Sync code and iter4 metric validation artifacts

README.md

@@ -8,175 +8,199 @@ tags:
 
 # VLAdaptorBench
 
-This repository contains the first-pass benchmark setup, metric code, debug history, and single-episode label-validation artifacts for the proposed VLA + adaptor study on `bimanual_take_tray_out_of_oven`.
+This repository contains the benchmark setup, metric code, debug history, and validation artifacts for the proposed VLA + adaptor label study on `bimanual_take_tray_out_of_oven`.
 
-This pass is a label study, not a policy study. No `pi0.5` integration is included here.
+This is still a label-validation repository, not a policy repository. No `pi0.5` integration is included here.
 
-## What is in this upload
+## Current Status
+
+The latest work in this upload fixes the three main oven-metric failures that were still present in the earlier `oven_episode0_repaired_v1` bundle:
+
+1. The reveal-to-retrieve transition used to occur too late, effectively at grasp time.
+2. The visibility metric used to drop to zero around frame 232 even when the tray grasp region was clearly visible in `wrist_left`.
+3. `p_pre` stayed near zero until grasp, and some late-frame repair runs produced corrupted rows because they replayed each frame from scratch in a separate process.
+
+The current code addresses those issues by:
+
+- decoding RLBench mask PNGs correctly before converting them back to simulator handles
+- scoring visibility directly from mask-handle agreement instead of the old depth/z heuristic
+- inferring tray mask handles from grasp-region projections
+- deriving a late-window pregrasp approach template instead of accidentally including frame-8 arm poses
+- adding explicit `pregrasp_progress`, `pregrasp_distance`, `pregrasp_speed`, and `phase_score`
+- making the repair path batch frames sequentially per worker so late-frame rows do not drift
+
+The latest validated artifacts are the `iter4_*` outputs, not `oven_episode0_repaired_v1`.
+
+## What Is In This Upload
 
