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Publish formal task-transfer and joint-training archive catalogue

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Files changed (29) hide show
  1. README.md +1 -0
  2. archive/task-transfer/README.md +5 -0
  3. archive/task-transfer/manifest.json +693 -0
  4. experiments/task-transfer/README.md +8 -0
  5. experiments/task-transfer/demon-attack/README.md +11 -0
  6. experiments/task-transfer/demon-attack/manifest.json +190 -0
  7. experiments/task-transfer/demon-attack/paper_comparison.json +386 -0
  8. experiments/task-transfer/paper/README.md +36 -0
  9. experiments/task-transfer/paper/data.csv +13 -0
  10. experiments/task-transfer/paper/fig_caption.tex +7 -0
  11. experiments/task-transfer/paper/plot.py +107 -0
  12. experiments/task-transfer/provenance/asset_identity_verification.json +1766 -0
  13. experiments/task-transfer/provenance/code/manifest.json +22 -0
  14. experiments/task-transfer/provenance/code/starvla-4106a99b03c427d9607a12857c04d82a58140c8f.tar.gz +3 -0
  15. experiments/task-transfer/provenance/code/starvla-fdbb7b46345e4bdd646af277e69d9aab8472c6f8.tar.gz +3 -0
  16. experiments/task-transfer/provenance/copy_manifest.json +0 -0
  17. experiments/task-transfer/provenance/numeric_verification.json +632 -0
  18. experiments/task-transfer/provenance/paper_numeric_comparison.json +386 -0
  19. experiments/task-transfer/provenance/repositories/latency-sensitive-bench--asterix_200ep.json +79 -0
  20. experiments/task-transfer/provenance/repositories/latency-sensitive-bench--atlantis_200ep.json +109 -0
  21. experiments/task-transfer/provenance/repositories/latency-sensitive-bench--deadly_1000ep.json +179 -0
  22. experiments/task-transfer/provenance/repositories/latency-sensitive-bench--defend_the_line_200ep.json +125 -0
  23. experiments/task-transfer/provenance/repositories/latency-sensitive-bench--memory-rollouts.json +0 -0
  24. experiments/task-transfer/provenance/repositories/latency-sensitive-bench--openvla_bridge_cross_defendtheline_zero_deadly_zero_exp3.json +77 -0
  25. experiments/task-transfer/provenance/repositories/latency-sensitive-bench--openvla_bridge_cross_mixed_all_024_5env200ep_deadly1000ep_exp1.json +277 -0
  26. experiments/task-transfer/provenance/repositories/latency-sensitive-bench--starvla-demon-attack-mixed-024-latency-evals.json +757 -0
  27. experiments/task-transfer/provenance/repositories/latency-sensitive-bench--starvla-demon-attack-zero-latency-evals.json +37 -0
  28. experiments/task-transfer/provenance/repositories/talha15032--openvla_bridge_demon_attack_latency_mixed_024_exp1.json +49 -0
  29. experiments/task-transfer/provenance/source_heads.json +12 -0
README.md CHANGED
@@ -3268,6 +3268,7 @@ Training data, episode-level evaluations and paper experiment manifests.
3268
  | Visual history | [Visual history](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/visual-history) |
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  | Latency in prompt | [Latency in prompt](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/latency-in-prompt) |
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  | Latency transfer | [Latency transfer](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/latency-transfer) |
 
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  | VLA fine-tuning scope | [VLA fine-tuning scope](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/vla-finetuning-scope) |
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  | Mean vs. profile training | [Mean vs. profile training](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/mean-vs-profile) |
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  | Observation stride | [Observation stride](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/observation-stride) |
 
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  | Visual history | [Visual history](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/visual-history) |
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  | Latency in prompt | [Latency in prompt](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/latency-in-prompt) |
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  | Latency transfer | [Latency transfer](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/latency-transfer) |
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+ | Task transfer | [Task transfer](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/task-transfer) |
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  | VLA fine-tuning scope | [VLA fine-tuning scope](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/vla-finetuning-scope) |
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  | Mean vs. profile training | [Mean vs. profile training](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/mean-vs-profile) |
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  | Observation stride | [Observation stride](https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets/tree/main/experiments/observation-stride) |
archive/task-transfer/README.md ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
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+ # Archived task-transfer experiments
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+
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+ The archive retains DefendTheLine + Deadly Corridor zero-latency joint training (step 2000) and six-task mixed-latency joint training (step 15000). These experiments are separate from the formal Demon Attack transfer figure.
