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+         236  code/reveal_vla_bimanual/reveal_vla_bimanual.egg-info/requires.txt
+          51  code/reveal_vla_bimanual/reveal_vla_bimanual.egg-info/top_level.txt
+         967  code/reveal_vla_bimanual/scripts/download_coppeliasim.sh
+         800  code/reveal_vla_bimanual/scripts/install_micromamba.sh
+        3400  code/reveal_vla_bimanual/scripts/setup_env_a_rlbench.sh
+        1909  code/reveal_vla_bimanual/scripts/setup_env_b_reveal.sh
+        2086  code/reveal_vla_bimanual/scripts/setup_rlbench_headless_x.sh
+        3116  code/reveal_vla_bimanual/scripts/start_rlbench_x.sh
+         456  code/reveal_vla_bimanual/sim_reveal/__init__.py
+         689  code/reveal_vla_bimanual/sim_reveal/base.py
+       11788  code/reveal_vla_bimanual/sim_reveal/dataset.py
+        1633  code/reveal_vla_bimanual/sim_reveal/generate_dataset.py
+         665  code/reveal_vla_bimanual/sim_reveal/isaac_smoke.py
+         358  code/reveal_vla_bimanual/sim_reveal/isaac_wrapper.py
+        2198  code/reveal_vla_bimanual/sim_reveal/labels.py
+       31458  code/reveal_vla_bimanual/sim_reveal/procedural_envs.py
+         960  code/reveal_vla_bimanual/sim_reveal/proxy_specs.py
+        1899  code/reveal_vla_bimanual/sim_reveal/teachers.py
+         335  code/reveal_vla_bimanual/sim_rlbench/__init__.py
+         885  code/reveal_vla_bimanual/sim_rlbench/camera_spec.py
+       13817  code/reveal_vla_bimanual/sim_rlbench/dataset.py
+        4368  code/reveal_vla_bimanual/sim_rlbench/dataset_download.py
+        4698  code/reveal_vla_bimanual/sim_rlbench/generate_smoke_dataset.py
+        3232  code/reveal_vla_bimanual/sim_rlbench/launch_smoke.py
+        3025  code/reveal_vla_bimanual/sim_rlbench/obs_adapter.py
+        4525  code/reveal_vla_bimanual/sim_rlbench/peract2_runner.py
+        1410  code/reveal_vla_bimanual/sim_rlbench/smoke_test.py
+         523  code/reveal_vla_bimanual/sim_rlbench/task_splits.py
+          78  code/reveal_vla_bimanual/train/__init__.py
+         299  code/reveal_vla_bimanual/train/configs/base.yaml
+         213  code/reveal_vla_bimanual/train/configs/data/reveal_proxies.yaml
+         193  code/reveal_vla_bimanual/train/configs/data/rlbench_3cam.yaml
+         517  code/reveal_vla_bimanual/train/configs/model/backbone_only.yaml
+        1014  code/reveal_vla_bimanual/train/configs/model/reveal_state.yaml
+        1957  code/reveal_vla_bimanual/train/configs/proxy_backbone_only.yaml
+        2069  code/reveal_vla_bimanual/train/configs/proxy_backbone_only_clip.yaml
+        2059  code/reveal_vla_bimanual/train/configs/proxy_backbone_only_smoke.yaml
+        1990  code/reveal_vla_bimanual/train/configs/proxy_reveal_state.yaml
+        2100  code/reveal_vla_bimanual/train/configs/proxy_reveal_state_clip.yaml
+        2058  code/reveal_vla_bimanual/train/configs/proxy_reveal_state_smoke.yaml
+        1921  code/reveal_vla_bimanual/train/configs/rlbench_subset3_backbone_only_clip.yaml
+        1914  code/reveal_vla_bimanual/train/configs/rlbench_subset3_backbone_only_dummy.yaml
+        2019  code/reveal_vla_bimanual/train/configs/rlbench_subset3_reveal_state_clip.yaml
+        2012  code/reveal_vla_bimanual/train/configs/rlbench_subset3_reveal_state_dummy.yaml
+        8452  code/reveal_vla_bimanual/train/losses.py
+        8870  code/reveal_vla_bimanual/train/run_experiment.py
+        7809  code/reveal_vla_bimanual/train/run_rlbench_experiment.py
+        2945  code/reveal_vla_bimanual/train/trainer.py
+       13139  code/upstream_local_patches/YARR/yarr/runners/_independent_env_runner.py
+       40316  code/upstream_local_patches/peract_bimanual/agents/bimanual_peract/qattention_peract_bc_agent.py
+        1501  environment/README.md
+         855  environment/glxinfo_B.txt
+        5417  environment/hardware_snapshot.txt
+       24531  environment/reveal_env_explicit.txt
+       13289  environment/reveal_env_export.yaml
+        7333  environment/reveal_pip_freeze.txt
+       25057  environment/rlbench_env_explicit.txt
+       11542  environment/rlbench_env_export.yaml
+        6265  environment/rlbench_pip_freeze.txt
+        2775  environment/setup_same_machine.sh
+         533  environment/upstream_revisions.txt
+       27789  export_manifest_data.json

MODEL_INDEX.md

@@ -1,68 +1,83 @@
 # Model Index
 
-This file points to the uploaded checkpoint files used for baseline comparison and for the proposed architecture runs.
+This file lists the uploaded checkpoints, datasets, and raw report files referenced by the current README.
 
-## Baseline comparison models
+## Proxy Checkpoints
 
-### Upstream PerAct2 bounded sanity, 3-task subset
+### Dummy Backbone Runs
 
-- method: `BIMANUAL_PERACT`
-- tasks:
-  - `bimanual_lift_ball`
-  - `bimanual_push_box`
-  - `bimanual_dual_push_buttons`
-- training scope:
-  - `1` demo per task
-  - `1` training iteration
-- checkpoint:
-  - `artifacts/logs/rlbench2_subset3/multi_3cam_subset3/BIMANUAL_PERACT/seed0/weights/0/QAttentionAgent_layer0.pt`
-- config:
-  - `artifacts/logs/rlbench2_subset3/multi_3cam_subset3/BIMANUAL_PERACT/seed0/config.yaml`
-- eval return CSV:
-  - `artifacts/logs/rlbench2_subset3/multi_3cam_subset3/BIMANUAL_PERACT/seed0/eval_data.csv`
-
-### Upstream PerAct2 bounded sanity, 2-task subset
-
-- checkpoint:
-  - `artifacts/logs/rlbench2_subset/multi_3cam_subset/BIMANUAL_PERACT/seed0/weights/0/QAttentionAgent_layer0.pt`
-- config:
-  - `artifacts/logs/rlbench2_subset/multi_3cam_subset/BIMANUAL_PERACT/seed0/config.yaml`
-
-## Proposed architecture models
-
-### Dummy-backbone reveal-proxy checkpoints
-
-- proxy backbone-only:
+- backbone-only checkpoint
   - `artifacts/outputs/reveal_runs/proxy_backbone_only/checkpoint_best.pt`
-- proxy reveal-state:
+- backbone-only metrics
+  - `artifacts/outputs/reveal_runs/proxy_backbone_only/metrics.json`
+- reveal-state checkpoint
   - `artifacts/outputs/reveal_runs/proxy_reveal_state/checkpoint_best.pt`
+- reveal-state metrics
+  - `artifacts/outputs/reveal_runs/proxy_reveal_state/metrics.json`
 
-### Frozen-CLIP reveal-proxy checkpoints
+### Frozen CLIP Backbone Runs
 
-- proxy backbone-only CLIP:
+- backbone-only checkpoint
   - `artifacts/outputs/reveal_runs/proxy_backbone_only_clip/checkpoint_best.pt`
-- proxy reveal-state CLIP:
+- backbone-only metrics
+  - `artifacts/outputs/reveal_runs/proxy_backbone_only_clip/metrics.json`
+- reveal-state checkpoint
   - `artifacts/outputs/reveal_runs/proxy_reveal_state_clip/checkpoint_best.pt`
-
-### RLBench custom checkpoints, dummy backbone
-
-- backbone-only dummy:
-  - `artifacts/outputs/rlbench_custom/rlbench_subset3_backbone_only_dummy/checkpoint_best.pt`
-- reveal-state dummy:
-  - `artifacts/outputs/rlbench_custom/rlbench_subset3_reveal_state_dummy/checkpoint_best.pt`
-
-### RLBench custom checkpoints, frozen CLIP backbone
-
-- backbone-only CLIP:
-  - `artifacts/outputs/rlbench_custom/rlbench_subset3_backbone_only_clip/checkpoint_best.pt`
-- reveal-state CLIP:
-  - `artifacts/outputs/rlbench_custom/rlbench_subset3_reveal_state_clip/checkpoint_best.pt`
-
-## Related reports
-
-- baseline sanity report:
-  - `artifacts/reports/rlbench_subset3_baseline_sanity.md`
-- dummy-backbone custom RLBench report:
-  - `artifacts/reports/rlbench_custom/rlbench_subset3_custom_eval.md`
-- frozen-CLIP custom RLBench report:
-  - `artifacts/reports/rlbench_custom_clip/rlbench_subset3_clip_eval.md`
+- reveal-state metrics
+  - `artifacts/outputs/reveal_runs/proxy_reveal_state_clip/metrics.json`
+
+## Proxy Datasets
+
+- dummy train dataset
+  - `artifacts/data/reveal_proxy/proxy_train_v4_noleak_counterfactual.pt`
+- dummy val dataset
+  - `artifacts/data/reveal_proxy/proxy_val_v4_noleak_counterfactual.pt`
+- CLIP train dataset
+  - `artifacts/data/reveal_proxy/proxy_train_clip224_v4_noleak_counterfactual.pt`
+- CLIP val dataset
+  - `artifacts/data/reveal_proxy/proxy_val_clip224_v4_noleak_counterfactual.pt`
+- smoke train dataset
+  - `artifacts/data/reveal_proxy/proxy_train_smoke_v4.pt`
+- smoke val dataset
+  - `artifacts/data/reveal_proxy/proxy_val_smoke_v4.pt`
+
+## Raw Benchmark Reports
+
+- dummy deterministic benchmark JSON
+  - `artifacts/outputs/reveal_runs/reveal_eval_v4_det/reveal_benchmark.json`
+- dummy deterministic benchmark Markdown
+  - `artifacts/outputs/reveal_runs/reveal_eval_v4_det/reveal_benchmark.md`
+- CLIP deterministic benchmark JSON
+  - `artifacts/outputs/reveal_runs/reveal_eval_v4_clip_det/reveal_benchmark.json`
+- CLIP deterministic benchmark Markdown
+  - `artifacts/outputs/reveal_runs/reveal_eval_v4_clip_det/reveal_benchmark.md`
+- CLIP 18-episode ablation JSON
+  - `artifacts/outputs/reveal_runs/reveal_ablation_v4_clip_ep18/ablations.json`
+- CLIP 18-episode ablation Markdown
+  - `artifacts/outputs/reveal_runs/reveal_ablation_v4_clip_ep18/ablations.md`
+- CLIP 18-episode ablation partial checkpoint
+  - `artifacts/outputs/reveal_runs/reveal_ablation_v4_clip_ep18/ablations.partial.json`
+
+## Smoke Artifacts
+
+- proxy backbone-only smoke checkpoint
+  - `artifacts/outputs/smoke/proxy_backbone_only_smoke/checkpoint_best.pt`
+- proxy reveal-state smoke checkpoint
+  - `artifacts/outputs/smoke/proxy_reveal_state_smoke/checkpoint_best.pt`
+- proxy smoke benchmark JSON
+  - `artifacts/outputs/smoke/reveal_eval_ep2/reveal_benchmark.json`
+- proxy smoke ablation JSON
+  - `artifacts/outputs/smoke/reveal_ablation_ep2/ablations.json`
+- RLBench launch smoke output
+  - `artifacts/logs/system/rlbench_launch_smoke.txt`
+
+## Environment Files
+
+- machine snapshot
+  - `environment/hardware_snapshot.txt`
+- OpenGL snapshot
+  - `environment/glxinfo_B.txt`
+- third-party pins
+  - `environment/upstream_revisions.txt`
+- same-machine setup helper
+  - `environment/setup_same_machine.sh`

README.md

@@ -1,232 +1,121 @@
-# VLAarchtests Export
+# VLAarchtests
 
-Export date: 2026-03-23 UTC
+Bundle uploaded from the `/workspace` runpod session dated `2026-03-23`.
 