-- `external/`
-  - Full local benchmark snapshots copied from the RunPod workspace.
-  - `external/rlbench/`: local RLBench tree used for this run.
-  - `external/pyrep/`: local PyRep tree used for this run.
-  - `external/peract_bimanual/`: local PerAct bimanual tree used for context.
-  - `external/yarr/`: local YARR tree used for context.
 - `code/rr_label_study/`
-  - Core study code, including dense replay, visibility metrics, pregrasp/extraction oracles, keyframe extraction, intervention checks, and summary metric computation.
+  - Core metric code.
+  - Dense replay, visibility scoring, pregrasp/extraction oracles, keyframe extraction, intervention checks, and summary metric computation.
 - `code/scripts/`
-  - Study runners and helper scripts.
-  - `run_oven_label_study.py`: main dense/keyframe study runner.
+  - Study runners and helpers.
+  - `run_oven_label_study.py`: dense/keyframe study runner.
   - `launch_parallel_oven_label_study.py`: multi-display worker launcher.
-  - `run_oven_single_frame.py`: isolated single-frame recomputation helper.
-  - `repair_oven_episode_dense.py`: external repair pass for corrupted dense frames.
-  - `render_oven_metric_frame.py`: renders per-frame visibility/path/all-metric overlays.
-  - `render_oven_metric_gifs.py`: parallel multi-display GIF renderer for the final visual diagnostics.
+  - `run_oven_single_frame.py`: single-frame recomputation helper.
+  - `run_oven_frame_batch.py`: new sequential batch recomputation helper used to avoid late-frame drift.
+  - `repair_oven_episode_dense.py`: batched repair pass for suspicious dense rows.
+  - `render_oven_metric_frame.py`: per-frame visualization renderer.
+  - `render_oven_metric_gifs.py`: GIF renderer.
 - `artifacts/results/`
-  - All result directories produced during debugging and validation.
-  - This includes failed/stale runs, partial runs, smoke runs, the first independent run, and the final repaired run.
-  - The final repaired run also includes full visualization artifacts and single-frame smoke-check images.
+  - Full debug history, including stale runs and current validation outputs.
 - `environment/`
-  - Machine snapshot, conda env export, pip freeze, upstream repo revisions, runtime activation helper, setup helper, and dataset notes.
+  - Machine snapshot, env export, pip freeze, setup helpers, and dataset notes.
+- `external/`
+  - Local source snapshots of RLBench, PyRep, PerAct bimanual, and YARR used for this work.
 - `MANIFEST.txt`
-  - Flat file listing of the uploaded bundle contents.
-
-## Repository map
-
-Relevant entry points and where to look:
-
-- Benchmark snapshots
-  - `external/README.md`
-  - `external/rlbench/README.md`
-  - `external/rlbench/rlbench/bimanual_tasks/`
-  - `external/rlbench/rlbench/action_modes/`
-  - `external/pyrep/README.md`
-  - `external/pyrep/pyrep/`
-  - `external/peract_bimanual/`
-  - `external/yarr/`
-- Study code
-  - `code/rr_label_study/oven_study.py`
-  - `code/scripts/run_oven_label_study.py`
-  - `code/scripts/launch_parallel_oven_label_study.py`
-  - `code/scripts/run_oven_single_frame.py`
-  - `code/scripts/repair_oven_episode_dense.py`
-  - `code/scripts/render_oven_metric_frame.py`
-  - `code/scripts/render_oven_metric_gifs.py`
-- Final clean artifact
-  - `artifacts/results/oven_episode0_repaired_v1/episode0.dense.csv`
-  - `artifacts/results/oven_episode0_repaired_v1/episode0.keyframes.csv`
-  - `artifacts/results/oven_episode0_repaired_v1/episode0.metrics.json`
-  - `artifacts/results/oven_episode0_repaired_v1/summary.json`
-  - `artifacts/results/oven_episode0_repaired_v1/visualizations/episode0_visibility_focus.gif`
-  - `artifacts/results/oven_episode0_repaired_v1/visualizations/episode0_path_quality_focus.gif`
-  - `artifacts/results/oven_episode0_repaired_v1/visualizations/episode0_all_metrics.gif`
-  - `artifacts/results/oven_episode0_repaired_v1/visualizations/README.md`
-  - `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/visibility_0232.png`
-  - `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/visibility_0240.png`
-  - `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/path_0232.png`
-  - `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/path_0240.png`
-  - `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/all_0232.png`
-  - `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/all_0240.png`
-- Intermediate/debug artifacts
-  - `artifacts/results/oven_episode0_full*/`
-  - `artifacts/results/oven_to240_*/`
-  - `artifacts/results/oven_episode0_independent_v1/`
-  - `artifacts/results/parallel_smoke_2x10/`
-- Environment/repro
-  - `environment/system_info.txt`
-  - `environment/repo_revisions.txt`
-  - `environment/conda_env_rlbench.yml`
-  - `environment/pip_freeze_rlbench.txt`
-  - `environment/setup_same_hardware.sh`
-  - `environment/activate_rlbench_runtime.sh`
-  - `environment/dataset_notes.txt`
-
-## Final validated artifact
-
-The clean single-episode artifact is:
-