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+
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+ [`manifest.json`](manifest.json) pins all model, original config, training-state, dataset and evaluation references. The six-task experiment trains on Flappy, Demon Attack, Deadly Corridor, Asterix, Atlantis and DefendTheLine. Earlier mixed-policy evaluation versions preserve their original prompts, horizons and returns.
archive/task-transfer/manifest.json ADDED
@@ -0,0 +1,693 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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experiments/task-transfer/README.md ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ # Task transfer
2
+
3
+ | Release classification | Experiment |
4
+ |---|---|
5
+ | Formal | [Demon Attack training, four-task evaluation](demon-attack/README.md) |
6
+ | Archive | [Joint training and earlier evaluation versions](../../archive/task-transfer/README.md) |
7
+
8
+ Shared checkpoints and datasets have one canonical location in benchmark-models and benchmark-datasets. Fixed references and source limits are in each manifest. Latency profiles use the existing profiles repository.
experiments/task-transfer/demon-attack/README.md ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Demon Attack task transfer
2
+
3
+ Two formal policies train on Demon Attack: zero latency at step 7000 and mixed latency at step 5000. Both evaluate on Demon Attack, Asterix, Atlantis and AirRaid at latency labels 0, 2 and 4, with 20 episodes per condition.
4
+
5
+ [`manifest.json`](manifest.json) pins checkpoints and original evaluation files. [`paper_comparison.json`](paper_comparison.json) contains all 24 recomputed means and the paper values.
6
+
7
+ The corrected mixed evaluation is `demon_attack_mixed_024_horizonfix_full_20261001_002008`. The paper records mixed Demon Attack L0 as 5812; its public evaluation gives 5832.25. Other 23 points agree within integer display rounding. The original plotted CSV remains unchanged.
8
+
9
+ The paper names delays as raw frames. The corrected mixed configuration uses 60 environment FPS and 15 observation FPS: label 4 is 266.67 ms, or 16 raw frames. Original units remain in each source file. Exact checkpoint identity binding to these evaluations remains unverified.
10
+
11
+ The mixed checkpoint lacks its original training configuration, normalization statistics and exact training-data binding. Zero-policy evaluation summaries lack resolved configs and action traces. Missing assets remain explicit.
experiments/task-transfer/demon-attack/manifest.json ADDED
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+ {
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+ "experiment": "task-transfer",
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+ "task": "demon-attack",
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+ "classification": "formal",
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+ "paper_locations": [
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+ "sections/latency_aware_training.tex:Transfer Across Tasks",
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+ "figures/fig21_demon_mixed_cross_task"
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+ ],
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+ "models": [
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+ {
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+ "condition": "zero-latency-trained",
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+ "checkpoint": {
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+ "repo": "latency-sensitive-bench/benchmark-models",
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+ "repo_type": "model",
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+ "revision": "671e2a7451fda7f7dba5606c6d11183ebd804b6d",
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+ "path": "zero-latency/demon-attack/vla/starvla-qwenoft-h1/demon_attack_fix_latency_0_200ep/checkpoints/steps_7000_model.safetensors"
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+ },
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+ "training_step": 7000,
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+ "cross_task_evaluation_binding": "script-specified; evaluation summary lacks a checkpoint digest",
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+ "training_data": []
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+ },
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+ {
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+ "condition": "mixed-latency-trained",
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+ "checkpoint": {
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+ "repo": "latency-sensitive-bench/benchmark-models",
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+ "repo_type": "model",
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+ "revision": "671e2a7451fda7f7dba5606c6d11183ebd804b6d",
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+ "path": "latency-aware/demon-attack/vla/starvla-qwenoft-h1/openvla_bridge_demon_attack_latency_mixed_024_exp1/checkpoints/steps_5000_model.safetensors"
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+ },
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+ "training_step": 5000,
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+ "cross_task_evaluation_binding": "script-specified; corrected evaluation lacks a checkpoint digest",
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+ "training_data": [],
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+ "missing_original_assets": [
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+ "training_configuration",
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+ "normalization_statistics",
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+ "exact_training_dataset_binding"
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+ ]
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+ }
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+ ],
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+ "evaluation": {
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+ "tasks": [
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+ "demon_attack",
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+ "asterix",
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+ "atlantis",
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+ "air_raid"
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+ ],
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+ "latency_labels": [
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+ 0,
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+ 2,
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+ 4
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+ ],
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+ "episodes_per_condition": 20,
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+ "episode_seed_range": [
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+ 42,
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+ 61
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+ ],
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+ "sources": [
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+ {
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "repo_type": "dataset",
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+ "revision": "d6f0ad0995f6e4b095f315920e8de18e04297048",