-This package contains the code and generated artifacts from the `/workspace` run that built and tested a simulation-first bimanual reveal-and-retrieve prototype.
-
-## Package layout
+## Contents
 
 - `code/reveal_vla_bimanual/`
-  - monorepo code used for the reveal-proxy work and the custom RLBench trainer/eval path
-- `code/upstream_local_patches/`
-  - copies of the two upstream files modified locally during the baseline benchmark work:
-  - `peract_bimanual/agents/bimanual_peract/qattention_peract_bc_agent.py`
-  - `YARR/yarr/runners/_independent_env_runner.py`
+  - project code used for the current proxy and RLBench runs
 - `artifacts/outputs/`
-  - generated checkpoints, resolved configs, and metrics JSON files
-- `artifacts/reports/`
-  - benchmark reports, rollout reports, and ablation reports
-- `artifacts/logs/`
-  - setup logs, extraction logs, baseline train/eval logs, and saved upstream sanity checkpoints
-- `FILE_MANIFEST.txt`
-  - file list with byte sizes for the uploaded package
-- `export_manifest_data.json`
-  - structured summary of the main metrics and report JSON files
-- `MODEL_INDEX.md`
-  - index of uploaded baseline and proposed-model checkpoints
+  - training outputs, checkpoints, benchmark JSON/Markdown reports, and smoke outputs
+- `artifacts/data/reveal_proxy/`
+  - generated proxy datasets used by the no-leak runs
+- `artifacts/logs/system/`
+  - Xorg config/log files from the RLBench headless setup on this node
 - `environment/`
-  - machine snapshot, env exports, and same-machine setup wrapper
-
-## Not included
+  - machine snapshot, env exports, upstream revision pins, and setup helpers
+- `MODEL_INDEX.md`
+  - checkpoint and dataset path index
 
-- `/workspace/data/`
-  - downloaded RLBench demos and reveal datasets are not included in this export package
-- `/workspace/assets/`
-  - simulator binaries are not included
-- `/workspace/third_party/`
-  - full upstream trees are not included; only the two modified files are copied under `code/upstream_local_patches/`
+## Hardware Snapshot
 
-## Machine and environment facts
+| Item | Value |
+| --- | --- |
+| GPU | NVIDIA RTX 6000 Ada Generation |
+| CPU | 2x AMD EPYC 75F3 32-Core Processor |
+| Visible CPUs | 128 |
+| RLBench env Python | 3.10.20 |
 
-- target machine: single RTX 6000 Ada
-- target memory assumption in the project brief: 48 GB VRAM
-- OS target in the setup scripts: Ubuntu 22.04
-- Env A: RLBench / PerAct2 stack under `/workspace/envs/rlbench`
-- Env B: reveal-proxy / Isaac stack under `/workspace/envs/reveal`
+Raw machine outputs are in:
 
-Environment recreation files:
-- `environment/README.md`
 - `environment/hardware_snapshot.txt`
+- `environment/glxinfo_B.txt`
+
+## Raw Training Endpoints
+
+| Run | Checkpoint | Final train total | Final val total | Metrics |
+| --- | --- | ---: | ---: | --- |
+| dummy backbone-only | `artifacts/outputs/reveal_runs/proxy_backbone_only/checkpoint_best.pt` | 0.0213407213644435 | 0.019940752536058426 | `artifacts/outputs/reveal_runs/proxy_backbone_only/metrics.json` |
+| dummy reveal-state | `artifacts/outputs/reveal_runs/proxy_reveal_state/checkpoint_best.pt` | 1.0815023109316826 | 1.0336408764123917 | `artifacts/outputs/reveal_runs/proxy_reveal_state/metrics.json` |
+| CLIP backbone-only | `artifacts/outputs/reveal_runs/proxy_backbone_only_clip/checkpoint_best.pt` | 0.017409040848602644 | 0.010200991117883296 | `artifacts/outputs/reveal_runs/proxy_backbone_only_clip/metrics.json` |
+| CLIP reveal-state | `artifacts/outputs/reveal_runs/proxy_reveal_state_clip/checkpoint_best.pt` | 0.7299397423941427 | 0.5189985349064782 | `artifacts/outputs/reveal_runs/proxy_reveal_state_clip/metrics.json` |
+
+## Raw Deterministic Proxy Benchmark Results
+
+### Dummy Backbone Runs
+
+Source: `artifacts/outputs/reveal_runs/reveal_eval_v4_det/reveal_benchmark.json`
+
+| Model | Mean success | foliage_proxy | bag_proxy | cloth_proxy | visibility_integral | corridor_availability | reocclusion_rate | persistence_horizon_mae | disturbance_cost |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
+| backbone | 0.0 | 0.0 | 0.0 | 0.0 | 62.80461756388346 | 0.9864540547132492 | 0.0 | 0.0 | 0.8890127365787824 |
+| reveal | 0.0 | 0.0 | 0.0 | 0.0 | 62.73463360468546 | 0.9864540547132492 | 0.0 | 2.419941000816309 | 0.8931084167626169 |
+
+### CLIP Backbone Runs
+
+Source: `artifacts/outputs/reveal_runs/reveal_eval_v4_clip_det/reveal_benchmark.json`
+
+| Model | Mean success | foliage_proxy | bag_proxy | cloth_proxy | visibility_integral | corridor_availability | reocclusion_rate | persistence_horizon_mae | disturbance_cost |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
+| backbone | 0.5138888888888888 | 0.4583333333333333 | 0.5416666666666666 | 0.5416666666666666 | 32.18176985614829 | 0.8593082576990128 | 0.0 | 0.0 | 0.49907831982192064 |
+| reveal | 0.40277777777777773 | 0.375 | 0.4583333333333333 | 0.375 | 38.406019500560234 | 0.8850651697980033 | 0.0026041666666666665 | 0.9629970236420518 | 0.5956562398415473 |
+
+## Raw CLIP Ablation Results
+
+Source: `artifacts/outputs/reveal_runs/reveal_ablation_v4_clip_ep18/ablations.json`
+
+| Ablation | Mean success | foliage_proxy | bag_proxy | cloth_proxy | visibility_integral | corridor_availability | reocclusion_rate | persistence_horizon_mae | disturbance_cost |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
+| full_model | 0.35185185185185186 | 0.3333333333333333 | 0.3888888888888889 | 0.3333333333333333 | 41.31481176614761 | 0.8930041271227377 | 0.002777777777777778 | 0.9662547600565393 | 0.6302865350411998 |
+| no_reveal_state_head | 0.3333333333333333 | 0.3333333333333333 | 0.3888888888888889 | 0.2777777777777778 | 6.436306021831654 | 0.33413351644520406 | 0.008333333333333335 | 0.0 | 0.5424560326393004 |
+| no_world_model | 0.3333333333333333 | 0.3333333333333333 | 0.3888888888888889 | 0.2777777777777778 | 6.436306021831654 | 0.33413351644520406 | 0.008333333333333335 | 4.395576057914128 | 0.5424560326393004 |
+| no_planner_reranking | 0.3333333333333333 | 0.3333333333333333 | 0.3888888888888889 | 0.2777777777777778 | 6.436306021831654 | 0.33413351644520406 | 0.008333333333333335 | 4.395576057914128 | 0.5424560326393004 |
+| no_support_mode_conditioning | 0.35185185185185186 | 0.3333333333333333 | 0.3888888888888889 | 0.3333333333333333 | 41.31481176614761 | 0.8930041271227377 | 0.002777777777777778 | 0.9662547600565393 | 0.6302865350411998 |
+| no_wrist_cameras | 0.35185185185185186 | 0.3333333333333333 | 0.3888888888888889 | 0.3333333333333333 | 41.34216132428911 | 0.8971193510073202 | 0.0011574074074074073 | 0.9659118890357264 | 0.6302977896950863 |
+| no_global_camera | 0.35185185185185186 | 0.3333333333333333 | 0.3888888888888889 | 0.3333333333333333 | 41.33038121020353 | 0.8943758684175985 | 0.002777777777777778 | 0.9659084288095618 | 0.6303076523321646 |
+
+## RLBench Headless Smoke
+
+The headless X server files used on this node are:
+
+- `artifacts/logs/system/x99.conf`
+- `artifacts/logs/system/x99.log`
+- `artifacts/logs/system/x99.pid`
+
+The smoke output file is:
+
+- `artifacts/logs/system/rlbench_launch_smoke.txt`
+
+## Dataset Files
+
+- `artifacts/data/reveal_proxy/proxy_train_v4_noleak_counterfactual.pt`
+- `artifacts/data/reveal_proxy/proxy_val_v4_noleak_counterfactual.pt`
+- `artifacts/data/reveal_proxy/proxy_train_clip224_v4_noleak_counterfactual.pt`
+- `artifacts/data/reveal_proxy/proxy_val_clip224_v4_noleak_counterfactual.pt`
+
+## Recreate The Same Software Layout
+
+Use:
+
+```bash
+/workspace/VLAarchtests/environment/setup_same_machine.sh
+```
+
+That helper:
+
+- links the bundled code to `/workspace/reveal_vla_bimanual` if needed
+- clones the pinned third-party repos into `/workspace/third_party`
+- installs the RLBench env
+- installs the reveal env base
+- installs the RLBench headless X prerequisites
+- starts X on `:99`
+
+Raw setup metadata is in:
+
+- `environment/upstream_revisions.txt`
 - `environment/rlbench_env_export.yaml`
 - `environment/rlbench_env_explicit.txt`
 - `environment/rlbench_pip_freeze.txt`
 - `environment/reveal_env_export.yaml`
 - `environment/reveal_env_explicit.txt`
 - `environment/reveal_pip_freeze.txt`
-- `environment/setup_same_machine.sh`
-
-## Smoke tests
-
-### RLBench smoke
-
-- script path: `code/reveal_vla_bimanual/sim_rlbench/launch_smoke.py`
-- fixed camera interface:
-  - `front`
-  - `wrist_left`
-  - `wrist_right`
-- observed smoke payload:
-  - RGB shape per camera: `224x224x3`
-  - camera intrinsics shape: `3x3`
-  - camera extrinsics shape: `4x4`
-  - bimanual action shape: `16`
-
-### Isaac / reveal smoke
-
-- script path: `code/reveal_vla_bimanual/sim_reveal/isaac_smoke.py`
-- log file: `artifacts/logs/isaac_smoke.log`
-- observed status: `app ready`
-
-## RLBench baseline sanity tests
-
-Report file:
-- `artifacts/reports/rlbench_subset3_baseline_sanity.md`
-
-Bounded baseline sanity scope:
-- upstream method: `BIMANUAL_PERACT`
-- tasks:
-  - `bimanual_lift_ball`
-  - `bimanual_push_box`
-  - `bimanual_dual_push_buttons`
-- demos per task: `1`
-- training iterations: `1`
-- batch size: `1`
-- eval episodes per task: `1`
-- eval episode length: `5`
-
-Observed replay fill:
-- `bimanual_lift_ball`: `4` keypoints
-- `bimanual_push_box`: `2` keypoints
-- `bimanual_dual_push_buttons`: `4` keypoints
-
-Observed short-eval episode scores:
-- `bimanual_lift_ball`: `0.0`
-- `bimanual_push_box`: `0.0`
-- `bimanual_dual_push_buttons`: `0.0`
-
-Persisted baseline artifacts:
-- `artifacts/logs/rlbench2_subset3/multi_3cam_subset3/BIMANUAL_PERACT/seed0/weights/0/QAttentionAgent_layer0.pt`
-- `artifacts/logs/rlbench2_subset/multi_3cam_subset/BIMANUAL_PERACT/seed0/weights/0/QAttentionAgent_layer0.pt`
-
-## Reveal-proxy benchmark facts
-
-Primary report files:
-- `artifacts/reports/reveal_eval_v2/reveal_benchmark.md`
-- `artifacts/reports/reveal_eval_v2/reveal_benchmark.json`
-
-Backbone-only proxy benchmark:
-- mean success: `0.9583333333333334`
-- per-task success:
-  - `foliage_proxy`: `0.9583333333333334`
-  - `bag_proxy`: `1.0`
-  - `cloth_proxy`: `0.9166666666666666`
-- visibility integral: `5.28285722186168`
-- corridor availability: `0.7595054432749748`
-- reocclusion rate: `0.0`
-- persistence horizon MAE: `0.0`
-- disturbance cost: `0.1763312140893605`
-
-Reveal-state proxy benchmark:
-- mean success: `0.6944444444444445`
-- per-task success:
-  - `foliage_proxy`: `0.75`
-  - `bag_proxy`: `0.625`
-  - `cloth_proxy`: `0.7083333333333334`
-- visibility integral: `24.614064537816578`
-- corridor availability: `0.8740722197625372`
-- reocclusion rate: `0.006712962962962964`
-- persistence horizon MAE: `1.284850824998643`
-- disturbance cost: `0.44315123330387807`
-
-## Reveal-proxy ablation facts
-
-Report files:
-- `artifacts/reports/reveal_ablation/ablations.md`
-- `artifacts/reports/reveal_ablation/ablations.json`
-
-Observed mean success by ablation:
-- `full_model`: `0.6666666666666666`
-- `no_reveal_state_head`: `0.611111111111111`
-- `no_world_model`: `0.611111111111111`
-- `no_planner_reranking`: `0.611111111111111`
-- `no_support_mode_conditioning`: `0.7222222222222222`
-- `no_wrist_cameras`: `0.75`
-- `no_global_camera`: `0.5555555555555556`
-
-Other recorded ablation metrics are in:
-- `artifacts/reports/reveal_ablation/ablations.json`
-
-## Custom RLBench runs with dummy backbone
-
-Report files:
-- `artifacts/reports/rlbench_custom/rlbench_subset3_custom_eval.md`
-- `artifacts/reports/rlbench_custom/backbone_only_rollout/rollout_eval.json`
-- `artifacts/reports/rlbench_custom/reveal_state_rollout_noplan/rollout_eval.json`
-- `artifacts/reports/rlbench_custom/reveal_state_rollout_plan/rollout_eval.json`
-
-Backbone:
-- frozen dummy backbone
-
-Offline training results:
-- backbone-only:
-  - final train total: `0.00792471425726641`
-  - final val total: `0.005605970580716608`
-- reveal-state:
-  - final train total: `0.007828686845944807`
-  - final val total: `0.0091639062995958`
-
-Live rollout results:
-- backbone-only, `plan=false`: mean success `0.0`
-- reveal-state, `plan=false`: mean success `0.0`
-- reveal-state, `plan=true`: mean success `0.0`
-
-## Custom RLBench runs with frozen CLIP backbone
-
-Report files:
-- `artifacts/reports/rlbench_custom_clip/rlbench_subset3_clip_eval.md`
-- `artifacts/reports/rlbench_custom_clip/backbone_only_rollout/rollout_eval.json`
-- `artifacts/reports/rlbench_custom_clip/reveal_state_rollout_noplan/rollout_eval.json`
-- `artifacts/reports/rlbench_custom_clip/reveal_state_rollout_plan/rollout_eval.json`
-
-Backbone:
-- frozen `openai/clip-vit-base-patch32`
-
-Proxy pretraining results:
-- backbone-only CLIP:
-  - final train total: `0.007774835790102784`
-  - final val total: `0.005187951255634073`
-- reveal-state CLIP:
-  - final train total: `0.3623058025905599`
-  - final val total: `0.3356363290832156`
-
-RLBench offline training results:
-- backbone-only CLIP:
-  - final train total: `0.007243322389241776`
-  - final val total: `0.004669623740794346`
-- reveal-state CLIP:
-  - final train total: `0.0070935887447924045`
-  - final val total: `0.004233352240750238`
-
-Live rollout results:
-- backbone-only CLIP, `plan=false`: mean success `0.0`
-- reveal-state CLIP, `plan=false`: mean success `0.0`
-- reveal-state CLIP, `plan=true`: mean success `0.0`
-
-Per-task live rollout success for all three CLIP rollout runs:
-- `bimanual_lift_ball`: `0.0`
-- `bimanual_push_box`: `0.0`
-- `bimanual_dual_push_buttons`: `0.0`
-
-## Output artifact roots
-
-- proxy checkpoints:
-  - `artifacts/outputs/reveal_runs/`
-- custom RLBench checkpoints:
-  - `artifacts/outputs/rlbench_custom/`
-
-Checkpoint index:
-- `MODEL_INDEX.md`
-
-## Notes on scope
-
-- A full official PerAct2 reproduction on the complete task split is not present in this package.
-- The package contains bounded subset runs, smoke tests, proxy benchmarks, ablations, checkpoints, reports, and logs generated during this workspace session.

code/reveal_vla_bimanual/README.md

@@ -1,6 +1,8 @@
 # reveal_vla_bimanual
 
-Simulation-first prototype for bimanual reveal-and-retrieve under elastic occlusion.
+Simulation-first prototype for a language-conditioned bimanual reveal-and-retrieve policy under elastic occlusion.
+
+This repo is not a generalist VLA backbone in the RT-2 / OpenVLA / Octo sense. The current contribution is the reveal-state machinery layered on top of a frozen vision-language encoder.
 
