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Mark A6000 sim-collection guide as ARCHIVED (glibc 2.31 vs 2.35 incompat); point readers to current data + training plan
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---
license: cc-by-4.0
language:
- en
pretty_name: baseline_3 v4 - Sim Collection Assets (ARCHIVED)
tags:
- robotics
- manipulation
- grasping
- diffusion-policy
- franka
- dexycb
- collection-assets
- archived
size_categories:
- 1B<n<10B
---
# baseline_3 v4 — sim collection assets
> **2026-05-26 — STATUS: ARCHIVED / REFERENCE-ONLY.**
>
> The plan to run sim collection on the A6000 was **abandoned** this round
> due to a glibc incompatibility: the A6000 system glibc is 2.31 (Ubuntu
> 20.04) but IsaacSim 5.1.0 requires glibc 2.35 (Ubuntu 24.04). All sim
> collection (DexYCB + OakInk) was completed on the dev box (RTX 5090).
>
> The contents of this dataset (tarballs of source episodes, USDs, scripts,
> partial results log) are kept for reference and reproducibility — the
> code links remain accurate — but the "run the resume on A6000"
> instructions below are **no longer the current plan**.
>
> **For the current state of the data and training pipeline, see:**
> - DexYCB-sourced training trajectories (162 ep) →
> [`UCBProject/DP3_DexYCB_training_data`](https://huggingface.co/datasets/UCBProject/DP3_DexYCB_training_data)
> - OakInk-sourced training trajectories (207 ep) →
> [`UCBProject/DP3_OakInk_training_data`](https://huggingface.co/datasets/UCBProject/DP3_OakInk_training_data)
>
> The DexYCB README also documents the new **combined 369-ep training run**
> on A6000.
---
## What's in this archived package
| file | size | purpose |
|------|------|---------|
| `episodes_g.tar.gz` | 1.2 GB | 900 retargeted DexYCB hdf5 (collector INPUT for the sim collection that ran on the dev box). Includes ycb_dex_01–20 minus the no-data ones; specifically the **newly retargeted dex_11 (pitcher) + dex_14 (mug)** missing from previous runs. |
| `obj_usd_cad_ycb.tar.gz` | 489 MB | YCB CAD USDs (17 files, Z-up tagged) + textures. Includes the **new dex_11/14/19 USDs** generated this round. |
| `episodes_b3_v4_15obj_3yaw_2026-05-25.tar.gz` | 266 MB | Already-collected sim hdf5 for 6 objects (tuna 06, tomato 04, pudding 07, gelatin 08, marker 18, potted_meat 09) at the time the partial results log was snapshotted. |
| `v4_full15_results_2026-05-25.txt` | 1.5 KB | Partial results log with 6 DONE_RETRY entries (point-in-time snapshot before the run continued on the dev box). |
| `v4_full15_queue_resume.sh` | 4.6 KB | Resume-aware orchestrator (2-parallel). Repo canonical version under `scripts/baseline_3_v4/`. |
| `v4_chunked_with_retry.sh` | 4.6 KB | Per-object chunk-5+retry wrapper. Repo canonical version under `scripts/baseline_3_v4/`. |
**Source code (canonical)**:
[`stzabl-png/UCB_Project @ gate3-curobo-ik`](https://github.com/stzabl-png/UCB_Project/tree/gate3-curobo-ik)
— `sim/run_grasp_sim_baseline3_v4.py` and `scripts/baseline_3_v4/*.sh`.
The OakInk-specific orchestrator (added 2026-05-26) lives at
`scripts/baseline_3_v4/oakink_full89_queue_resume.sh` in the same repo.
---
## How sim collection actually ran (2026-05-25 + 2026-05-26)
All on the dev box (RTX 5090, Ubuntu 24.04, glibc 2.35):
| Run | Date | Result |
|------|------|--------|
| DexYCB resume — 15 obj, 2-parallel chunked-5 | 2026-05-25 | **162 successful trajectories** across 10 objects → `UCBProject/DP3_DexYCB_training_data` |
| OakInk full — 89 obj, 2-parallel chunked-5 | 2026-05-26 | **207 successful trajectories** across 45 objects (44 obj contributed 0 due to obj geometry / Franka kinematic limits) → `UCBProject/DP3_OakInk_training_data` |
---
## Why the A6000 was dropped from the collection pipeline
Diagnosed 2026-05-25:
```
$ python -c "from isaacsim import SimulationApp"
ImportError: /lib/x86_64-linux-gnu/libc.so.6: version 'GLIBC_2.35' not found
(required by .../isaacsim-5.1.0/_build/lib/libomni.kit.app.so)
```
A6000 system glibc 2.31 is fixed by the Ubuntu 20.04 base; bumping the
system libc to 2.35 in-place is not safe. Containerizing IsaacSim would
work but adds a deployment burden we decided wasn't worth it for sim
collection that runs on the dev box anyway. The A6000 stays on training.
---
## Original "resume on A6000" instructions (DEPRECATED — kept for reference)
<details>
<summary>Click to expand the original A6000 sim-collection guide.
This was written before the glibc issue was diagnosed; it is no longer the
plan. Follow the new training instructions in the DexYCB dataset README instead.</summary>
The instructions below describe how the A6000 sim collection *would* have
worked if glibc had been compatible. They are kept verbatim for
reproducibility; do not follow them on the current A6000.
### env_isaaclab install (requires glibc ≥ 2.35)
```bash
conda create -n env_isaaclab python=3.11 -y
conda activate env_isaaclab
pip install --upgrade --extra-index-url=https://pypi.nvidia.com isaacsim==5.1.0
pip install --extra-index-url=https://pypi.nvidia.com nvidia-curobo
pip install h5py scipy 'numpy<2' termcolor pyyaml requests usd-core
```
### Download + extract from this archive
```bash
cd UCB_Project
pip install huggingface_hub
mkdir -p Baseline1/data output
huggingface-cli download UCBProject/baseline_3_v4_collection_assets \
--repo-type dataset --local-dir /tmp/v4_pkg
tar xzf /tmp/v4_pkg/episodes_g.tar.gz
tar xzf /tmp/v4_pkg/obj_usd_cad_ycb.tar.gz
tar xzf /tmp/v4_pkg/episodes_b3_v4_15obj_3yaw_2026-05-25.tar.gz
cp /tmp/v4_pkg/v4_full15_results_2026-05-25.txt /tmp/
```
### Run the resume
```bash
cd UCB_Project
PROJ=$HOME/UCB_Project \
PY=$HOME/miniconda3/envs/env_isaaclab/bin/python \
OUT=Baseline1/data/episodes_b3_v4_15obj_3yaw_2026-05-25 \
RESULTS=/tmp/v4_full15_results_2026-05-25.txt \
PAR=2 \
bash scripts/baseline_3_v4/v4_full15_queue_resume.sh
```
For PAR tuning, gotcha list, troubleshooting, and per-object expected yield,
see the original 10-gotcha table that previously appeared here — the
canonical version is now in the repo's `Baseline1/RETRAIN_V4_FULL12.md` and
the inline comments in `scripts/baseline_3_v4/v4_*.sh`.
</details>
---
## License & citation
Sim collection assets: CC-BY-4.0.
DexYCB source data subject to the original DexYCB license.
YCB object meshes: Yale-CMU-Berkeley YCB Object & Model Set license.