"VISUAL": "MEAN_STD",
|
| 50 |
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"STATE": "MEAN_STD",
|
| 51 |
+
"ACTION": "MEAN_STD"
|
| 52 |
+
},
|
| 53 |
+
"vision_backbone": "resnet18",
|
| 54 |
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"pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
|
| 55 |
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"replace_final_stride_with_dilation": 0,
|
| 56 |
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"pre_norm": false,
|
| 57 |
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"dim_model": 512,
|
| 58 |
+
"n_heads": 8,
|
| 59 |
+
"dim_feedforward": 3200,
|
| 60 |
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"feedforward_activation": "relu",
|
| 61 |
+
"n_encoder_layers": 4,
|
| 62 |
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"n_decoder_layers": 1,
|
| 63 |
+
"use_vae": true,
|
| 64 |
+
"latent_dim": 32,
|
| 65 |
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"n_vae_encoder_layers": 4,
|
| 66 |
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"temporal_ensemble_coeff": null,
|
| 67 |
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"dropout": 0.1,
|
| 68 |
+
"kl_weight": 10.0,
|
| 69 |
+
"optimizer_lr": 2e-05,
|
| 70 |
+
"optimizer_weight_decay": 0.001,
|
| 71 |
+
"optimizer_lr_backbone": 1e-05,
|
| 72 |
+
"bspline_degree": 3,
|
| 73 |
+
"bspline_chunk_size": 10,
|
| 74 |
+
"relative_knots": false,
|
| 75 |
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"speed_up": 1.0,
|
| 76 |
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"n_decoded_steps": 32,
|
| 77 |
+
"align_segments": true,
|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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"replan_margin": 1.0,
|
| 82 |
+
"channels_last": true
|
| 83 |
+
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|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4e16d5b72180ba0ecf13a77f9a81b69b3f252d9ca457941ff211c19b65859d85
|
| 3 |
+
size 206360820
|
policy_postprocessor.json
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"name": "policy_postprocessor",
|
| 3 |
+
"steps": [
|
| 4 |
+
{
|
| 5 |
+
"registry_name": "device_processor",
|
| 6 |
+
"config": {
|
| 7 |
+
"device": "cpu",
|
| 8 |
+
"float_dtype": null
|
| 9 |
+
}
|
| 10 |
+
}
|
| 11 |
+
]
|
| 12 |
+
}
|
policy_preprocessor.json
ADDED
|
@@ -0,0 +1,64 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
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|
|
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|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"name": "policy_preprocessor",
|
| 3 |
+
"steps": [
|
| 4 |
+
{
|
| 5 |
+
"registry_name": "rename_observations_processor",
|
| 6 |
+
"config": {
|
| 7 |
+
"rename_map": {}
|
| 8 |
+
}
|
| 9 |
+
},
|
| 10 |
+
{
|
| 11 |
+
"registry_name": "to_batch_processor",
|
| 12 |
+
"config": {}
|
| 13 |
+
},
|
| 14 |
+
{
|
| 15 |
+
"registry_name": "device_processor",
|
| 16 |
+
"config": {
|
| 17 |
+
"device": "cuda",
|
| 18 |
+
"float_dtype": null
|
| 19 |
+
}
|
| 20 |
+
},
|
| 21 |
+
{
|
| 22 |
+
"registry_name": "normalizer_processor",
|
| 23 |
+
"config": {
|
| 24 |
+
"eps": 1e-08,
|
| 25 |
+
"features": {
|
| 26 |
+
"observation.state": {
|
| 27 |
+
"type": "STATE",
|
| 28 |
+
"shape": [
|
| 29 |
+
6
|
| 30 |
+
]
|
| 31 |
+
},
|
| 32 |
+
"observation.images.ee": {
|
| 33 |
+
"type": "VISUAL",
|
| 34 |
+
"shape": [
|
| 35 |
+
3,
|
| 36 |
+
360,
|
| 37 |
+
640
|
| 38 |
+
]
|
| 39 |
+
},
|
| 40 |
+
"observation.images.front": {
|
| 41 |
+
"type": "VISUAL",
|
| 42 |
+
"shape": [
|
| 43 |
+
3,
|
| 44 |
+
360,
|
| 45 |
+
640
|
| 46 |
+
]
|
| 47 |
+
},
|
| 48 |
+
"action": {
|
| 49 |
+
"type": "ACTION",
|
| 50 |
+
"shape": [
|
| 51 |
+
112
|
| 52 |
+
]
|
| 53 |
+
}
|
| 54 |
+
},
|
| 55 |
+
"norm_map": {
|
| 56 |
+
"VISUAL": "MEAN_STD",
|
| 57 |
+
"STATE": "MEAN_STD",
|
| 58 |
+
"ACTION": "MEAN_STD"
|
| 59 |
+
}
|
| 60 |
+
},
|
| 61 |
+
"state_file": "policy_preprocessor_step_3_normalizer_processor.safetensors"
|
| 62 |
+
}
|
| 63 |
+
]
|
| 64 |
+
}
|
policy_preprocessor_step_3_normalizer_processor.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:7b1863e4f75643077d48e73b9a90b50bec2e8a27fb3cb5d60195ac41d06ef48e
|
| 3 |
+
size 11544
|
train_config.json
ADDED
|
@@ -0,0 +1,230 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
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|
|
|
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|
|
|
| 1 |
+
{
|
| 2 |
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"dataset": {
|
| 3 |
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|
| 4 |
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|
| 5 |
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|
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|
| 7 |
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|
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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"type": "ColorJitter",
|
| 14 |
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|
| 15 |
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"brightness": [
|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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"contrast": {
|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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"saturation": {
|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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},
|
| 41 |
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"hue": {
|
| 42 |
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"weight": 1.0,
|
| 43 |
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"type": "ColorJitter",
|
| 44 |
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"kwargs": {
|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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|
| 53 |
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|
| 54 |
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| 55 |
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| 56 |
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|
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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},
|
| 85 |
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|
| 86 |
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|
| 87 |
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"type": "bspline_act",
|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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|
| 104 |
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"observation.images.front": {
|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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|
| 117 |
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|
| 118 |
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|
| 119 |
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|
| 120 |
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|
| 121 |
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|
| 122 |
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|
| 123 |
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|
| 124 |
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|
| 125 |
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|
| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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|
| 131 |
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|
| 132 |
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|
| 133 |
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|
| 134 |
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"VISUAL": "MEAN_STD",
|
| 135 |
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"STATE": "MEAN_STD",
|
| 136 |
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"ACTION": "MEAN_STD"
|
| 137 |
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|
| 138 |
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|
| 139 |
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|
| 140 |
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|
| 141 |
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|
| 142 |
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|
| 143 |
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|
| 144 |
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|
| 145 |
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|
| 146 |
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|
| 147 |
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|
| 148 |
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|
| 149 |
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|
| 150 |
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|
| 151 |
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|
| 153 |
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|
| 154 |
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|
| 155 |
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|
| 156 |
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|
| 157 |
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|
| 158 |
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|
| 159 |
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|
| 160 |
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|
| 161 |
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|
| 162 |
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|
| 163 |
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|
| 164 |
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|
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|
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|
| 167 |
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|
| 168 |
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|
| 169 |
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|
| 170 |
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|
| 171 |
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|
| 172 |
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|
| 173 |
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|
| 174 |
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|
| 175 |
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|
| 176 |
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|
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|
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|
| 179 |
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|
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|
| 181 |
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|
| 182 |
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|
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|
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