 This repo is structured around five top-level modules:
 

code/reveal_vla_bimanual/pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta"
 [project]
 name = "reveal-vla-bimanual"
 version = "0.1.0"
-description = "Simulation-first bimanual reveal-and-retrieve prototype"
+description = "Language-conditioned bimanual reveal-and-retrieve policy prototype"
 readme = "README.md"
 requires-python = ">=3.10,<3.11"
 dependencies = [

code/reveal_vla_bimanual/sim_rlbench/dataset.py

@@ -212,6 +212,7 @@ class RLBenchOfflineChunkDataset(Dataset[dict[str, Any]]):
         chunk_size: int = 8,
         proprio_dim: int = 32,
         cameras: Sequence[str] = THREE_CAMERAS,
+        history_steps: int = 2,
         max_samples: int | None = None,
     ) -> None:
         self.dataset_root = Path(dataset_root)
@@ -221,6 +222,7 @@ class RLBenchOfflineChunkDataset(Dataset[dict[str, Any]]):
         self.chunk_size = int(chunk_size)
         self.proprio_dim = int(proprio_dim)
         self.cameras = tuple(cameras)
+        self.history_steps = int(history_steps)
         self._episodes: dict[str, EpisodeRecord] = {}
         self._samples: list[SampleRecord] = []
 
@@ -277,6 +279,33 @@ class RLBenchOfflineChunkDataset(Dataset[dict[str, Any]]):
             actions.append(action)
         return torch.from_numpy(np.stack(actions, axis=0))
 
+    def _history_rgb_stack(self, episode_dir: Path, step_index: int) -> torch.Tensor:
+        if self.history_steps <= 0:
+            return torch.zeros((0, len(self.cameras), 3, self.resolution, self.resolution), dtype=torch.float32)
+        history_frames = []
+        for history_offset in range(self.history_steps, 0, -1):
+            history_index = max(0, step_index - history_offset)
+            history_frames.append(self._load_rgb_stack(episode_dir, history_index))
+        return torch.stack(history_frames, dim=0)
+
+    def _history_proprio(self, observations: Any, step_index: int) -> torch.Tensor:
+        if self.history_steps <= 0:
+            return torch.zeros((0, self.proprio_dim), dtype=torch.float32)
+        history_features = []
+        for history_offset in range(self.history_steps, 0, -1):
+            history_index = max(0, step_index - history_offset)
+            history_features.append(
+                torch.from_numpy(
+                    bimanual_proprio_from_obs(
+                        observations[history_index],
+                        timestep=history_index,
+                        episode_length=len(observations),
+                        target_dim=self.proprio_dim,
+                    )
+                )
+            )
+        return torch.stack(history_features, dim=0)
+
     def __getitem__(self, index: int) -> dict[str, Any]:
         sample = self._samples[index]
         episode = self._episodes[sample.episode_key]
@@ -284,6 +313,8 @@ class RLBenchOfflineChunkDataset(Dataset[dict[str, Any]]):
         obs = observations[sample.step_index]
         return {
             "images": self._load_rgb_stack(episode.episode_dir, sample.step_index),
+            "history_images": self._history_rgb_stack(episode.episode_dir, sample.step_index),
+            "history_proprio": self._history_proprio(observations, sample.step_index),
             "proprio": torch.from_numpy(
                 bimanual_proprio_from_obs(
                     obs,
@@ -309,4 +340,5 @@ class RLBenchOfflineChunkDataset(Dataset[dict[str, Any]]):
             "resolution": self.resolution,
             "chunk_size": self.chunk_size,
             "proprio_dim": self.proprio_dim,
+            "history_steps": self.history_steps,
         }

code/reveal_vla_bimanual/train/configs/proxy_backbone_only.yaml

@@ -8,11 +8,13 @@ data:
   resolution: 96
   train_episodes_per_proxy: 48
   val_episodes_per_proxy: 16
-  train_dataset_path: /workspace/data/reveal_proxy/proxy_train_v2.pt
-  val_dataset_path: /workspace/data/reveal_proxy/proxy_val_v2.pt
+  train_dataset_path: /workspace/data/reveal_proxy/proxy_train_v4_noleak_counterfactual.pt
+  val_dataset_path: /workspace/data/reveal_proxy/proxy_val_v4_noleak_counterfactual.pt
   rebuild_dataset: true
   chunk_horizon: 8
   rollout_horizon: 5
+  history_steps: 2
+  planner_candidates: 4
   seed: 7
 
 optim:
@@ -46,6 +48,11 @@ policy:
     dropout: 0.1
     proprio_dim: 32
     proprio_tokens: 1
+  memory:
+    hidden_dim: 128
+    history_steps: 2
+    num_layers: 1
+    dropout: 0.1
   decoder:
     hidden_dim: 128
     num_heads: 4
@@ -69,13 +76,10 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
   planner:
+    hidden_dim: 128
     num_candidates: 8
-    corridor_weight: 1.0
-    persistence_weight: 0.5
-    proposal_weight: 0.5
-    disturbance_weight: 0.75
-    reocclusion_weight: 0.5
-    visibility_weight: 0.25
+    action_dim: 14
+    utility_margin: 0.1
 
 loss_weights:
   action: 1.0
@@ -85,3 +89,6 @@ loss_weights:
   disturbance: 0.05
   world_model: 0.1
   belief: 0.05
+  planner_success: 0.0
+  planner_risk: 0.0
+  planner_ranking: 0.0

code/reveal_vla_bimanual/train/configs/proxy_backbone_only_clip.yaml

@@ -8,11 +8,13 @@ data:
   resolution: 224
   train_episodes_per_proxy: 48
   val_episodes_per_proxy: 16
-  train_dataset_path: /workspace/data/reveal_proxy/proxy_train_clip224.pt
-  val_dataset_path: /workspace/data/reveal_proxy/proxy_val_clip224.pt
+  train_dataset_path: /workspace/data/reveal_proxy/proxy_train_clip224_v4_noleak_counterfactual.pt
+  val_dataset_path: /workspace/data/reveal_proxy/proxy_val_clip224_v4_noleak_counterfactual.pt
   rebuild_dataset: true
   chunk_horizon: 8
   rollout_horizon: 5
+  history_steps: 2
+  planner_candidates: 4
   seed: 7
 
 optim:
@@ -49,6 +51,11 @@ policy:
     dropout: 0.1
     proprio_dim: 32
     proprio_tokens: 1
+  memory:
+    hidden_dim: 512
+    history_steps: 2
+    num_layers: 1
+    dropout: 0.1
   decoder:
     hidden_dim: 512
     num_heads: 8
@@ -72,13 +79,10 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
   planner:
+    hidden_dim: 512
     num_candidates: 8
-    corridor_weight: 1.0
-    persistence_weight: 0.5
-    proposal_weight: 0.5
-    disturbance_weight: 0.75
-    reocclusion_weight: 0.5
-    visibility_weight: 0.25
+    action_dim: 14
+    utility_margin: 0.1
 
 loss_weights:
   action: 1.0
@@ -88,3 +92,6 @@ loss_weights:
   disturbance: 0.05
   world_model: 0.1
   belief: 0.05
+  planner_success: 0.0
+  planner_risk: 0.0
+  planner_ranking: 0.0

code/reveal_vla_bimanual/train/configs/proxy_backbone_only_smoke.yaml

@@ -0,0 +1,100 @@
+experiment_name: proxy_backbone_only_smoke
+output_dir: /workspace/outputs/smoke
+device: cuda
+seed: 11
+
+data:
+  proxies: [foliage_proxy, bag_proxy, cloth_proxy]
+  resolution: 64
+  train_episodes_per_proxy: 6
+  val_episodes_per_proxy: 2
+  train_dataset_path: /workspace/data/reveal_proxy/proxy_train_smoke_v4.pt
+  val_dataset_path: /workspace/data/reveal_proxy/proxy_val_smoke_v4.pt
+  rebuild_dataset: true
+  chunk_horizon: 4
+  rollout_horizon: 3
+  history_steps: 2
+  planner_candidates: 4
+  seed: 11
+
+optim:
+  epochs: 2
+  batch_size: 8
+  num_workers: 0
+  lr: 0.001
+  weight_decay: 0.0001
+
+trainer:
+  policy_type: backbone_only
+  use_bf16: true
+  grad_clip_norm: 1.0
+  freeze_backbone: true
+  gradient_checkpointing: false
+  plan_during_train: false
+  plan_during_eval: false
+  support_mode_conditioning: true
+
+policy:
+  backbone:
+    model_name: openai/clip-vit-base-patch32
+    hidden_dim: 64
+    max_text_tokens: 32
+    freeze_backbone: true
+    gradient_checkpointing: false
+    use_dummy_backbone: true
+  fusion:
+    hidden_dim: 64
+    num_cameras: 3
+    num_layers: 2
+    num_heads: 4
+    ff_dim: 128
+    dropout: 0.1
+    proprio_dim: 32
+    proprio_tokens: 1
+  memory:
+    hidden_dim: 64
+    history_steps: 2
+    num_layers: 1
+    dropout: 0.1
+  decoder:
+    hidden_dim: 64
+    num_heads: 4
+    num_layers: 2
+    ff_dim: 128
+    dropout: 0.1
+    chunk_size: 4
+    action_dim: 14
+    arm_action_dim: 7
+    num_candidates: 4
+  reveal_head:
+    hidden_dim: 64
+    num_support_modes: 3
+    num_approach_templates: 32
+    rollout_horizon: 3
+    belief_map_size: 32
+    field_size: 16
+    num_heads: 4
+    predict_belief_map: true
+  world_model:
+    hidden_dim: 64
+    action_dim: 14
+    num_support_modes: 3
+    num_approach_templates: 32
+    rollout_horizon: 3
+  planner:
+    hidden_dim: 64
+    num_candidates: 4
+    action_dim: 14
+    utility_margin: 0.1
+
+loss_weights:
+  action: 1.0
+  support_mode: 0.0
+  corridor: 0.0
+  persistence: 0.0
+  disturbance: 0.0
+  world_model: 0.0
+  belief: 0.0
+  planner_success: 0.0
+  planner_risk: 0.0
+  planner_ranking: 0.0

code/reveal_vla_bimanual/train/configs/proxy_reveal_state.yaml

@@ -8,11 +8,13 @@ data:
   resolution: 96
   train_episodes_per_proxy: 48
   val_episodes_per_proxy: 16
-  train_dataset_path: /workspace/data/reveal_proxy/proxy_train_v2.pt
-  val_dataset_path: /workspace/data/reveal_proxy/proxy_val_v2.pt
-  rebuild_dataset: false
+  train_dataset_path: /workspace/data/reveal_proxy/proxy_train_v4_noleak_counterfactual.pt
+  val_dataset_path: /workspace/data/reveal_proxy/proxy_val_v4_noleak_counterfactual.pt
+  rebuild_dataset: true
   chunk_horizon: 8
   rollout_horizon: 5
+  history_steps: 2
+  planner_candidates: 4
   seed: 7
 
 optim:
@@ -46,6 +48,11 @@ policy:
     dropout: 0.1
     proprio_dim: 32
     proprio_tokens: 1
+  memory:
+    hidden_dim: 128
+    history_steps: 2
+    num_layers: 1
+    dropout: 0.1
   decoder:
     hidden_dim: 128
     num_heads: 4
@@ -61,6 +68,8 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
     belief_map_size: 32
+    field_size: 16
+    num_heads: 4
     predict_belief_map: true
   world_model:
     hidden_dim: 128
@@ -69,13 +78,10 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
   planner:
+    hidden_dim: 128
     num_candidates: 8
-    corridor_weight: 1.0
-    persistence_weight: 0.65
-    proposal_weight: 0.35
-    disturbance_weight: 0.8
-    reocclusion_weight: 0.6
-    visibility_weight: 0.35
+    action_dim: 14
+    utility_margin: 0.1
 
 loss_weights:
   action: 1.0
@@ -85,3 +91,6 @@ loss_weights:
   disturbance: 0.1
   world_model: 0.2
   belief: 0.05
+  planner_success: 0.2
+  planner_risk: 0.1
+  planner_ranking: 0.1

code/reveal_vla_bimanual/train/configs/proxy_reveal_state_clip.yaml

@@ -8,11 +8,13 @@ data:
   resolution: 224
   train_episodes_per_proxy: 48
   val_episodes_per_proxy: 16
-  train_dataset_path: /workspace/data/reveal_proxy/proxy_train_clip224.pt
-  val_dataset_path: /workspace/data/reveal_proxy/proxy_val_clip224.pt
-  rebuild_dataset: false
+  train_dataset_path: /workspace/data/reveal_proxy/proxy_train_clip224_v4_noleak_counterfactual.pt
+  val_dataset_path: /workspace/data/reveal_proxy/proxy_val_clip224_v4_noleak_counterfactual.pt
+  rebuild_dataset: true
   chunk_horizon: 8
   rollout_horizon: 5
+  history_steps: 2
+  planner_candidates: 4
   seed: 7
 
 optim:
@@ -49,6 +51,11 @@ policy:
     dropout: 0.1
     proprio_dim: 32
     proprio_tokens: 1
+  memory:
+    hidden_dim: 512
+    history_steps: 2
+    num_layers: 1
+    dropout: 0.1
   decoder:
     hidden_dim: 512
     num_heads: 8
@@ -64,6 +71,8 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
     belief_map_size: 32
+    field_size: 16
+    num_heads: 4
     predict_belief_map: true
   world_model:
     hidden_dim: 512
@@ -72,13 +81,10 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
   planner:
+    hidden_dim: 512
     num_candidates: 8
-    corridor_weight: 1.0
-    persistence_weight: 0.65
-    proposal_weight: 0.35
-    disturbance_weight: 0.8
-    reocclusion_weight: 0.6
-    visibility_weight: 0.35
+    action_dim: 14
+    utility_margin: 0.1
 
 loss_weights:
   action: 1.0
@@ -88,3 +94,6 @@ loss_weights:
   disturbance: 0.1
   world_model: 0.2
   belief: 0.05
+  planner_success: 0.2
+  planner_risk: 0.1
+  planner_ranking: 0.1