-- `artifacts/results/oven_episode0_repaired_v1/episode0.dense.csv`
-- `artifacts/results/oven_episode0_repaired_v1/episode0.keyframes.csv`
-- `artifacts/results/oven_episode0_repaired_v1/episode0.metrics.json`
-- `artifacts/results/oven_episode0_repaired_v1/summary.json`
-
-The visual verification artifacts for that same run are:
-
-- `artifacts/results/oven_episode0_repaired_v1/visualizations/episode0_visibility_focus.gif`
-- `artifacts/results/oven_episode0_repaired_v1/visualizations/episode0_path_quality_focus.gif`
-- `artifacts/results/oven_episode0_repaired_v1/visualizations/episode0_all_metrics.gif`
-- `artifacts/results/oven_episode0_repaired_v1/visualizations/README.md`
-- `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/visibility_0232.png`
-- `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/visibility_0240.png`
-- `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/path_0232.png`
-- `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/path_0240.png`
-- `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/all_0232.png`
-- `artifacts/results/oven_episode0_repaired_v1/visualizations_smoke/all_0240.png`
-
-Key numbers from `oven_episode0_repaired_v1`:
-
-- `phase_switch_rises = 1`
-- `phase_switch_falls = 0`
-- `ppre_cross_frame = 232`
-- `pext_cross_frame = 232`
-- `ready_cross_frame = 234`
-- `phase_cross_frame = 236`
-- `dense_boundary_error_frames = 2`
-- `key_boundary_error_keyframes = 1`
-- `auroc_ppre_ypre = 1.0`
-- `auprc_ppre_ypre = 1.0`
-- `auroc_pext_yext = 1.0`
-- `auprc_pext_yext = 1.0`
-- `auroc_phase_yready = 0.9895`
-- `auprc_phase_yready = 0.9850`
-- `f1_phase_yready = 0.9894`
-- Interventions:
-  - pre-ready `open_more` raises `p_ext` in `2/2`
-  - pre-ready extract succeeds in `0/2`
-  - post-ready extract succeeds in `2/2`
-  - post-ready extra reveal has low gain in `2/2`
-
-## What was done
-
-The work in this bundle is the full benchmark/metric debugging path, including intermediate failures:
-
-1. Built dense replay and label-generation scaffolding around RLBench/PerAct-style demos.
-2. Verified the local RLBench fork was not actuating discrete grippers correctly through `BimanualJointPositionActionMode`.
-3. Patched replay to explicitly apply bimanual discrete gripper state from demonstrations.
-4. Fixed visibility scoring so it does not depend on stale simulator object handles in stored mask images.
-5. Reworked snapshot restoration to bypass RLBench task-state restore issues after grasp events.
-6. Tightened template extraction and extraction scoring for already-grasped/already-extracted states.
-7. Added independent replay evaluation for dense label validation.
-8. Identified remaining corrupted dense frames caused by repeated replay/restore contamination inside one simulator process.
-9. Added an external isolated-frame repair pass and used it to produce the clean `oven_episode0_repaired_v1` artifact.
-10. Added visualization renderers and produced GIF/still overlays to inspect visibility, path quality, and phase switching directly against the episode camera feeds.
-
-The result directories preserve this whole path. They are intentionally not pruned.
-
-## Result directory guide
-
-- `oven_smoke_1`, `oven_smoke_30`, `oven_smoke_30_fast`
-  - Early smoke tests.
-- `oven_episode0_full*`
-  - Early full-episode dense runs before the replay/visibility/oracle fixes converged.
-- `oven_to240_*`
-  - Shorter targeted runs used while debugging replay, snapshots, and late-phase drift.
-- `oven_episode0_independent_v1`
-  - First successful independent dense pass. Core metrics were already strong, but the dense CSV still had stale corrupted rows.
-- `oven_episode0_repaired_v1`
-  - Final cleaned artifact after isolated-frame recomputation.
-  - Includes `visualizations/` with full GIF diagnostics and `visualizations_smoke/` with targeted still-image checks around the reveal to retrieve boundary.
-- `parallel_smoke_2x10`
-  - Worker/Xvfb parallelization smoke test.
+  - Flat file listing of the upload contents.
+
+## Latest Metric Fixes
+
+The latest code changes are in:
+
+- `code/rr_label_study/oven_study.py`
+- `code/scripts/repair_oven_episode_dense.py`
+- `code/scripts/run_oven_frame_batch.py`
+- `code/scripts/render_oven_metric_frame.py`
+
+The important changes are:
+
+### 1. Visibility metric repair
+
+- `_load_mask()` now rescales stored mask PNGs back to `[0, 1]` before calling `rgb_handles_to_mask`.
+- Visibility is now computed by projecting grasp-region or whole-tray points into each camera and checking whether the decoded mask handle at the projected pixel matches the inferred tray handles.
+- Template derivation now infers `mask_handle_ids` from reference frames near the actual pregrasp/grasp window.
+
+This fixes the old failure where visibility dropped to zero even when the tray lip was visibly present in the wrist camera.
+
+### 2. Pregrasp/path metric repair
+
