Upload full BRIDGE R3M cached features
Browse files- features/full_bridge/r3m_resnet34_features_bs256/README.md +56 -0
- features/full_bridge/r3m_resnet34_features_bs256/SHA256SUMS +4 -0
- features/full_bridge/r3m_resnet34_features_bs256/features_config.json +16 -0
- features/full_bridge/r3m_resnet34_features_bs256/manifest.json +28 -0
- features/full_bridge/r3m_resnet34_features_bs256/test.tar.zst +3 -0
- features/full_bridge/r3m_resnet34_features_bs256/train.tar.zst +3 -0
- features/full_bridge/r3m_resnet34_features_bs256/val.tar.zst +3 -0
features/full_bridge/r3m_resnet34_features_bs256/README.md
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# Full BRIDGE R3M ResNet34 Cached Features
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These archives contain the cached R3M ResNet34 features used by the full BRIDGE
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semantic latent action experiments.
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## Contents
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- `train.tar.zst`
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- `val.tar.zst`
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- `test.tar.zst`
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- `features_config.json`
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- `SHA256SUMS`
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- `manifest.json`
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Each split archive preserves the original cache structure, e.g. extracting
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`train.tar.zst` recreates a `train/` directory containing per-trajectory
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`features.npy` files.
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## Feature Config
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```json
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{
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"created_utc": "2026-05-14T15:27:27+00:00",
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"dataset_root": "/home/bagel/bridge_processed_full/extracted/bridge_processed_full",
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"feature_dim": 512,
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"image_size": [
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224,
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224
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],
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"r3m_model_id": "resnet34",
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"schema_version": 1,
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"splits": [
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"train",
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"val",
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"test"
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]
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}
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```
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## Restore
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From a directory where you want the cache restored:
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```bash
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tar --use-compress-program zstd -xf train.tar.zst
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tar --use-compress-program zstd -xf val.tar.zst
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tar --use-compress-program zstd -xf test.tar.zst
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```
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The original training cache path was:
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```text
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/home/bagel/bridge_processed_full/r3m_resnet34_features_bs256
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```
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The BRIDGE image dataset itself is not included here.
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features/full_bridge/r3m_resnet34_features_bs256/SHA256SUMS
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f6884dd1442e05c3ec755072e1a425c896d81ad29f74844580a5591339a2a03f train.tar.zst
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e76c53392c419c494bf248e31f7c4def22b364015b1fbd3bfef9d20c3a889e53 val.tar.zst
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c5bb6d1346cd6714b51f278f0eb35a15f2ee613e9c462659cb97377f28587925 test.tar.zst
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7e0ec098203df9b7002ec32a72280a979ff23ff66fbec64c2b7d19e3da259815 features_config.json
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features/full_bridge/r3m_resnet34_features_bs256/features_config.json
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{
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"created_utc": "2026-05-14T15:27:27+00:00",
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"dataset_root": "/home/bagel/bridge_processed_full/extracted/bridge_processed_full",
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"feature_dim": 512,
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"image_size": [
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224,
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224
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],
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"r3m_model_id": "resnet34",
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"schema_version": 1,
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"splits": [
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"train",
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"val",
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"test"
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]
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}
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features/full_bridge/r3m_resnet34_features_bs256/manifest.json
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{
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"archive_dir": "/home/bagel/bridge_processed_full/hf_feature_archives/r3m_resnet34_features_bs256",
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"entries": [
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{
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"file": "train.tar.zst",
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"sha256": "f6884dd1442e05c3ec755072e1a425c896d81ad29f74844580a5591339a2a03f",
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"size_bytes": 2272282264
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},
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{
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"file": "val.tar.zst",
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"sha256": "e76c53392c419c494bf248e31f7c4def22b364015b1fbd3bfef9d20c3a889e53",
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"size_bytes": 286159983
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},
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{
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"file": "test.tar.zst",
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"sha256": "c5bb6d1346cd6714b51f278f0eb35a15f2ee613e9c462659cb97377f28587925",
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"size_bytes": 283063996
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},
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{
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"file": "features_config.json",
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"sha256": "7e0ec098203df9b7002ec32a72280a979ff23ff66fbec64c2b7d19e3da259815",
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"size_bytes": 305
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}
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],
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"format": "one tar.zst archive per split",
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"hf_prefix": "features/full_bridge/r3m_resnet34_features_bs256",
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"source_cache_dir": "/home/bagel/bridge_processed_full/r3m_resnet34_features_bs256"
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}
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features/full_bridge/r3m_resnet34_features_bs256/test.tar.zst
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version https://git-lfs.github.com/spec/v1
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oid sha256:c5bb6d1346cd6714b51f278f0eb35a15f2ee613e9c462659cb97377f28587925
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size 283063996
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features/full_bridge/r3m_resnet34_features_bs256/train.tar.zst
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version https://git-lfs.github.com/spec/v1
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oid sha256:f6884dd1442e05c3ec755072e1a425c896d81ad29f74844580a5591339a2a03f
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size 2272282264
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features/full_bridge/r3m_resnet34_features_bs256/val.tar.zst
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version https://git-lfs.github.com/spec/v1
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oid sha256:e76c53392c419c494bf248e31f7c4def22b364015b1fbd3bfef9d20c3a889e53
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size 286159983
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