Add HF 0420 balanced validation package README
Browse files
validation/hanoi_0420_balanced/README.md
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| 1 |
+
# GNN Hanoi 0420 Balanced Validation Package
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+
This folder contains a self-contained validation-data package for paired evaluation of a pure fine-tuned video world model versus a graph-conditioned world model on Tower-of-Hanoi disassembly episodes.
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+
This artifact is for validation only. It does not contain model checkpoints, generated predictions, inference outputs, benchmark tables, or final metric claims.
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## Files in this Hugging Face folder
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Expected files:
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```text
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validation/hanoi_0420_balanced/
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README.md
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GNN_Hanoi_0420_balanced_validation_package.zip
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GNN_Hanoi_0420_balanced_validation_package.zip.sha256
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GNN_Hanoi_0420_balanced_validation_package.zip.test.txt
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GNN_Hanoi_0420_balanced_validation_package.zip.contents.txt
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```
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The ZIP contains:
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```text
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GNN_Hanoi_0420_balanced_validation_package/
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README.md
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MANIFEST.json
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episodes.csv
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metadata/
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session_metadata.json
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session_plan.json
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perception_log.jsonl
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setup_snapshot.yaml
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data/
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episode_00.zip
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episode_07.zip
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episode_10.zip
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episode_12.zip
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episode_14.zip
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episode_15.zip
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config/
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val_0420_episode_manifest.jsonl
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test_split_0420_balanced.txt
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```
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## Source
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The package is built from this same Hugging Face dataset repository:
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```text
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ChangChrisLiu/GNN_Disassembly_WorldModel
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```
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Source session:
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```text
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hanoi/session_hanoi_0420_132840
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```
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Selected validation episodes:
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```text
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episode_00 classical 6 moves
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episode_10 classical 12 moves
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episode_14 single_ring 3 moves
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episode_07 single_ring 7 moves
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episode_12 rearrange 4 moves
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episode_15 rearrange 6 moves
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```
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This gives a compact balanced validation subset:
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- 2 classical tasks
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- 2 single-ring tasks
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- 2 rearrange tasks
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## Why this package exists
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This package is intended to freeze a clear validation subset for later model comparison. It avoids using local 0423 data because that local run has known action/proprio recording issues. HF 0420 is preferred because the selected episode ZIPs include synchronized robot states, side RGB/depth frames, and graph annotations.
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Before reporting benchmark numbers, verify that `session_hanoi_0420_132840` was held out from training and model selection for every compared checkpoint. If either checkpoint trained on these episodes, do not call the resulting metrics validation performance.
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## Data inside each episode ZIP
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Each included episode ZIP was locally validated for ZIP integrity and required schema. Each selected episode contains:
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```text
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metadata.json
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robot_states.npy
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timestamps.npy
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side/rgb/frame_*.png
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side/depth/frame_*.npy
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annotations/side_graph.json
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annotations/side_masks/frame_*.npz
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annotations/side_embeddings/frame_*.npz
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annotations/side_depth_info/frame_*.npz
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annotations/side_robot/frame_*.npz
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```
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Important action-field note:
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These selected episode ZIPs do not bundle a separate `robot_actions.npy`. For any action-conditioned inference or diagnostics, derive per-frame action deltas from robot states:
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```python
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robot_action_t = robot_states[t + 1] - robot_states[t]
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```
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Use the same source/eval frame interval consistently when deriving action deltas for model inputs.
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## Graph information
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Yes, graph information is included. Each selected episode ZIP contains:
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```text
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annotations/side_graph.json
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```
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This is the ground-truth graph source for the Hanoi objects/rings and should be used for graph-conditioned validation inputs and graph-based scoring. Do not use HSV proxy labels as the final graph ground truth.
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Graph modes must be labeled explicitly in later experiments:
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- `gt_anchor_graph`: only current/anchor GT graph is used
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- `oracle_future_graph`: future GT graph is used; upper-bound only
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- `predicted_graph`: deployment-style recursive graph prediction
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## Later inference protocol
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This ZIP is data-only. Later inference should use a paired protocol:
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1. Build a window-level inference manifest from the selected episodes.
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2. For each window, run both models with identical:
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- episode/window
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- anchor/context frames
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- goal prompt
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- seed
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- output FPS
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- resolution
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- sampler/chunking settings
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- generation length
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3. Generate one recursive 10-second rollout per window.
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4. Evaluate cumulative prefixes from that same rollout:
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- 1s
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- 3s
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- 6s
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- 10s
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Do not generate separate independent 1s/3s/6s/10s clips unless explicitly labeling that as a separate non-recursive protocol.
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Recommended timing contract:
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```text
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source FPS: 30
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eval/model FPS: 5
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frame interval: 6 source frames per eval frame
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10s rollout: 50 eval frames
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1s prefix: 5 eval frames
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3s prefix: 15 eval frames
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6s prefix: 30 eval frames
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10s prefix: 50 eval frames
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```
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## Later metric protocol
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Valid immediately after predictions exist:
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- ROI PSNR
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- ROI SSIM
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- ROI LPIPS
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- ROI motion error
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- ROI color metric
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- ROI PSNR min/std/drift slope
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- whole-frame backup metrics
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Recommended ROI:
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```text
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x = 25-75%
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y = 20-80%
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```
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Graph metrics require generated-frame labeler validation before final claims:
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- ring position accuracy
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- exact state match
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- held-state F1
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- edge/is_locked F1
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- state edit distance
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- illegal-stack rate
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- task success
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## Local verification result before upload
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The package ZIP was created and verified locally.
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Package SHA256:
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```text
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6a9a42ed346df7a1139344e351ce24daa2b82957dd1feeb0ff41c8ff2e168c3d GNN_Hanoi_0420_balanced_validation_package.zip
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```
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ZIP test result:
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```text
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test of GNN_Hanoi_0420_balanced_validation_package.zip OK
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```
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Per-source-file checksums are included in the package manifest and in the original local download checksum log.
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## How to use
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Download and verify:
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```bash
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sha256sum -c GNN_Hanoi_0420_balanced_validation_package.zip.sha256
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unzip -t GNN_Hanoi_0420_balanced_validation_package.zip
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unzip GNN_Hanoi_0420_balanced_validation_package.zip
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```
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Then inspect:
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```bash
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cd GNN_Hanoi_0420_balanced_validation_package
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cat README.md
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cat episodes.csv
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cat config/test_split_0420_balanced.txt
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```
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The package is ready for validation dataset preparation and later paired inference/evaluation. It is not itself a final benchmark-result artifact.
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