code/reveal_vla_bimanual/train/configs/proxy_reveal_state_smoke.yaml

@@ -0,0 +1,100 @@
+experiment_name: proxy_reveal_state_smoke
+output_dir: /workspace/outputs/smoke
+device: cuda
+seed: 11
+
+data:
+  proxies: [foliage_proxy, bag_proxy, cloth_proxy]
+  resolution: 64
+  train_episodes_per_proxy: 6
+  val_episodes_per_proxy: 2
+  train_dataset_path: /workspace/data/reveal_proxy/proxy_train_smoke_v4.pt
+  val_dataset_path: /workspace/data/reveal_proxy/proxy_val_smoke_v4.pt
+  rebuild_dataset: false
+  chunk_horizon: 4
+  rollout_horizon: 3
+  history_steps: 2
+  planner_candidates: 4
+  seed: 11
+
+optim:
+  epochs: 2
+  batch_size: 8
+  num_workers: 0
+  lr: 0.001
+  weight_decay: 0.0001
+
+trainer:
+  policy_type: reveal_state
+  use_bf16: true
+  grad_clip_norm: 1.0
+  freeze_backbone: true
+  gradient_checkpointing: false
+  plan_during_train: true
+  plan_during_eval: true
+  support_mode_conditioning: true
+
+policy:
+  backbone:
+    model_name: openai/clip-vit-base-patch32
+    hidden_dim: 64
+    max_text_tokens: 32
+    freeze_backbone: true
+    gradient_checkpointing: false
+    use_dummy_backbone: true
+  fusion:
+    hidden_dim: 64
+    num_cameras: 3
+    num_layers: 2
+    num_heads: 4
+    ff_dim: 128
+    dropout: 0.1
+    proprio_dim: 32
+    proprio_tokens: 1
+  memory:
+    hidden_dim: 64
+    history_steps: 2
+    num_layers: 1
+    dropout: 0.1
+  decoder:
+    hidden_dim: 64
+    num_heads: 4
+    num_layers: 2
+    ff_dim: 128
+    dropout: 0.1
+    chunk_size: 4
+    action_dim: 14
+    arm_action_dim: 7
+    num_candidates: 4
+  reveal_head:
+    hidden_dim: 64
+    num_support_modes: 3
+    num_approach_templates: 32
+    rollout_horizon: 3
+    belief_map_size: 32
+    field_size: 16
+    num_heads: 4
+    predict_belief_map: true
+  world_model:
+    hidden_dim: 64
+    action_dim: 14
+    num_support_modes: 3
+    num_approach_templates: 32
+    rollout_horizon: 3
+  planner:
+    hidden_dim: 64
+    num_candidates: 4
+    action_dim: 14
+    utility_margin: 0.1
+
+loss_weights:
+  action: 1.0
+  support_mode: 0.15
+  corridor: 0.2
+  persistence: 0.1
+  disturbance: 0.1
+  world_model: 0.2
+  belief: 0.05
+  planner_success: 0.2
+  planner_risk: 0.1
+  planner_ranking: 0.1

code/reveal_vla_bimanual/train/configs/rlbench_subset3_backbone_only_clip.yaml

@@ -13,6 +13,7 @@ data:
   resolution: 224
   chunk_horizon: 8
   proprio_dim: 32
+  history_steps: 2
 
 optim:
   epochs: 2
@@ -48,6 +49,11 @@ policy:
     dropout: 0.1
     proprio_dim: 32
     proprio_tokens: 1
+  memory:
+    hidden_dim: 512
+    history_steps: 2
+    num_layers: 1
+    dropout: 0.1
   decoder:
     hidden_dim: 512
     num_heads: 8
@@ -71,13 +77,10 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
   planner:
+    hidden_dim: 512
     num_candidates: 8
-    corridor_weight: 1.0
-    persistence_weight: 0.5
-    proposal_weight: 0.5
-    disturbance_weight: 0.75
-    reocclusion_weight: 0.5
-    visibility_weight: 0.25
+    action_dim: 14
+    utility_margin: 0.1
 
 loss_weights:
   action: 1.0

code/reveal_vla_bimanual/train/configs/rlbench_subset3_backbone_only_dummy.yaml

@@ -13,6 +13,7 @@ data:
   resolution: 224
   chunk_horizon: 8
   proprio_dim: 32
+  history_steps: 2
 
 optim:
   epochs: 2
@@ -48,6 +49,11 @@ policy:
     dropout: 0.1
     proprio_dim: 32
     proprio_tokens: 1
+  memory:
+    hidden_dim: 128
+    history_steps: 2
+    num_layers: 1
+    dropout: 0.1
   decoder:
     hidden_dim: 128
     num_heads: 4
@@ -71,13 +77,10 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
   planner:
+    hidden_dim: 128
     num_candidates: 8
-    corridor_weight: 1.0
-    persistence_weight: 0.5
-    proposal_weight: 0.5
-    disturbance_weight: 0.75
-    reocclusion_weight: 0.5
-    visibility_weight: 0.25
+    action_dim: 14
+    utility_margin: 0.1
 
 loss_weights:
   action: 1.0

code/reveal_vla_bimanual/train/configs/rlbench_subset3_reveal_state_clip.yaml

@@ -13,6 +13,7 @@ data:
   resolution: 224
   chunk_horizon: 8
   proprio_dim: 32
+  history_steps: 2
 
 optim:
   epochs: 2
@@ -48,6 +49,11 @@ policy:
     dropout: 0.1
     proprio_dim: 32
     proprio_tokens: 1
+  memory:
+    hidden_dim: 512
+    history_steps: 2
+    num_layers: 1
+    dropout: 0.1
   decoder:
     hidden_dim: 512
     num_heads: 8
@@ -63,6 +69,8 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
     belief_map_size: 32
+    field_size: 16
+    num_heads: 4
     predict_belief_map: true
   world_model:
     hidden_dim: 512
@@ -71,13 +79,10 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
   planner:
+    hidden_dim: 512
     num_candidates: 8
-    corridor_weight: 1.0
-    persistence_weight: 0.65
-    proposal_weight: 0.35
-    disturbance_weight: 0.8
-    reocclusion_weight: 0.6
-    visibility_weight: 0.35
+    action_dim: 14
+    utility_margin: 0.1
 
 loss_weights:
   action: 1.0
@@ -87,3 +92,6 @@ loss_weights:
   disturbance: 0.1
   world_model: 0.2
   belief: 0.05
+  planner_success: 0.0
+  planner_risk: 0.0
+  planner_ranking: 0.0

code/reveal_vla_bimanual/train/configs/rlbench_subset3_reveal_state_dummy.yaml

@@ -13,6 +13,7 @@ data:
   resolution: 224
   chunk_horizon: 8
   proprio_dim: 32
+  history_steps: 2
 
 optim:
   epochs: 2
@@ -48,6 +49,11 @@ policy:
     dropout: 0.1
     proprio_dim: 32
     proprio_tokens: 1
+  memory:
+    hidden_dim: 128
+    history_steps: 2
+    num_layers: 1
+    dropout: 0.1
   decoder:
     hidden_dim: 128
     num_heads: 4
@@ -63,6 +69,8 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
     belief_map_size: 32
+    field_size: 16
+    num_heads: 4
     predict_belief_map: true
   world_model:
     hidden_dim: 128
@@ -71,13 +79,10 @@ policy:
     num_approach_templates: 32
     rollout_horizon: 5
   planner:
+    hidden_dim: 128
     num_candidates: 8
-    corridor_weight: 1.0
-    persistence_weight: 0.65
-    proposal_weight: 0.35
-    disturbance_weight: 0.8
-    reocclusion_weight: 0.6
-    visibility_weight: 0.35
+    action_dim: 14
+    utility_margin: 0.1
 
 loss_weights:
   action: 1.0
@@ -87,3 +92,6 @@ loss_weights:
   disturbance: 0.1
   world_model: 0.2
   belief: 0.05
+  planner_success: 0.0
+  planner_risk: 0.0
+  planner_ranking: 0.0

code/reveal_vla_bimanual/train/losses.py

@@ -16,6 +16,9 @@ class LossWeights:
     disturbance: float = 0.05
     world_model: float = 0.1
     belief: float = 0.05
+    planner_success: float = 0.1
+    planner_risk: float = 0.05
+    planner_ranking: float = 0.05
 
 
 def chunk_bc_loss(pred_actions: Tensor, target_actions: Tensor, mask: Tensor | None = None) -> Tensor:
@@ -40,25 +43,44 @@ def reveal_state_loss(pred: dict[str, Tensor], target: dict[str, Tensor], weight
         losses["belief"] = F.binary_cross_entropy_with_logits(pred["belief_map"], target["belief_map"].float())
     else:
         losses["belief"] = pred["support_mode_logits"].new_tensor(0.0)
+    if "reocclusion_logit" in pred and "corridor_feasible" in target:
+        target_reocclusion = 1.0 - target["corridor_feasible"].float().amax(dim=-1)
+        losses["reocclusion"] = F.binary_cross_entropy_with_logits(pred["reocclusion_logit"], target_reocclusion)
+    else:
+        losses["reocclusion"] = pred["support_mode_logits"].new_tensor(0.0)
+    if "persistence_uncertainty" in pred:
+        losses["uncertainty"] = pred["persistence_uncertainty"].mean()
+    else:
+        losses["uncertainty"] = pred["support_mode_logits"].new_tensor(0.0)
     return losses
 
 
 def world_model_rollout_consistency_loss(pred_rollout: dict[str, Tensor], target_rollout: dict[str, Tensor]) -> Tensor:
+    has_candidates = pred_rollout["support_mode_logits"].ndim == 4
+    candidate_dim = pred_rollout["support_mode_logits"].shape[1] if has_candidates else 1
+
+    def _expand_target(value: Tensor) -> Tensor:
+        if not has_candidates:
+            return value
+        if value.ndim >= 2 and value.shape[1] == candidate_dim:
+            return value
+        return value.unsqueeze(1).expand(-1, candidate_dim, *value.shape[1:])
+
     horizon = min(
-        pred_rollout["support_mode_logits"].shape[1],
-        target_rollout["support_mode"].shape[1],
+        pred_rollout["support_mode_logits"].shape[-2],
+        target_rollout["support_mode"].shape[-1],
     )
     pred_rollout = {
-        "support_mode_logits": pred_rollout["support_mode_logits"][:, :horizon],
-        "corridor_logits": pred_rollout["corridor_logits"][:, :horizon],
-        "persistence_horizon": pred_rollout["persistence_horizon"][:, :horizon],
-        "disturbance_cost": pred_rollout["disturbance_cost"][:, :horizon],
+        "support_mode_logits": pred_rollout["support_mode_logits"][..., :horizon, :],
+        "corridor_logits": pred_rollout["corridor_logits"][..., :horizon, :, :],
+        "persistence_horizon": pred_rollout["persistence_horizon"][..., :horizon, :],
+        "disturbance_cost": pred_rollout["disturbance_cost"][..., :horizon],
     }
     target_rollout = {
-        "support_mode": target_rollout["support_mode"][:, :horizon],
-        "corridor_feasible": target_rollout["corridor_feasible"][:, :horizon],
-        "persistence_horizon": target_rollout["persistence_horizon"][:, :horizon],
-        "disturbance_cost": target_rollout["disturbance_cost"][:, :horizon],
+        "support_mode": _expand_target(target_rollout["support_mode"][..., :horizon]),
+        "corridor_feasible": _expand_target(target_rollout["corridor_feasible"][..., :horizon, :, :]),
+        "persistence_horizon": _expand_target(target_rollout["persistence_horizon"][..., :horizon, :]),
+        "disturbance_cost": _expand_target(target_rollout["disturbance_cost"][..., :horizon]),
     }
     return (
         F.cross_entropy(
@@ -95,17 +117,29 @@ def compute_total_loss(
             + weights.persistence * reveal_losses["persistence"]
             + weights.disturbance * reveal_losses["disturbance"]
             + weights.belief * reveal_losses["belief"]
+            + 0.02 * reveal_losses["reocclusion"]
+            + 0.01 * reveal_losses["uncertainty"]
         )
 
-    if "planned_rollout" in model_output and "rollout_support_mode" in batch:
-        rollout_target = {
-            "support_mode": batch["rollout_support_mode"],
-            "corridor_feasible": batch["rollout_corridor_feasible"],
-            "persistence_horizon": batch["rollout_persistence_horizon"],
-            "disturbance_cost": batch["rollout_disturbance_cost"],
-        }
+    if "planned_rollout" in model_output and (
+        "candidate_rollout_support_mode" in batch or "rollout_support_mode" in batch
+    ):
+        if "candidate_rollout_support_mode" in batch:
+            rollout_target = {
+                "support_mode": batch["candidate_rollout_support_mode"],
+                "corridor_feasible": batch["candidate_rollout_corridor_feasible"],
+                "persistence_horizon": batch["candidate_rollout_persistence_horizon"],
+                "disturbance_cost": batch["candidate_rollout_disturbance_cost"],
+            }
+        else:
+            rollout_target = {
+                "support_mode": batch["rollout_support_mode"],
+                "corridor_feasible": batch["rollout_corridor_feasible"],
+                "persistence_horizon": batch["rollout_persistence_horizon"],
+                "disturbance_cost": batch["rollout_disturbance_cost"],
+            }
         world_model_loss = world_model_rollout_consistency_loss(
-            {key: value[:, 0] for key, value in model_output["planned_rollout"].items()},
+            model_output["planned_rollout"],
             rollout_target,
         )
         losses["world_model"] = world_model_loss
@@ -113,5 +147,40 @@ def compute_total_loss(
     else:
         losses["world_model"] = model_output["action_mean"].new_tensor(0.0)
 