+- Template extraction now detects the pregrasp approach onset in a bounded late window before grasp instead of taking the first small negative slope in the entire episode.
+- The current template approach frames for episode 0 are now:
+  - `177, 187, 197, 208, 218, 229, 232`
+- `p_pre` now uses the last few approach templates plus explicit geometric progress toward the pregrasp pose instead of only brittle planner success.
+- `y_pre` now treats "already inside the pregrasp corridor" as success, which is appropriate for this oracle study.
+
+### 3. Replay/repair correctness
+
+- The old isolated repair path replayed every suspicious frame from a fresh reset, which could corrupt late rows.
+- The new helper `run_oven_frame_batch.py` computes frame rows sequentially inside a single env per worker.
+- `repair_oven_episode_dense.py` now distributes frame batches, not individual frames, across displays.
+
+This specifically fixed the bad frame-232 drift that reappeared in the old isolated-per-frame repair path even after the visibility formula was corrected.
+
+### 4. Earlier phase signal
+
+- The code now records:
+  - `pregrasp_progress`
+  - `pregrasp_distance`
+  - `pregrasp_speed`
+  - `phase_score`
+- `phase_switch` is now driven from a persistent threshold on `phase_score` instead of only `p_pre >= tau`.
+- `y_retrieve` is still oracle-like and monotone, but the metric side now has a smoother approach-sensitive signal for early switching.
+
+## Latest Validated Artifacts
+
+The current trustworthy artifacts are:
+
+- `artifacts/results/oven_episode0_iter4_templates/templates.json`
+- `artifacts/results/oven_episode0_iter4_templates/templates.pkl`
+- `artifacts/results/oven_episode0_iter4_batch/iter4_batch_comparison.csv`
+- `artifacts/results/oven_episode0_iter4_batch/frames/`
+- `artifacts/results/oven_episode0_iter4_clean/iter4_targeted_comparison.csv`
+- `artifacts/results/oven_episode0_iter4_dense_geom_170_234.csv`
+
+These artifacts are the main evidence for the latest fixes.
+
+## Key Verified Findings
+
+From the latest iter4 validation on episode 0:
+
+- Visibility over the dense 170-234 window is clean:
+  - min `three_view_visibility = 1.0`
+  - min `full_view_visibility = 1.0`
+- Frame 232 is now correct in sequential replay:
+  - `three_view_visibility = 1.0`
+  - `full_view_visibility = 1.0`
+  - `pregrasp_progress = 0.8946`
+- Pregrasp progress now rises well before grasp:
+  - first `pregrasp_speed >= 0.01` at frame `178`
+  - first `pregrasp_progress >= 0.05` at frame `189`
+  - first `pregrasp_progress >= 0.25` at frame `200`
+  - first `pregrasp_progress >= 0.50` at frame `213`
+- `p_pre` now rises before grasp instead of staying at zero:
+  - frame `190`: `0.044`
+  - frame `210`: `0.185`
+  - frame `215`: `0.373`
+  - frame `220`: `0.497`
+  - frame `232`: `0.666`
+- The old artifact had `three_view_visibility = 0.0` and `p_pre = 0.0` at the same frames.
+- `p_ext` is no longer spuriously high before grasp in the corrected batch replay:
+  - pregrasp region stays at `0.2`
+  - rises at grasp / early extract
+  - reaches `0.8846` by frame `260`
+  - reaches `1.0` by frames `321` and `326`
+
+See:
+
+- `artifacts/results/oven_episode0_iter4_batch/iter4_batch_comparison.csv`
+- `artifacts/results/oven_episode0_iter4_dense_geom_170_234.csv`
+
+## Artifact Guide
+
+### Current artifacts
+
+- `oven_episode0_iter3_templates/`
+  - First regenerated template bundle after the mask/approach fixes.
+- `oven_episode0_iter4_templates/`
+  - Current template bundle with the corrected late-window approach onset.
+- `oven_episode0_iter4_clean/`
+  - Isolated targeted frame checks used while diagnosing the old per-frame repair drift.
+- `oven_episode0_iter4_batch/`
+  - Current batched sequential repair validation.
+- `oven_episode0_iter4_dense_geom_170_234.csv`
+  - Dense sequential geometry and visibility sweep across the reveal-to-retrieve boundary.
+
+### Historical artifacts
+
+- `oven_episode0_repaired_v1/`
+  - Useful historical reference, but not the current authoritative artifact.
+  - It still contains the old late transition and old visibility/path issues.
+- `oven_episode0_full*/`, `oven_to240_*/`, `oven_episode0_independent_v*/`
+  - Debugging history from earlier iterations.
+- `parallel_smoke_2x10/`
+  - Xvfb/worker parallelization smoke test.
+- `oven_smoke_*`
+  - Early smoke runs.
+
+## Repository Map
+
+Relevant entry points:
+
+- `code/rr_label_study/oven_study.py`
+- `code/scripts/run_oven_label_study.py`
+- `code/scripts/launch_parallel_oven_label_study.py`
+- `code/scripts/run_oven_single_frame.py`
+- `code/scripts/run_oven_frame_batch.py`
+- `code/scripts/repair_oven_episode_dense.py`
+- `code/scripts/render_oven_metric_frame.py`
+- `code/scripts/render_oven_metric_gifs.py`
+
+Relevant current artifacts:
+
+- `artifacts/results/oven_episode0_iter4_templates/templates.json`
+- `artifacts/results/oven_episode0_iter4_batch/iter4_batch_comparison.csv`
+- `artifacts/results/oven_episode0_iter4_dense_geom_170_234.csv`
 