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+ "path": "evaluations/task-transfer/demon-attack/demon_attack_zero_latency_latency024_cross_games/air_raid/eval/post_train/step_7000.json"
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+ },
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+ {
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "repo_type": "dataset",
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+ "revision": "d6f0ad0995f6e4b095f315920e8de18e04297048",
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+ "path": "evaluations/task-transfer/demon-attack/demon_attack_zero_latency_latency024_cross_games/asterix/eval/post_train/step_7000.json"
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+ },
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+ {
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+ "repo_type": "dataset",
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+ "revision": "d6f0ad0995f6e4b095f315920e8de18e04297048",
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+ "path": "evaluations/task-transfer/demon-attack/demon_attack_zero_latency_latency024_cross_games/atlantis/eval/post_train/step_7000.json"
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+ },
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+ {
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+ "repo_type": "dataset",
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+ "revision": "d6f0ad0995f6e4b095f315920e8de18e04297048",
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+ "path": "evaluations/task-transfer/demon-attack/demon_attack_zero_latency_latency024_cross_games/demon_attack/eval/post_train/step_7000.json"
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+ },
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+ {
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "repo_type": "dataset",
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+ "revision": "d6f0ad0995f6e4b095f315920e8de18e04297048",
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+ "path": "evaluations/task-transfer/demon-attack/demon_attack_mixed_024_horizonfix_full_20261001_002008/air_raid/eval/post_train/step_5000.json"
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+ },
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+ {
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "repo_type": "dataset",
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+ "revision": "d6f0ad0995f6e4b095f315920e8de18e04297048",
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+ "path": "evaluations/task-transfer/demon-attack/demon_attack_mixed_024_horizonfix_full_20261001_002008/asterix/eval/post_train/step_5000.json"
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+ },
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+ {
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "repo_type": "dataset",
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+ "revision": "d6f0ad0995f6e4b095f315920e8de18e04297048",
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+ "path": "evaluations/task-transfer/demon-attack/demon_attack_mixed_024_horizonfix_full_20261001_002008/atlantis/eval/post_train/step_5000.json"
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+ },
100
+ {
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "repo_type": "dataset",
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+ "revision": "d6f0ad0995f6e4b095f315920e8de18e04297048",
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+ "path": "evaluations/task-transfer/demon-attack/demon_attack_mixed_024_horizonfix_full_20261001_002008/demon_attack/eval/post_train/step_5000.json"
105
+ }
106
+ ],
107
+ "mixed_evaluation_run": "demon_attack_mixed_024_horizonfix_full_20261001_002008"
108
+ },
109
+ "source_limits": [
110
+ "Paper Demon Attack mixed L0 value is 5812; the published corrected evaluation recomputes to 5832.25.",
111
+ "Paper calls evaluation delays raw frames. Corrected mixed resolved configs use fixed latency labels: label 4 is 266.6666666666667 ms with env_fps=60 and obs_fps=15, equivalent to 16 raw frames.",
112
+ "Zero-policy source provides summary JSONs; original resolved configs and action traces are absent.",
113
+ "Public source versions preserve distinct prompt and horizon corrections. No rerun replaces the recorded paper values."
114
+ ],
115
+ "historical_evaluations": [
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+ {
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "repo_type": "dataset",
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+ "revision": "d6f0ad0995f6e4b095f315920e8de18e04297048",
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+ "path": "archive/task-transfer/evaluations/demon_attack_mixed_024_latency_cross_games/air_raid/eval/post_train/step_5000.json"
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+ },
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+ {
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "repo_type": "dataset",
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+ "revision": "d6f0ad0995f6e4b095f315920e8de18e04297048",
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+ "path": "archive/task-transfer/evaluations/demon_attack_mixed_024_latency_cross_games/asterix/eval/post_train/step_5000.json"
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+ },
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+ {
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "repo_type": "dataset",
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+ "path": "archive/task-transfer/evaluations/demon_attack_mixed_024_latency_cross_games/atlantis/eval/post_train/step_5000.json"
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+ "path": "archive/task-transfer/evaluations/demon_attack_mixed_024_promptfix_full_20260930_212002/air_raid/eval/post_train/step_5000.json"
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+ },
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+ {
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "repo_type": "dataset",
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+ "path": "archive/task-transfer/evaluations/demon_attack_mixed_024_promptfix_full_20260930_212002/asterix/eval/post_train/step_5000.json"
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "path": "archive/task-transfer/evaluations/demon_attack_mixed_024_promptfix_full_20260930_212002/atlantis/eval/post_train/step_5000.json"
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+ "repo": "latency-sensitive-bench/benchmark-datasets",
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+ "path": "archive/task-transfer/evaluations/demon_attack_mixed_024_promptfix_full_20260930_212002/demon_attack/eval/post_train/step_5000.json"
187
+ }
188
+ ],
189
+ "paper_comparison": "paper_comparison.json"
190
+ }
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experiments/task-transfer/paper/README.md ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Transfer across tasks
2
+
3
+ Figure 7 in Section 4.5 compares two policies trained on Demon Attack: one
4
+ with zero latency and one with mixed latencies. Panels show Demon Attack,
5
+ Asterix, Atlantis, and AirRaid, evaluated at fixed delays of 0, 2, and 4 raw
6
+ frames. Each displayed mean uses 20 evaluation episodes, as documented in
7
+ the manuscript. Returns use each task's native reward scale.