+    if "planner_success_logits" in model_output and "candidate_retrieval_success" in batch:
+        success_target = batch["candidate_retrieval_success"].float()
+        risk_target = batch.get("candidate_risk")
+        if risk_target is None:
+            risk_target = torch.clamp(
+                batch["candidate_final_disturbance_cost"].float() + batch["candidate_reocclusion_rate"].float(),
+                0.0,
+                1.0,
+            )
+        utility_target = batch.get("candidate_utility")
+        if utility_target is None:
+            utility_target = success_target - risk_target
+        success_loss = F.binary_cross_entropy_with_logits(model_output["planner_success_logits"], success_target)
+        risk_loss = F.mse_loss(model_output["planner_risk_values"], risk_target.float())
+        pred_diff = model_output["planner_scores"].unsqueeze(-1) - model_output["planner_scores"].unsqueeze(-2)
+        target_diff = utility_target.float().unsqueeze(-1) - utility_target.float().unsqueeze(-2)
+        ranking_mask = target_diff.abs() > 1e-4
+        if ranking_mask.any():
+            ranking_loss = torch.relu(0.1 - torch.sign(target_diff) * pred_diff)[ranking_mask].mean()
+        else:
+            ranking_loss = model_output["planner_scores"].new_tensor(0.0)
+        losses["planner_success"] = success_loss
+        losses["planner_risk"] = risk_loss
+        losses["planner_ranking"] = ranking_loss
+        total = (
+            total
+            + weights.planner_success * success_loss
+            + weights.planner_risk * risk_loss
+            + weights.planner_ranking * ranking_loss
+        )
+    else:
+        losses["planner_success"] = model_output["action_mean"].new_tensor(0.0)
+        losses["planner_risk"] = model_output["action_mean"].new_tensor(0.0)
+        losses["planner_ranking"] = model_output["action_mean"].new_tensor(0.0)
+
     losses["total"] = total
     return losses

code/reveal_vla_bimanual/train/run_experiment.py

@@ -14,6 +14,7 @@ from torch.utils.data import DataLoader
 from models.action_decoder import ChunkDecoderConfig
 from models.backbones import FrozenVLBackboneConfig
 from models.multiview_fusion import MultiViewFusionConfig
+from models.observation_memory import ObservationMemoryConfig
 from models.planner import PlannerConfig
 from models.policy import PolicyConfig
 from models.reveal_head import RevealHeadConfig
@@ -37,6 +38,7 @@ def _policy_config_from_omega(cfg: Any) -> PolicyConfig:
     return PolicyConfig(
         backbone=FrozenVLBackboneConfig(**OmegaConf.to_container(cfg.backbone, resolve=True)),
         fusion=MultiViewFusionConfig(**OmegaConf.to_container(cfg.fusion, resolve=True)),
+        memory=ObservationMemoryConfig(**OmegaConf.to_container(cfg.get("memory", {}), resolve=True)),
         decoder=ChunkDecoderConfig(**OmegaConf.to_container(cfg.decoder, resolve=True)),
         reveal_head=RevealHeadConfig(**OmegaConf.to_container(cfg.reveal_head, resolve=True)),
         world_model=RevealWMConfig(**OmegaConf.to_container(cfg.world_model, resolve=True)),
@@ -65,6 +67,8 @@ def _build_dataset_from_config(data_cfg: Any, split: str) -> dict[str, Any]:
         seed=int(data_cfg.seed) + (10_000 if split == "val" else 0),
         chunk_horizon=int(data_cfg.chunk_horizon),
         rollout_horizon=int(data_cfg.rollout_horizon),
+        history_steps=int(data_cfg.get("history_steps", 2)),
+        planner_candidates=int(data_cfg.get("planner_candidates", 4)),
     )
     if dataset_path:
         save_teacher_dataset(dataset_path, dataset_bundle)
@@ -152,10 +156,14 @@ def main() -> None:
                     "images": moved["images"],
                     "proprio": moved["proprio"],
                     "texts": moved["texts"],
+                    "history_images": moved.get("history_images"),
+                    "history_proprio": moved.get("history_proprio"),
                 }
                 if trainer_config.policy_type == "reveal_state":
                     forward_kwargs["plan"] = trainer_config.plan_during_eval
                     forward_kwargs["support_mode_conditioning"] = trainer_config.support_mode_conditioning
+                    if "candidate_action_chunks" in moved:
+                        forward_kwargs["candidate_chunks_override"] = moved["candidate_action_chunks"]
                 output = model(**forward_kwargs)
                 losses = compute_total_loss(output, moved, weights=loss_weights)
                 val_losses.append({key: float(value.detach().cpu()) for key, value in losses.items()})

code/reveal_vla_bimanual/train/run_rlbench_experiment.py

@@ -67,6 +67,7 @@ def main() -> None:
         resolution=int(cfg.data.resolution),
         chunk_size=int(cfg.data.chunk_horizon),
         proprio_dim=int(cfg.data.proprio_dim),
+        history_steps=int(cfg.data.get("history_steps", 2)),
         max_samples=cfg.data.get("max_train_samples"),
     )
     val_dataset = RLBenchOfflineChunkDataset(
@@ -76,6 +77,7 @@ def main() -> None:
         resolution=int(cfg.data.resolution),
         chunk_size=int(cfg.data.chunk_horizon),
         proprio_dim=int(cfg.data.proprio_dim),
+        history_steps=int(cfg.data.get("history_steps", 2)),
         max_samples=cfg.data.get("max_val_samples"),
     )
     train_loader = _make_loader(
@@ -93,6 +95,13 @@ def main() -> None:
 
     policy_config = _policy_config_from_omega(cfg.policy)
     trainer_config = _trainer_config_from_omega(cfg.trainer)
+    planning_disabled_for_rlbench = False
+    if trainer_config.policy_type == "reveal_state" and (
+        trainer_config.plan_during_train or trainer_config.plan_during_eval
+    ):
+        trainer_config.plan_during_train = False
+        trainer_config.plan_during_eval = False
+        planning_disabled_for_rlbench = True
     loss_weights = _loss_weights_from_omega(cfg.loss_weights)
     model = build_policy(policy_config, trainer_config).to(device)
     init_info = _load_init_checkpoint(model, cfg.get("init_checkpoint"), bool(cfg.get("init_strict", False)))
@@ -122,6 +131,8 @@ def main() -> None:
                     "images": moved["images"],
                     "proprio": moved["proprio"],
                     "texts": moved["texts"],
+                    "history_images": moved.get("history_images"),
+                    "history_proprio": moved.get("history_proprio"),
                 }
                 if trainer_config.policy_type == "reveal_state":
                     forward_kwargs["plan"] = trainer_config.plan_during_eval
@@ -167,6 +178,7 @@ def main() -> None:
         "train_dataset": train_dataset.summary(),
         "val_dataset": val_dataset.summary(),
         "init_info": init_info,
+        "planning_disabled_for_rlbench": planning_disabled_for_rlbench,
     }
     (output_dir / "summary.json").write_text(json.dumps(summary, indent=2), encoding="utf-8")
     print(json.dumps(summary, indent=2))

code/reveal_vla_bimanual/train/trainer.py

@@ -53,10 +53,14 @@ class BimanualTrainer:
                 "proprio": proprio,
                 "texts": texts if isinstance(texts, Sequence) else None,
                 "language_tokens": language_tokens if isinstance(language_tokens, dict) else None,
+                "history_images": batch.get("history_images"),
+                "history_proprio": batch.get("history_proprio"),
             }
             if self.config.policy_type == "reveal_state":
                 forward_kwargs["plan"] = self.config.plan_during_train
                 forward_kwargs["support_mode_conditioning"] = self.config.support_mode_conditioning
+                if "candidate_action_chunks" in batch:
+                    forward_kwargs["candidate_chunks_override"] = batch["candidate_action_chunks"]
             model_output = self.model(**forward_kwargs)
             losses = compute_total_loss(model_output, batch, weights=loss_weights)
         losses["total"].backward()

environment/README.md

@@ -1,33 +1,40 @@
 # Environment Recreation Files
 
-Files in this directory were added to make it easier to recreate the same machine state on a similar node.
+This directory contains the machine snapshot and setup helpers for the runpod node used for the uploaded artifacts.
+
+## Files
 
-Contents:
 - `hardware_snapshot.txt`
-  - captured machine facts from the source run:
-  - `uname -a`
-  - `lscpu`
-  - `free -h`
-  - `nvidia-smi -L`
-  - `nvidia-smi`
+  - raw outputs for `uname -a`, `lscpu`, `free -h`, `nvidia-smi -L`, and `nvidia-smi`
+- `glxinfo_B.txt`
+  - raw `glxinfo -B` output from the working `:99` X server
+- `upstream_revisions.txt`
+  - third-party repo URLs and pinned commits used on this node
 - `rlbench_env_export.yaml`
-  - `micromamba env export` for Env A
+  - `micromamba env export` for `/workspace/envs/rlbench`
 - `rlbench_env_explicit.txt`
-  - explicit package list for Env A
+  - explicit package list for `/workspace/envs/rlbench`
 - `rlbench_pip_freeze.txt`
-  - `pip freeze` for Env A
+  - `pip freeze` for `/workspace/envs/rlbench`
 - `reveal_env_export.yaml`
-  - `micromamba env export` for Env B
+  - `micromamba env export` for `/workspace/envs/reveal`
 - `reveal_env_explicit.txt`
-  - explicit package list for Env B
+  - explicit package list for `/workspace/envs/reveal`
 - `reveal_pip_freeze.txt`
-  - `pip freeze` for Env B
+  - `pip freeze` for `/workspace/envs/reveal`
 - `setup_same_machine.sh`
-  - wrapper script that runs the repo setup scripts in the same order used here
+  - bundle-aware bootstrap script for a matching `/workspace` machine
+
+## Default Layout
+
+- bundle root: `/workspace/VLAarchtests`
+- bundled project code: `/workspace/VLAarchtests/code/reveal_vla_bimanual`
+- runtime symlink target used by the setup scripts: `/workspace/reveal_vla_bimanual`
+- third-party checkout root: `/workspace/third_party`
 
-The wrapper script assumes:
-- workspace root: `/workspace`
-- project checkout path: `/workspace/reveal_vla_bimanual`
+## Validation Commands
 
-The main repo setup scripts remain under:
-- `code/reveal_vla_bimanual/scripts/`
+```bash
+DISPLAY=:99 glxinfo -B
+/workspace/.tools/micromamba/bin/micromamba run -r /workspace/.micromamba -p /workspace/envs/rlbench python -m sim_rlbench.launch_smoke --headless
+```

environment/glxinfo_B.txt

@@ -0,0 +1,22 @@
+name of display: :99
+display: :99  screen: 0
+direct rendering: Yes
+Memory info (GL_NVX_gpu_memory_info):
+    Dedicated video memory: 49140 MB
+    Total available memory: 49140 MB
+    Currently available dedicated video memory: 48598 MB
+OpenGL vendor string: NVIDIA Corporation
+OpenGL renderer string: NVIDIA RTX 6000 Ada Generation/PCIe/SSE2
+OpenGL core profile version string: 4.6.0 NVIDIA 550.127.05
+OpenGL core profile shading language version string: 4.60 NVIDIA
+OpenGL core profile context flags: (none)
+OpenGL core profile profile mask: core profile
+
+OpenGL version string: 4.6.0 NVIDIA 550.127.05
+OpenGL shading language version string: 4.60 NVIDIA
+OpenGL context flags: (none)
+OpenGL profile mask: (none)
+
+OpenGL ES profile version string: OpenGL ES 3.2 NVIDIA 550.127.05
+OpenGL ES profile shading language version string: OpenGL ES GLSL ES 3.20
+

environment/hardware_snapshot.txt

@@ -1,7 +1,7 @@
-UTC_DATE=2026-03-23T02:59:22Z
+UTC_DATE=2026-03-23T18:46:00Z
 
 UNAME
-Linux e52be9725b2e 6.8.0-62-generic #65-Ubuntu SMP PREEMPT_DYNAMIC Mon May 19 17:15:03 UTC 2025 x86_64 x86_64 x86_64 GNU/Linux
+Linux c36959bce5da 6.8.0-52-generic #53~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Wed Jan 15 19:18:46 UTC 2 x86_64 x86_64 x86_64 GNU/Linux
 
 LSCPU
 Architecture:                         x86_64
@@ -21,7 +21,7 @@ Stepping:                             1
 Frequency boost:                      enabled
 CPU max MHz:                          4041.8450
 CPU min MHz:                          1500.0000
-BogoMIPS:                             5899.68
+BogoMIPS:                             5900.00
 Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local user_shstk clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin brs arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca debug_swap
 Virtualization:                       AMD-V
 L1d cache:                            2 MiB (64 instances)
@@ -48,29 +48,29 @@ Vulnerability Tsx async abort:        Not affected
 
 FREE
                total        used        free      shared  buff/cache   available
-Mem:           503Gi        57Gi        94Gi       8.4Gi       351Gi       432Gi
+Mem:           503Gi        54Gi       185Gi       512Mi       263Gi       443Gi
 Swap:             0B          0B          0B
 
 NVIDIA_SMI_L
-GPU 0: NVIDIA RTX 6000 Ada Generation (UUID: GPU-4231978c-ce91-8daa-102c-6b3911cd9938)
+GPU 0: NVIDIA RTX 6000 Ada Generation (UUID: GPU-c6807b50-90eb-199d-3f71-256fb12947e2)
 
 NVIDIA_SMI
-Mon Mar 23 02:59:22 2026       
+Mon Mar 23 18:46:00 2026       
 +-----------------------------------------------------------------------------------------+
-| NVIDIA-SMI 570.124.06             Driver Version: 570.124.06     CUDA Version: 12.8     |
+| NVIDIA-SMI 550.127.05             Driver Version: 550.127.05     CUDA Version: 12.4     |
 |-----------------------------------------+------------------------+----------------------+
 | GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
 | Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
 |                                         |                        |               MIG M. |
 |=========================================+========================+======================|
-|   0  NVIDIA RTX 6000 Ada Gene...    On  |   00000000:41:00.0 Off |                  Off |
-| 30%   29C    P8             23W /  300W |      35MiB /  49140MiB |      0%      Default |
+|   0  NVIDIA RTX 6000 Ada Gene...    On  |   00000000:01:00.0 Off |                  Off |
+| 30%   35C    P0             38W /  300W |      32MiB /  49140MiB |      0%      Default |
 |                                         |                        |                  N/A |
 +-----------------------------------------+------------------------+----------------------+
                                                                                          
 +-----------------------------------------------------------------------------------------+
 | Processes:                                                                              |
-|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
+|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
 |        ID   ID                                                               Usage      |
 |=========================================================================================|
 +-----------------------------------------------------------------------------------------+

environment/reveal_env_explicit.txt

@@ -3,15 +3,11 @@ List of packages in environment: "/workspace/envs/reveal"
 
 
 