 ## Environment
 
-The run used:
+This was run on:
 
 - Ubuntu `22.04.5`
 - Kernel `6.8.0-65-generic`
 - `96` CPU cores visible
 - `503 GiB` RAM visible
-- `NVIDIA A40` with driver `570.195.03`
-- CUDA reported by `nvidia-smi`: `12.8`
+- `NVIDIA A40`
 
 See:
 
@@ -185,24 +209,24 @@ See:
 - `environment/conda_env_rlbench.yml`
 - `environment/pip_freeze_rlbench.txt`
 
-## Upstream repos used
+## Upstream Repos Used
 
-Exact upstream revisions are recorded in `environment/repo_revisions.txt`.
+Exact revisions are recorded in `environment/repo_revisions.txt`.
 
 The local run used:
 
-- `markusgrotz/RLBench` at `8af748c51287989294e00c9c670e3330a0e35ed5`
-- `markusgrotz/PyRep` at `b8bd1d7a3182adcd570d001649c0849047ebf197`
-- `markusgrotz/peract_bimanual` at `bb0232a6ba3fe116566e9568f0c7af980ed6703d`
-- `markusgrotz/YARR` at `6822ff78602c77878b27d4cfe759ce029c67bffb`
+- `markusgrotz/RLBench`
+- `markusgrotz/PyRep`
+- `markusgrotz/peract_bimanual`
+- `markusgrotz/YARR`
 
-Those exact local source snapshots are also included under `external/`.
+Those source snapshots are included under `external/`.
 
-## Reproducing on the same hardware class
+## Reproducing On The Same Hardware Class
 
 1. Read `environment/dataset_notes.txt`.
 2. Run `environment/setup_same_hardware.sh /workspace`.
-   3. Source `environment/activate_rlbench_runtime.sh /workspace`.
+3. Source `environment/activate_rlbench_runtime.sh /workspace`.
 4. Run the dense study:
 
 ```bash
@@ -211,11 +235,10 @@ python /workspace/VLAdaptorBench_upload/code/scripts/run_oven_label_study.py \
   --result-dir /workspace/tmp_run \
   --max-episodes 1 \
   --checkpoint-stride 16 \
-  --template-episode-index 0 \
-  --independent-replay
+  --template-episode-index 0
 ```
 
-5. If the dense CSV shows the known replay contamination pattern, run the external repair pass:
+5. If you want to repair suspicious frames in parallel with the new batched path:
 
 ```bash
 python /workspace/VLAdaptorBench_upload/code/scripts/repair_oven_episode_dense.py \
@@ -225,18 +248,15 @@ python /workspace/VLAdaptorBench_upload/code/scripts/repair_oven_episode_dense.p
   --output-dir /workspace/tmp_run_repaired \
   --checkpoint-stride 16 \
   --num-workers 4 \
-  --base-display 170 \
-  --template-episode-dir /workspace/data/bimanual_take_tray_out_of_oven_train_128/all_variations/episodes/episode0
+  --base-display 170
 ```
 
-## Important note about baselines
-
-On a single deterministic episode, normalized time can become a degenerate perfect predictor for `y_ext`. That is an artifact of single-episode evaluation, not evidence that time is a useful control signal. The cleaned artifact here should be treated as a validated single-episode label trace, not as a multi-episode benchmark conclusion.
+## Important Note
 
-## Dataset note
+The full 100-episode run is not yet the authoritative artifact in this upload. The current repository state documents the repaired metric code and the targeted validation work that was necessary before scaling to the full study.
 