-
-
 https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-7_kmp_llvm.conda
 
 
 https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.15.3-hb03c661_0.conda
 
-
-
 https://conda.anaconda.org/conda-forge/linux-64/aom-3.9.1-hac33072_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/attr-2.5.2-hb03c661_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/backports.zstd-1.3.0-py310h69bd2ac_0.conda
@@ -19,8 +15,6 @@ https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.45.1-de
 https://conda.anaconda.org/conda-forge/linux-64/binutils_linux-64-2.45.1-default_h4852527_102.conda
 https://conda.anaconda.org/conda-forge/linux-64/blas-2.108-mkl.tar.bz2
 https://conda.anaconda.org/conda-forge/linux-64/blas-devel-3.9.0-8_mkl.tar.bz2
-
-
 https://conda.anaconda.org/conda-forge/linux-64/brotli-1.2.0-hed03a55_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.2.0-hb03c661_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.2.0-py310hba01987_1.conda
@@ -31,27 +25,15 @@ https://conda.anaconda.org/conda-forge/linux-64/cairo-1.18.4-he90730b_1.conda
 https://conda.anaconda.org/conda-forge/noarch/certifi-2026.2.25-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.4.6-pyhd8ed1ab_0.conda
 
-
 https://conda.anaconda.org/conda-forge/linux-64/cmake-4.3.0-hc85cc9f_0.conda
-
-
-
-
-
-
-
-
-
 https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.3.2-py310h3788b33_0.conda
 https://conda.anaconda.org/conda-forge/noarch/cpython-3.10.20-py310hd8ed1ab_0.conda
-
 https://conda.anaconda.org/nvidia/linux-64/cuda-cudart-12.1.105-0.tar.bz2
 https://conda.anaconda.org/nvidia/linux-64/cuda-cupti-12.1.105-0.tar.bz2
 https://conda.anaconda.org/nvidia/linux-64/cuda-libraries-12.1.0-0.tar.bz2
 https://conda.anaconda.org/nvidia/linux-64/cuda-nvrtc-12.1.105-0.tar.bz2
 https://conda.anaconda.org/nvidia/linux-64/cuda-nvtx-12.1.105-0.tar.bz2
 https://conda.anaconda.org/nvidia/linux-64/cuda-opencl-12.9.19-0.conda
-
 https://conda.anaconda.org/nvidia/linux-64/cuda-runtime-12.1.0-0.tar.bz2
 https://conda.anaconda.org/nvidia/noarch/cuda-version-12.9-3.conda
 https://conda.anaconda.org/conda-forge/noarch/cycler-0.12.1-pyhcf101f3_2.conda
@@ -60,12 +42,8 @@ https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/dbus-1.16.2-h24cb091_1.conda
 
 
-
-
-
-https://conda.anaconda.org/conda-forge/linux-64/ffmpeg-8.0.1-gpl_hcddb375_914.conda
+https://conda.anaconda.org/conda-forge/linux-64/ffmpeg-8.0.1-gpl_he74fc74_714.conda
 https://conda.anaconda.org/conda-forge/noarch/filelock-3.25.2-pyhd8ed1ab_0.conda
-
 https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
 https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
 https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2
@@ -93,51 +71,19 @@ https://conda.anaconda.org/conda-forge/linux-64/gst-plugins-base-1.26.10-h036367
 https://conda.anaconda.org/conda-forge/linux-64/gstreamer-1.26.10-h17cb667_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-15.2.0-hda75c37_18.conda
 https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-15.2.0-h1fb793f_21.conda
-
 https://conda.anaconda.org/conda-forge/noarch/h2-4.3.0-pyhcf101f3_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/harfbuzz-13.2.0-h6083320_0.conda
-
+https://conda.anaconda.org/conda-forge/linux-64/harfbuzz-13.2.1-h6083320_0.conda
 
 https://conda.anaconda.org/conda-forge/noarch/hpack-4.1.0-pyhd8ed1ab_0.conda
 
 
-
 https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.1.0-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda
 https://conda.anaconda.org/conda-forge/noarch/idna-3.11-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/imageio-2.37.0-pyhfb79c49_0.conda
-
 https://conda.anaconda.org/conda-forge/linux-64/intel-gmmlib-22.9.0-hb700be7_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/intel-media-driver-26.1.4-hecca717_0.conda
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+https://conda.anaconda.org/conda-forge/linux-64/intel-media-driver-26.1.5-hecca717_0.conda
 https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.6-pyhcf101f3_1.conda
-
-
 https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-5.14.0-he073ed8_3.conda
 https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.3-hb9d3cd8_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.5.0-py310haaf941d_0.conda
@@ -252,8 +198,6 @@ https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.15.2-he237659_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/libxml2-16-2.15.2-hca6bf5a_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_2.conda
 https://conda.anaconda.org/conda-forge/linux-64/llvm-openmp-15.0.7-h0cdce71_0.conda
-
-
 https://conda.anaconda.org/conda-forge/linux-64/make-4.4.1-hb9d3cd8_2.conda
 https://conda.anaconda.org/conda-forge/linux-64/markupsafe-3.0.3-py310h3406613_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/matplotlib-3.8.4-py310hff52083_2.conda
@@ -269,64 +213,36 @@ https://conda.anaconda.org/conda-forge/noarch/munkres-1.1.4-pyhd8ed1ab_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda
 https://conda.anaconda.org/conda-forge/noarch/networkx-3.4.2-pyh267e887_2.conda
 https://conda.anaconda.org/conda-forge/linux-64/ninja-1.13.2-h171cf75_0.conda
-
 https://conda.anaconda.org/conda-forge/linux-64/nspr-4.38-h29cc59b_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/nss-3.118-h445c969_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/numpy-1.26.4-py310hb13e2d6_0.conda
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
 https://conda.anaconda.org/conda-forge/linux-64/ocl-icd-2.3.3-hb9d3cd8_0.conda
 
-
-
 https://conda.anaconda.org/conda-forge/linux-64/opencl-headers-2025.06.13-hecca717_0.conda
-
 https://conda.anaconda.org/conda-forge/linux-64/openh264-2.6.0-hc22cd8d_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/openjpeg-2.5.4-h55fea9a_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/openldap-2.6.10-hbde042b_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda
-
 https://conda.anaconda.org/conda-forge/noarch/packaging-26.0-pyhcf101f3_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/pandas-2.2.3-py310h5eaa309_3.conda
-https://conda.anaconda.org/conda-forge/linux-64/pango-1.56.4-hadf4263_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/pango-1.56.4-hda50119_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/pcre2-10.47-haa7fec5_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/perl-5.32.1-7_hd590300_perl5.conda
 https://conda.anaconda.org/conda-forge/linux-64/pillow-12.1.1-py310h5a73078_0.conda
-
-
 https://conda.anaconda.org/conda-forge/noarch/pip-26.0.1-pyh8b19718_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/pixman-0.46.4-h54a6638_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/pkg-config-0.29.2-h4bc722e_1009.conda
 
-
 https://conda.anaconda.org/conda-forge/noarch/ply-3.11-pyhd8ed1ab_3.conda
 
-
 https://conda.anaconda.org/conda-forge/linux-64/psutil-7.2.2-py310h139afa4_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-hb9d3cd8_1002.conda
 https://conda.anaconda.org/conda-forge/linux-64/pugixml-1.15-h3f63f65_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/pulseaudio-client-17.0-h9a6aba3_3.conda
-
 https://conda.anaconda.org/conda-forge/noarch/pyparsing-3.3.2-pyhcf101f3_0.conda
-
 https://conda.anaconda.org/conda-forge/linux-64/pyqt-5.15.11-py310h046fae5_2.conda
 https://conda.anaconda.org/conda-forge/linux-64/pyqt5-sip-12.17.0-py310hea6c23e_2.conda
 https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha55dd90_7.conda
-
-
 https://conda.anaconda.org/conda-forge/linux-64/python-3.10.20-h3c07f61_0_cpython.conda
 https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.9.0.post0-pyhe01879c_2.conda
 https://conda.anaconda.org/conda-forge/noarch/python-tzdata-2025.3-pyhd8ed1ab_0.conda
@@ -334,20 +250,15 @@ https://conda.anaconda.org/conda-forge/noarch/python_abi-3.10-8_cp310.conda
 https://conda.anaconda.org/pytorch/linux-64/pytorch-2.3.1-py3.10_cuda12.1_cudnn8.9.2_0.tar.bz2
 https://conda.anaconda.org/pytorch/linux-64/pytorch-cuda-12.1-ha16c6d3_6.tar.bz2
 https://conda.anaconda.org/pytorch/noarch/pytorch-mutex-1.0-cuda.tar.bz2
-
 https://conda.anaconda.org/conda-forge/noarch/pytz-2026.1.post1-pyhcf101f3_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/pyyaml-6.0.3-py310h3406613_1.conda
-
-
 https://conda.anaconda.org/conda-forge/linux-64/qt-main-5.15.15-h0c412b5_8.conda
-
 https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda
 
 https://conda.anaconda.org/conda-forge/noarch/requests-2.32.5-pyhcf101f3_1.conda
 
 https://conda.anaconda.org/conda-forge/linux-64/rhash-1.4.6-hb9d3cd8_1.conda
 
-
 https://conda.anaconda.org/conda-forge/linux-64/scipy-1.13.1-py310h93e2701_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/sdl2-2.32.56-h54a6638_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/sdl3-3.4.2-hdeec2a5_0.conda
@@ -360,7 +271,6 @@ https://conda.anaconda.org/conda-forge/noarch/six-1.17.0-pyhe01879c_1.conda
 
 https://conda.anaconda.org/conda-forge/linux-64/snappy-1.2.2-h03e3b7b_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/spirv-tools-2026.1-hb700be7_0.conda
-
 https://conda.anaconda.org/conda-forge/linux-64/svt-av1-4.0.1-hecca717_0.conda
 https://conda.anaconda.org/conda-forge/noarch/sympy-1.14.0-pyh2585a3b_106.conda
 https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-64-2.34-h087de78_3.conda
@@ -372,7 +282,6 @@ https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.con
 
 https://conda.anaconda.org/conda-forge/noarch/toml-0.10.2-pyhcf101f3_3.conda
 https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.0-pyhcf101f3_0.conda
-
 https://conda.anaconda.org/pytorch/linux-64/torchaudio-2.3.1-py310_cu121.tar.bz2
 https://conda.anaconda.org/pytorch/linux-64/torchtriton-2.3.1-py310.tar.bz2
 https://conda.anaconda.org/pytorch/linux-64/torchvision-0.18.1-py310_cu121.tar.bz2
@@ -380,16 +289,13 @@ https://conda.anaconda.org/conda-forge/linux-64/tornado-6.5.4-py310ha78b2d2_0.co
 https://conda.anaconda.org/conda-forge/noarch/tqdm-4.67.3-pyh8f84b5b_0.conda
 
 https://conda.anaconda.org/conda-forge/noarch/trimesh-4.11.4-pyh7b2049a_0.conda
-
 https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
 https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/unicodedata2-17.0.1-py310h7c4b9e2_0.conda
 https://conda.anaconda.org/conda-forge/noarch/urllib3-2.6.3-pyhd8ed1ab_0.conda
 
-
 https://conda.anaconda.org/conda-forge/linux-64/wayland-1.25.0-hd6090a7_0.conda
 https://conda.anaconda.org/conda-forge/noarch/wayland-protocols-1.47-hd8ed1ab_0.conda
-
 https://conda.anaconda.org/conda-forge/noarch/wheel-0.46.3-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/x264-1%21164.3095-h166bdaf_2.tar.bz2
 https://conda.anaconda.org/conda-forge/linux-64/x265-3.5-h924138e_3.tar.bz2

environment/reveal_env_export.yaml

@@ -37,7 +37,7 @@ dependencies:
   - cyrus-sasl=2.1.28=hac629b4_1
   - dav1d=1.2.1=hd590300_0
   - dbus=1.16.2=h24cb091_1
-  - ffmpeg=8.0.1=gpl_hcddb375_914
+  - ffmpeg=8.0.1=gpl_he74fc74_714
   - filelock=3.25.2=pyhd8ed1ab_0
   - font-ttf-dejavu-sans-mono=2.37=hab24e00_0
   - font-ttf-inconsolata=3.000=h77eed37_0
@@ -64,14 +64,14 @@ dependencies:
   - gxx_impl_linux-64=15.2.0=hda75c37_18
   - gxx_linux-64=15.2.0=h1fb793f_21
   - h2=4.3.0=pyhcf101f3_0
-  - harfbuzz=13.2.0=h6083320_0
+  - harfbuzz=13.2.1=h6083320_0
   - hpack=4.1.0=pyhd8ed1ab_0
   - hyperframe=6.1.0=pyhd8ed1ab_0
   - icu=78.3=h33c6efd_0
   - idna=3.11=pyhd8ed1ab_0
   - imageio=2.37.0=pyhfb79c49_0
   - intel-gmmlib=22.9.0=hb700be7_0
-  - intel-media-driver=26.1.4=hecca717_0
+  - intel-media-driver=26.1.5=hecca717_0
   - jinja2=3.1.6=pyhcf101f3_1
   - kernel-headers_linux-64=5.14.0=he073ed8_3
   - keyutils=1.6.3=hb9d3cd8_0
@@ -213,7 +213,7 @@ dependencies:
   - openssl=3.6.1=h35e630c_1
   - packaging=26.0=pyhcf101f3_0
   - pandas=2.2.3=py310h5eaa309_3
-  - pango=1.56.4=hadf4263_0
+  - pango=1.56.4=hda50119_1
   - pcre2=10.47=haa7fec5_0
   - perl=5.32.1=7_hd590300_perl5
   - pillow=12.1.1=py310h5a73078_0
@@ -300,131 +300,36 @@ dependencies:
   - zlib-ng=2.3.3=hceb46e0_1
   - zstd=1.5.7=hb78ec9c_6
   - pip:
-    - Farama-Notifications==0.0.4
     - GitPython==3.1.46
     - Markdown==3.10.2
-    - Pygments==2.19.2
     - Werkzeug==3.1.6
     - absl-py==2.4.0
     - accelerate==0.31.0
     - antlr4-python3-runtime==4.9.3
-    - anyio==4.12.1
-    - anytree==2.13.0
-    - boto3==1.42.73
-    - botocore==1.42.73
     - click==8.3.1
-    - cloudpickle==3.1.2
-    - cmeel==0.59.0
-    - cmeel-assimp==5.4.3.1
-    - cmeel-boost==1.83.0
-    - cmeel-console-bridge==1.0.2.3
-    - cmeel-octomap==1.10.0
-    - cmeel-qhull==8.0.2.1
-    - cmeel-tinyxml==2.6.2.3
-    - cmeel-urdfdom==3.1.1.1
-    - cmeel-zlib==1.3.1
-    - cuda-bindings==12.9.4
-    - cuda-pathfinder==1.4.3
-    - dex_retargeting==0.4.6
     - docker-pycreds==0.4.0
-    - eigenpy==3.5.1
     - einops==0.8.0
-    - exceptiongroup==1.3.1
-    - flatdict==4.0.1
     - fsspec==2026.2.0
     - gitdb==4.0.12
     - grpcio==1.78.0
-    - gymnasium==1.2.0
     - hf-xet==1.4.2
-    - hidapi==0.14.0.post2
-    - hpp-fcl==2.4.4
     - huggingface_hub==0.36.2
     - hydra-core==1.3.2
-    - iniconfig==2.3.0
-    - isaaclab==0.41.3
-    - isaacsim==4.5.0.0
-    - isaacsim-app==4.5.0.0
-    - isaacsim-asset==4.5.0.0
-    - isaacsim-benchmark==4.5.0.0
-    - isaacsim-code-editor==4.5.0.0
-    - isaacsim-core==4.5.0.0
-    - isaacsim-cortex==4.5.0.0
-    - isaacsim-example==4.5.0.0
-    - isaacsim-extscache-kit==4.5.0.0
-    - isaacsim-extscache-kit-sdk==4.5.0.0
-    - isaacsim-extscache-physics==4.5.0.0
-    - isaacsim-gui==4.5.0.0
-    - isaacsim-kernel==4.5.0.0
-    - isaacsim-replicator==4.5.0.0
-    - isaacsim-rl==4.5.0.0
-    - isaacsim-robot==4.5.0.0
-    - isaacsim-robot-motion==4.5.0.0
-    - isaacsim-robot-setup==4.5.0.0
-    - isaacsim-ros1==4.5.0.0
-    - isaacsim-ros2==4.5.0.0
-    - isaacsim-sensor==4.5.0.0
-    - isaacsim-storage==4.5.0.0
-    - isaacsim-template==4.5.0.0
-    - isaacsim-test==4.5.0.0
-    - isaacsim-utils==4.5.0.0
-    - jmespath==1.1.0
-    - junitparser==4.0.2
-    - loop-rate-limiters==1.2.0
-    - lxml==6.0.2
-    - nlopt==2.7.1
-    - nvidia-cublas-cu12==12.8.4.1
-    - nvidia-cuda-cupti-cu12==12.8.90
-    - nvidia-cuda-nvrtc-cu12==12.8.93
-    - nvidia-cuda-runtime-cu12==12.8.90
-    - nvidia-cudnn-cu12==9.10.2.21
-    - nvidia-cufft-cu12==11.3.3.83
-    - nvidia-cufile-cu12==1.13.1.3
-    - nvidia-curand-cu12==10.3.9.90
-    - nvidia-cusolver-cu12==11.7.3.90
-    - nvidia-cusparse-cu12==12.5.8.93
-    - nvidia-cusparselt-cu12==0.7.1
-    - nvidia-nccl-cu12==2.27.5
-    - nvidia-nvjitlink-cu12==12.8.93
-    - nvidia-nvshmem-cu12==3.4.5
-    - nvidia-nvtx-cu12==12.8.90
     - omegaconf==2.3.0
-    - omniverse-kit==106.5.0.162521
-    - onnx==1.16.1
-    - opencv-python==4.11.0.86
-    - osqp==0.6.7.post3
-    - pillow==11.2.1
-    - pin==2.7.0
-    - pin-pink==3.1.0
     - platformdirs==4.9.4
-    - pluggy==1.6.0
-    - prettytable==3.3.0
     - protobuf==5.29.6
-    - pyglet==1.5.31
-    - pyperclip==1.11.0
-    - pytest==9.0.2
-    - pytest-mock==3.15.1
-    - pytransform3d==3.14.4
-    - qdldl==0.1.9.post1
-    - qpsolvers==4.11.0
-    - quadprog==0.1.13
     - regex==2026.2.28
     - reveal-vla-bimanual==0.1.0
-    - s3transfer==0.16.0
     - safetensors==0.4.3
     - sentry-sdk==2.55.0
     - setproctitle==1.3.7
     - setuptools==75.8.0
     - smmap==5.0.3
-    - starlette==0.45.3
     - tensorboard==2.16.2
     - tensorboard-data-server==0.7.2
     - timm==1.0.7
     - tokenizers==0.19.1
-    - torch==2.10.0
     - transformers==4.41.2
-    - triton==3.6.0
     - wandb==0.18.0
-    - warp-lang==1.12.0
-    - wcwidth==0.6.0
 
 prefix: "/workspace/envs/reveal"

environment/reveal_pip_freeze.txt

@@ -1,147 +1,58 @@
 absl-py==2.4.0
 accelerate==0.31.0
 antlr4-python3-runtime==4.9.3
-anyio==4.12.1
-anytree==2.13.0
 backports.zstd @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_backports.zstd_1767044984/work
-boto3==1.42.73
-botocore==1.42.73
 Brotli @ file:///home/conda/feedstock_root/build_artifacts/brotli-split_1764016952863/work
 certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1772001073725/work/certifi
 charset-normalizer @ file:///home/conda/feedstock_root/build_artifacts/charset-normalizer_1773659966602/work
 click==8.3.1
-cloudpickle==3.1.2
-cmeel==0.59.0
-cmeel-assimp==5.4.3.1
-cmeel-boost==1.83.0
-cmeel-console-bridge==1.0.2.3
-cmeel-octomap==1.10.0
-cmeel-qhull==8.0.2.1
-cmeel-tinyxml==2.6.2.3
-cmeel-urdfdom==3.1.1.1
-cmeel-zlib==1.3.1
 contourpy @ file:///home/conda/feedstock_root/build_artifacts/contourpy_1744743067588/work
-cuda-bindings==12.9.4
-cuda-pathfinder==1.4.3
 cycler @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_cycler_1764466758/work
-dex_retargeting==0.4.6
 docker-pycreds==0.4.0
-eigenpy==3.5.1
 einops==0.8.0
-exceptiongroup==1.3.1
-Farama-Notifications==0.0.4
 filelock @ file:///home/conda/feedstock_root/build_artifacts/filelock_1773313889543/work
-flatdict==4.0.1
 fonttools @ file:///home/conda/feedstock_root/build_artifacts/fonttools_1773137064424/work
 fsspec==2026.2.0
 gitdb==4.0.12
 GitPython==3.1.46
 gmpy2 @ file:///home/conda/feedstock_root/build_artifacts/gmpy2_1773244929835/work
 grpcio==1.78.0
-gymnasium==1.2.0
 h2 @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_h2_1756364871/work
 hf-xet==1.4.2
-hidapi==0.14.0.post2
 hpack @ file:///home/conda/feedstock_root/build_artifacts/hpack_1737618293087/work
-hpp-fcl==2.4.4
 huggingface_hub==0.36.2
 hydra-core==1.3.2
 hyperframe @ file:///home/conda/feedstock_root/build_artifacts/hyperframe_1737618333194/work
 idna @ file:///home/conda/feedstock_root/build_artifacts/idna_1760286409563/work
 imageio @ file:///home/conda/feedstock_root/build_artifacts/imageio_1738273805233/work
-iniconfig==2.3.0
--e git+https://github.com/isaac-sim/IsaacLab.git@90b79bb2d44feb8d833f260f2bf37da3487180ba#egg=isaaclab&subdirectory=source/isaaclab
-isaacsim==4.5.0.0
-isaacsim-app==4.5.0.0
-isaacsim-asset==4.5.0.0
-isaacsim-benchmark==4.5.0.0
-isaacsim-code-editor==4.5.0.0
-isaacsim-core==4.5.0.0
-isaacsim-cortex==4.5.0.0
-isaacsim-example==4.5.0.0
-isaacsim-extscache-kit==4.5.0.0
-isaacsim-extscache-kit-sdk==4.5.0.0
-isaacsim-extscache-physics==4.5.0.0
-isaacsim-gui==4.5.0.0
-isaacsim-kernel==4.5.0.0
-isaacsim-replicator==4.5.0.0
-isaacsim-rl==4.5.0.0
-isaacsim-robot==4.5.0.0
-isaacsim-robot-motion==4.5.0.0
-isaacsim-robot-setup==4.5.0.0
-isaacsim-ros1==4.5.0.0
-isaacsim-ros2==4.5.0.0
-isaacsim-sensor==4.5.0.0
-isaacsim-storage==4.5.0.0
-isaacsim-template==4.5.0.0
-isaacsim-test==4.5.0.0
-isaacsim-utils==4.5.0.0
 Jinja2 @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_jinja2_1764517220/work
-jmespath==1.1.0
-junitparser==4.0.2
 kiwisolver @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_kiwisolver_1773067043/work
-loop-rate-limiters==1.2.0
-lxml==6.0.2
 Markdown==3.10.2
 MarkupSafe @ file:///home/conda/feedstock_root/build_artifacts/markupsafe_1772444934960/work
 matplotlib @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-suite_1715976200404/work
 mpmath @ file:///home/conda/feedstock_root/build_artifacts/mpmath_1773661943568/work
 munkres==1.1.4
 networkx @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_networkx_1731521053/work
-nlopt==2.7.1
 numpy @ file:///home/conda/feedstock_root/build_artifacts/numpy_1707225380409/work/dist/numpy-1.26.4-cp310-cp310-linux_x86_64.whl#sha256=51131fd8fc130cd168aecaf1bc0ea85f92e8ffebf211772ceb16ac2e7f10d7ca
-nvidia-cublas-cu12==12.8.4.1
-nvidia-cuda-cupti-cu12==12.8.90
-nvidia-cuda-nvrtc-cu12==12.8.93
-nvidia-cuda-runtime-cu12==12.8.90
-nvidia-cudnn-cu12==9.10.2.21
-nvidia-cufft-cu12==11.3.3.83
-nvidia-cufile-cu12==1.13.1.3
-nvidia-curand-cu12==10.3.9.90
-nvidia-cusolver-cu12==11.7.3.90
-nvidia-cusparse-cu12==12.5.8.93
-nvidia-cusparselt-cu12==0.7.1
-nvidia-nccl-cu12==2.27.5
-nvidia-nvjitlink-cu12==12.8.93
-nvidia-nvshmem-cu12==3.4.5
-nvidia-nvtx-cu12==12.8.90
 omegaconf==2.3.0
-omniverse-kit==106.5.0.162521
-onnx==1.16.1
-opencv-python==4.11.0.86
-osqp==0.6.7.post3
 packaging @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_packaging_1769093650/work
 pandas @ file:///home/conda/feedstock_root/build_artifacts/pandas_1744430447393/work
-pillow==11.2.1
-pin==2.7.0
-pin-pink==3.1.0
+pillow @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_pillow_1770794002/work
 platformdirs==4.9.4
-pluggy==1.6.0
 ply @ file:///home/conda/feedstock_root/build_artifacts/ply_1733239724146/work
-prettytable==3.3.0
 protobuf==5.29.6
 psutil @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_psutil_1769678154/work
-pyglet==1.5.31
-Pygments==2.19.2
 pyparsing @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_pyparsing_1769003998/work
-pyperclip==1.11.0
 PyQt5==5.15.11
 PyQt5_sip==12.17.0
 PySocks @ file:///home/conda/feedstock_root/build_artifacts/pysocks_1733217236728/work
-pytest==9.0.2
-pytest-mock==3.15.1
 python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_python-dateutil_1751104122/work
-pytransform3d==3.14.4
 pytz @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_pytz_1773679724/work
 PyYAML @ file:///home/conda/feedstock_root/build_artifacts/pyyaml_1770223234623/work
-qdldl==0.1.9.post1
-qpsolvers==4.11.0
-quadprog==0.1.13
 regex==2026.2.28
 requests @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_requests_1766926974/work
 # Editable install with no version control (reveal-vla-bimanual==0.1.0)
 -e /workspace/reveal_vla_bimanual
-s3transfer==0.16.0
 safetensors==0.4.3
 scipy @ file:///home/conda/feedstock_root/build_artifacts/scipy-split_1716470219380/work/dist/scipy-1.13.1-cp310-cp310-linux_x86_64.whl#sha256=a4ff22b6dc27b61196be51695f53f9b0676e7c1bc564872b51fc3c41b79ae80b
 sentry-sdk==2.55.0
@@ -149,7 +60,6 @@ setproctitle==1.3.7
 sip @ file:///home/conda/feedstock_root/build_artifacts/sip_1759437834046/work
 six @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_six_1753199211/work
 smmap==5.0.3
-starlette==0.45.3
 sympy @ file:///home/conda/feedstock_root/build_artifacts/sympy_1771952240620/work
 tensorboard==2.16.2
 tensorboard-data-server==0.7.2
@@ -157,19 +67,17 @@ timm==1.0.7
 tokenizers==0.19.1
 toml @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_toml_1764486833/work
 tomli @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_tomli_1768146676/work
-torch==2.10.0
+torch==2.3.1
 torchaudio==2.3.1
 torchvision==0.18.1
 tornado @ file:///home/conda/feedstock_root/build_artifacts/tornado_1765836373149/work
 tqdm @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_tqdm_1770153424/work
 transformers==4.41.2
 trimesh @ file:///home/conda/feedstock_root/build_artifacts/trimesh_1773883117645/work
-triton==3.6.0
+triton==2.3.1
 typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_typing_extensions_1756220668/work
 tzdata @ file:///home/conda/feedstock_root/build_artifacts/python-tzdata_1765719872007/work
 unicodedata2 @ file:///home/conda/feedstock_root/build_artifacts/unicodedata2_1770908960326/work
 urllib3 @ file:///home/conda/feedstock_root/build_artifacts/urllib3_1767817748113/work
 wandb==0.18.0
-warp-lang==1.12.0
-wcwidth==0.6.0
 Werkzeug==3.1.6

environment/rlbench_env_explicit.txt

@@ -51,8 +51,7 @@ https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/dbus-1.16.2-h24cb091_1.conda
 
 
-
-https://conda.anaconda.org/conda-forge/linux-64/ffmpeg-8.0.1-gpl_hcddb375_914.conda
+https://conda.anaconda.org/conda-forge/linux-64/ffmpeg-8.0.1-gpl_he74fc74_714.conda
 https://conda.anaconda.org/conda-forge/noarch/filelock-3.25.2-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
 https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
@@ -97,9 +96,8 @@ https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.1.0-pyhd8ed1ab_0.cond
 https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda
 https://conda.anaconda.org/conda-forge/noarch/idna-3.11-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/imageio-2.37.0-pyhfb79c49_0.conda
-
 https://conda.anaconda.org/conda-forge/linux-64/intel-gmmlib-22.9.0-hb700be7_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/intel-media-driver-26.1.4-hecca717_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/intel-media-driver-26.1.5-hecca717_0.conda
 https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.6-pyhcf101f3_1.conda
 https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-5.14.0-he073ed8_3.conda
 https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.3-hb9d3cd8_0.conda
@@ -261,7 +259,6 @@ https://conda.anaconda.org/conda-forge/linux-64/pkg-config-0.29.2-h4bc722e_1009.
 https://conda.anaconda.org/conda-forge/noarch/ply-3.11-pyhd8ed1ab_3.conda
 