-The upstream RLBench demonstration dataset itself is not re-uploaded in this bundle. This repo contains the study code and all artifacts generated from the local run. The expected dataset path is documented in `environment/dataset_notes.txt`.
+## Dataset Note
 
-The cloned benchmark code is included directly in this upload under `external/`.
+The RLBench demonstration dataset itself is not re-uploaded here. This repository contains the study code and generated artifacts only. The expected dataset path is documented in `environment/dataset_notes.txt`.
 
-CoppeliaSim binaries are not included in this repo. The setup helpers expect a local extraction at `/workspace/coppelia_sim`.
+CoppeliaSim binaries are not included. The setup helpers expect a local extraction at `/workspace/coppelia_sim`.

artifacts/results/oven_episode0_iter2/templates.json

@@ -0,0 +1,244 @@
+{
+  "templates": {
+    "approach_rel_poses": [
+      [
+        -0.36284447577179757,
+        0.08341954953162961,
+        0.13926937907313985,
+        0.6412600192919022,
+        0.6409827527870906,
+        0.29862535693182624,
+        0.29790870159257216
+      ],
+      [
+        -0.3339562037728317,
+        0.08597817122949926,
+        0.123829399129612,
+        0.6302099047870953,
+        0.6302273583819168,
+        0.32117103361854643,
+        0.3201532755096935
+      ],
+      [
+        -0.2872891338932384,
+        0.08984092640927242,
+        0.10034728162541895,
+        0.6105241991318046,
+        0.6103672514966187,
+        0.3572664406820997,
+        0.3564725949316099
+      ],
+      [
+        -0.23904203338976665,
+        0.08899223486806208,
+        0.07178204634811691,
+        0.5937699233857425,
+        0.5843451603769391,
+        0.384677856075976,
+        0.39749334418494287
+      ],
+      [
+        -0.19046952226959657,
+        0.09786257186209256,
+        0.05094144694703484,
+        0.5634784389989876,
+        0.5630020605347386,
+        0.4276660048685565,
+        0.4273435583891148
+      ],
+      [
+        -0.14928672873242044,
+        0.10114962823170283,
+        0.030087029366532292,
+        0.541168186249708,
+        0.5403455150507429,
+        0.4554541645184262,
+        0.4557688258081848
+      ],
+      [
+        -0.12217129631756263,
+        0.09345070134195246,
+        -0.006546997831216039,
+        0.5503450945485194,
+        0.5264249147312487,
+        0.4450459711257041,
+        0.47109571176286236
+      ],
+      [
+        -0.11121477625092058,
+        0.0896385488954243,
+        -0.030442970753480347,
+        0.5622227243916537,
+        0.5225037729406623,
+        0.43290100712281304,
+        0.47274954624246207
+      ]
+    ],
+    "pregrasp_rel_pose": [
+      -0.12217129631756263,
+      0.09345070134195246,
+      -0.006546997831216039,
+      0.5503450945485194,
+      0.5264249147312487,
+      0.4450459711257041,
+      0.47109571176286236
+    ],
+    "grasp_rel_pose": [
+      -0.09865615619553114,
+      0.09471180553609355,
+      -0.023587008474192483,
+      0.5452601219922814,
+      0.5150377871073674,
+      0.45379910210390734,
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artifacts/results/oven_episode0_iter2_clean/frames/frame_170.json

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artifacts/results/oven_episode0_iter2_clean/frames/frame_178.json

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artifacts/results/oven_episode0_iter2_clean/frames/frame_190.json

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artifacts/results/oven_episode0_iter2_clean/frames/frame_200.json

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artifacts/results/oven_episode0_iter2_clean/frames/frame_220.json

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artifacts/results/oven_episode0_iter2_clean/frames/frame_232.json

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artifacts/results/oven_episode0_iter2_clean/frames/frame_234.json

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artifacts/results/oven_episode0_iter2_clean/frames/frame_260.json

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artifacts/results/oven_episode0_iter2_clean/frames/frame_321.json

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artifacts/results/oven_episode0_iter2_clean/frames/frame_326.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_170.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_175.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_178.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_180.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_185.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_190.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_200.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_210.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_220.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_225.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_228.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_230.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_232.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_234.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_236.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_240.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_260.json

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artifacts/results/oven_episode0_iter2_parallel/frames/frame_280.json

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