 
-
 https://conda.anaconda.org/conda-forge/linux-64/psutil-7.2.2-py310h139afa4_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-hb9d3cd8_1002.conda
 https://conda.anaconda.org/conda-forge/linux-64/pugixml-1.15-h3f63f65_0.conda
@@ -276,7 +273,6 @@ https://conda.anaconda.org/conda-forge/linux-64/pyqt5-sip-12.17.0-py310hea6c23e_
 https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha55dd90_7.conda
 https://conda.anaconda.org/conda-forge/linux-64/python-3.10.20-h3c07f61_0_cpython.conda
 https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.9.0.post0-pyhe01879c_2.conda
-
 https://conda.anaconda.org/conda-forge/noarch/python-tzdata-2025.3-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/python_abi-3.10-8_cp310.conda
 https://conda.anaconda.org/pytorch/linux-64/pytorch-2.3.1-py3.10_cuda12.1_cudnn8.9.2_0.tar.bz2

environment/rlbench_env_export.yaml

@@ -40,7 +40,7 @@ dependencies:
   - cyrus-sasl=2.1.28=hac629b4_1
   - dav1d=1.2.1=hd590300_0
   - dbus=1.16.2=h24cb091_1
-  - ffmpeg=8.0.1=gpl_hcddb375_914
+  - ffmpeg=8.0.1=gpl_he74fc74_714
   - filelock=3.25.2=pyhd8ed1ab_0
   - font-ttf-dejavu-sans-mono=2.37=hab24e00_0
   - font-ttf-inconsolata=3.000=h77eed37_0
@@ -76,7 +76,7 @@ dependencies:
   - idna=3.11=pyhd8ed1ab_0
   - imageio=2.37.0=pyhfb79c49_0
   - intel-gmmlib=22.9.0=hb700be7_0
-  - intel-media-driver=26.1.4=hecca717_0
+  - intel-media-driver=26.1.5=hecca717_0
   - jinja2=3.1.6=pyhcf101f3_1
   - kernel-headers_linux-64=5.14.0=he073ed8_3
   - keyutils=1.6.3=hb9d3cd8_0
@@ -316,12 +316,10 @@ dependencies:
     - absl-py==2.1.0
     - accelerate==0.31.0
     - antlr4-python3-runtime==4.9.3
-    - cffi==1.17.1
     - click==8.3.1
     - click-prompt==0.5.1
     - clip==1.0
     - cloudpickle==3.1.2
-    - decorator==5.2.1
     - docker-pycreds==0.4.0
     - einops==0.8.0
     - freetype-py==2.5.1
@@ -334,7 +332,6 @@ dependencies:
     - hf-xet==1.4.2
     - huggingface_hub==0.36.2
     - hydra-core==1.3.2
-    - imageio-ffmpeg==0.6.0
     - markdown-it-py==4.0.0
     - mdurl==0.1.2
     - moviepy==2.2.1
@@ -342,21 +339,16 @@ dependencies:
     - numpy==1.26.4
     - omegaconf==2.3.0
     - opencv-python==4.10.0.84
-    - pandas==2.2.3
     - peract_bimanual==0.0.1
     - perceiver-pytorch==0.8.8
     - pillow==12.1.1
     - platformdirs==4.9.4
     - poetry-core==2.3.1
-    - proglog==0.1.12
     - protobuf==5.29.6
     - pyglet==2.1.13
     - pyquaternion==0.9.9
     - pyrender==0.1.45
-    - python-dateutil==2.9.0.post0
-    - python-dotenv==1.2.2
     - pytorch-lamb==1.0.0
-    - pytz==2026.1.post1
     - regex==2024.5.15
     - reveal-vla-bimanual==0.1.0
     - rich==13.9.4
@@ -365,7 +357,6 @@ dependencies:
     - safetensors==0.4.3
     - sentry-sdk==2.55.0
     - setproctitle==1.3.7
-    - six==1.17.0
     - smmap==5.0.3
     - tensorboard==2.16.2
     - tensorboard-data-server==0.7.2
@@ -374,7 +365,6 @@ dependencies:
     - timm==1.0.25
     - tokenizers==0.19.1
     - transformers==4.41.2
-    - tzdata==2025.3
     - wandb==0.18.0
     - wcwidth==0.2.14
     - yarr==0.1

environment/rlbench_pip_freeze.txt

@@ -5,7 +5,7 @@ backports.zstd @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-b
 Brotli @ file:///home/conda/feedstock_root/build_artifacts/brotli-split_1764016952863/work
 cached-property @ file:///home/conda/feedstock_root/build_artifacts/cached_property_1615209429212/work
 certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1772001073725/work/certifi
-cffi==1.17.1
+cffi @ file:///home/conda/feedstock_root/build_artifacts/cffi_1761202865726/work
 charset-normalizer @ file:///home/conda/feedstock_root/build_artifacts/charset-normalizer_1773659966602/work
 click==8.3.1
 click-prompt==0.5.1
@@ -13,7 +13,6 @@ clip @ git+https://github.com/openai/CLIP.git@ded190a052fdf4585bd685cee5bc96e031
 cloudpickle==3.1.2
 contourpy @ file:///home/conda/feedstock_root/build_artifacts/contourpy_1744743067588/work
 cycler @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_cycler_1764466758/work
-decorator==5.2.1
 docker-pycreds==0.4.0
 einops==0.8.0
 filelock @ file:///home/conda/feedstock_root/build_artifacts/filelock_1773313889543/work
@@ -36,7 +35,6 @@ hydra-core==1.3.2
 hyperframe @ file:///home/conda/feedstock_root/build_artifacts/hyperframe_1737618333194/work
 idna @ file:///home/conda/feedstock_root/build_artifacts/idna_1760286409563/work
 imageio @ file:///home/conda/feedstock_root/build_artifacts/imageio_1738273805233/work
-imageio-ffmpeg==0.6.0
 Jinja2 @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_jinja2_1764517220/work
 kiwisolver @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_kiwisolver_1773067043/work
 Markdown==3.10.2
@@ -53,14 +51,13 @@ numpy==1.26.4
 omegaconf==2.3.0
 opencv-python==4.10.0.84
 packaging @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_packaging_1769093650/work
-pandas==2.2.3
+pandas @ file:///home/conda/feedstock_root/build_artifacts/pandas_1744430447393/work
 -e git+https://github.com/markusgrotz/peract_bimanual.git@bb0232a6ba3fe116566e9568f0c7af980ed6703d#egg=peract_bimanual
 perceiver-pytorch==0.8.8
 pillow==12.1.1
 platformdirs==4.9.4
 ply @ file:///home/conda/feedstock_root/build_artifacts/ply_1733239724146/work
 poetry-core==2.3.1
-proglog==0.1.12
 protobuf==5.29.6
 psutil @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_psutil_1769678154/work
 pycparser @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_pycparser_1733195786/work
@@ -74,10 +71,9 @@ pyquaternion==0.9.9
 pyrender==0.1.45
 -e git+https://github.com/markusgrotz/PyRep.git@b8bd1d7a3182adcd570d001649c0849047ebf197#egg=PyRep
 PySocks @ file:///home/conda/feedstock_root/build_artifacts/pysocks_1733217236728/work
-python-dateutil==2.9.0.post0
-python-dotenv==1.2.2
+python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_python-dateutil_1751104122/work
 pytorch-lamb==1.0.0
-pytz==2026.1.post1
+pytz @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_pytz_1773679724/work
 PyYAML @ file:///home/conda/feedstock_root/build_artifacts/pyyaml_1770223234623/work
 regex==2024.5.15
 requests @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_requests_1766926974/work
@@ -91,7 +87,7 @@ scipy @ file:///home/conda/feedstock_root/build_artifacts/scipy-split_1716470219
 sentry-sdk==2.55.0
 setproctitle==1.3.7
 sip @ file:///home/conda/feedstock_root/build_artifacts/sip_1759437834046/work
-six==1.17.0
+six @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_six_1753199211/work
 smmap==5.0.3
 sympy @ file:///home/conda/feedstock_root/build_artifacts/sympy_1771952240620/work
 tensorboard==2.16.2
@@ -111,7 +107,7 @@ transformers==4.41.2
 trimesh @ file:///home/conda/feedstock_root/build_artifacts/trimesh_1773883117645/work
 triton==2.3.1
 typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_typing_extensions_1756220668/work
-tzdata==2025.3
+tzdata @ file:///home/conda/feedstock_root/build_artifacts/python-tzdata_1765719872007/work
 unicodedata2 @ file:///home/conda/feedstock_root/build_artifacts/unicodedata2_1770908960326/work
 urllib3 @ file:///home/conda/feedstock_root/build_artifacts/urllib3_1767817748113/work
 wandb==0.18.0

environment/setup_same_machine.sh

@@ -2,24 +2,65 @@
 set -euo pipefail
 
 ROOT_DIR="${ROOT_DIR:-/workspace}"
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+BUNDLE_ROOT="$(cd "${SCRIPT_DIR}/.." && pwd)"
+BUNDLED_PROJECT_DIR="${BUNDLE_ROOT}/code/reveal_vla_bimanual"
 PROJECT_DIR="${PROJECT_DIR:-${ROOT_DIR}/reveal_vla_bimanual}"
+THIRD_PARTY_DIR="${ROOT_DIR}/third_party"
+INSTALL_ENV_B="${INSTALL_ENV_B:-1}"
 
 echo "Using ROOT_DIR=${ROOT_DIR}"
+echo "Using BUNDLE_ROOT=${BUNDLE_ROOT}"
+echo "Using BUNDLED_PROJECT_DIR=${BUNDLED_PROJECT_DIR}"
 echo "Using PROJECT_DIR=${PROJECT_DIR}"
 
-echo "1/5 Install or update Env A (RLBench / PerAct2)"
-"${PROJECT_DIR}/scripts/setup_env_a_rlbench.sh"
+ensure_project_dir() {
+  if [[ -e "${PROJECT_DIR}" ]]; then
+    return 0
+  fi
+  ln -s "${BUNDLED_PROJECT_DIR}" "${PROJECT_DIR}"
+}
 
-echo "2/5 Install RLBench headless X prerequisites"
-"${PROJECT_DIR}/scripts/setup_rlbench_headless_x.sh"
+sync_repo() {
+  local target_dir="$1"
+  local repo_url="$2"
+  local repo_rev="$3"
 
-echo "3/5 Start RLBench X server on :99"
-"${PROJECT_DIR}/scripts/start_rlbench_x.sh"
+  if [[ ! -d "${target_dir}/.git" ]]; then
+    git clone "${repo_url}" "${target_dir}"
+  fi
 
-echo "4/5 Install or update Env B base (reveal / IsaacLab source)"
-"${PROJECT_DIR}/scripts/setup_env_b_reveal.sh"
+  git -C "${target_dir}" fetch --all --tags
+  git -C "${target_dir}" checkout "${repo_rev}"
+}
 
-echo "5/5 Done"
+chmod +x "${BUNDLED_PROJECT_DIR}/scripts/"*.sh
+mkdir -p "${THIRD_PARTY_DIR}"
+ensure_project_dir
+
+echo "1/6 Sync pinned third-party repos"
+sync_repo "${THIRD_PARTY_DIR}/peract_bimanual" "https://github.com/markusgrotz/peract_bimanual.git" "bb0232a6ba3fe116566e9568f0c7af980ed6703d"
+sync_repo "${THIRD_PARTY_DIR}/RLBench" "https://github.com/markusgrotz/RLBench.git" "8af748c51287989294e00c9c670e3330a0e35ed5"
+sync_repo "${THIRD_PARTY_DIR}/PyRep" "https://github.com/markusgrotz/PyRep.git" "b8bd1d7a3182adcd570d001649c0849047ebf197"
+sync_repo "${THIRD_PARTY_DIR}/YARR" "https://github.com/markusgrotz/YARR.git" "6822ff78602c77878b27d4cfe759ce029c67bffb"
+
+echo "2/6 Install or update Env A (RLBench / PerAct2)"
+ROOT_DIR="${ROOT_DIR}" "${PROJECT_DIR}/scripts/setup_env_a_rlbench.sh"
+
+echo "3/6 Install RLBench headless X prerequisites"
+ROOT_DIR="${ROOT_DIR}" "${PROJECT_DIR}/scripts/setup_rlbench_headless_x.sh"
+
+echo "4/6 Start RLBench X server on :99"
+ROOT_DIR="${ROOT_DIR}" DISPLAY_NUM=99 "${PROJECT_DIR}/scripts/start_rlbench_x.sh"
+
+if [[ "${INSTALL_ENV_B}" == "1" ]]; then
+  echo "5/6 Install or update Env B base (reveal / IsaacLab source)"
+  ROOT_DIR="${ROOT_DIR}" "${PROJECT_DIR}/scripts/setup_env_b_reveal.sh"
+else
+  echo "5/6 Skip Env B base because INSTALL_ENV_B=${INSTALL_ENV_B}"
+fi
+
+echo "6/6 Done"
 echo
 echo "Optional next step for full Isaac Sim pip install:"
 echo "  INSTALL_ISAACSIM=1 ${PROJECT_DIR}/scripts/setup_env_b_reveal.sh"

environment/upstream_revisions.txt

@@ -0,0 +1,15 @@
+/workspace/third_party/peract_bimanual
+repo_url=https://github.com/markusgrotz/peract_bimanual.git
+commit=bb0232a6ba3fe116566e9568f0c7af980ed6703d
+
+/workspace/third_party/RLBench
+repo_url=https://github.com/markusgrotz/RLBench.git
+commit=8af748c51287989294e00c9c670e3330a0e35ed5
+
+/workspace/third_party/PyRep
+repo_url=https://github.com/markusgrotz/PyRep.git
+commit=b8bd1d7a3182adcd570d001649c0849047ebf197
+
+/workspace/third_party/YARR
+repo_url=https://github.com/markusgrotz/YARR.git
+commit=6822ff78602c77878b27d4cfe759ce029c67bffb

export_manifest_data.json

@@ -1,985 +1,671 @@
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