8
+
9
+ `data.csv` is the committed local plotting input. Its columns contain the
10
+ task, evaluation delay, zero-latency-trained mean return, and mixed-latency-trained
11
+ mean return. It does not contain checkpoint identifiers, the mixed-delay
12
+ training distribution, per-episode records, or uncertainty estimates.
13
+
14
+ At four frames, the mixed-latency policy has higher returns on Atlantis
15
+ (5,010 versus 2,000) and AirRaid (178 versus 15), but lower return on Asterix
16
+ (178 versus 212). Asterix has the opposite direction at two frames
17
+ (262 versus 202). Demon Attack is the training-task comparison
18
+ (3,510 versus 96 at four frames).
19
+
20
+ ## Assets and reproduction
21
+
22
+ `fig.pdf` and `fig.png` are the existing vector and 300-DPI raster assets.
23
+ `fig_caption.tex` supplies the manuscript caption; its numbering comes from
24
+ LaTeX. `plot.py` reads only the local CSV and uses the shared
25
+ `plot_style.mplstyle` and `paper_colors.py`: gray denotes zero-latency
26
+ training and purple denotes mixed-latency training.
27
+ The chart uses lines and markers; exact point values are reported in the CSV
28
+ and manuscript text.
29
+
30
+ From the paper repository root:
31
+
32
+ ```bash
33
+ python3 figures/fig21_demon_mixed_cross_task/plot.py
34
+ latexmk -pdf arxiv.tex
35
+ latexmk -pdf iclr2027.tex
36
+ ```
experiments/task-transfer/paper/data.csv ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ task,eval_latency,zero_latency_train,mixed_latency_train
2
+ Demon Attack,0,6113,5812
3
+ Demon Attack,2,294,5542
4
+ Demon Attack,4,96,3510
5
+ Asterix,0,192,230
6
+ Asterix,2,202,262
7
+ Asterix,4,212,178
8
+ Atlantis,0,2000,2000
9
+ Atlantis,2,2000,3900
10
+ Atlantis,4,2000,5010
11
+ AirRaid,0,20,351
12
+ AirRaid,2,15,346
13
+ AirRaid,4,15,178
experiments/task-transfer/paper/fig_caption.tex ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ \caption{\textbf{Cross-task gains depend on the task and evaluation delay.}
2
+ Mixed-latency training on Demon Attack yields higher delayed returns on
3
+ Atlantis and AirRaid, while Asterix has lower return at four frames than with
4
+ zero-latency training. Gray and purple denote zero-latency and mixed-latency
5
+ training, respectively. From left to right, panels show Demon Attack,
6
+ Asterix, Atlantis, and AirRaid, evaluated at delays of 0, 2, and 4 raw frames.
7
+ Each point is the mean episode return over 20 evaluation episodes.}
experiments/task-transfer/paper/plot.py ADDED
@@ -0,0 +1,107 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """Demon Attack training cross-task evaluation companion figure."""
2
+
3
+ from __future__ import annotations
4
+
5
+ import csv
6
+ from pathlib import Path
7
+ import sys
8
+
9
+ import matplotlib
10
+
11
+ matplotlib.use("Agg")
12
+ import matplotlib.pyplot as plt
13
+ from matplotlib.lines import Line2D
14
+ from matplotlib.ticker import FuncFormatter
15
+
16
+
17
+ HERE = Path(__file__).resolve().parent
18
+ PAPER = HERE.parents[1]
19
+ sys.path.insert(0, str(PAPER))
20
+ import paper_colors
21
+
22
+
23
+ TASKS = ("Demon Attack", "Asterix", "Atlantis", "AirRaid")
24
+ SERIES = (
25
+ ("zero_latency_train", "Zero-latency training", paper_colors.GRAY),
26
+ ("mixed_latency_train", "Mixed-latency training", paper_colors.PURPLE),
27
+ )
28
+
29
+
30
+ def read_rows() -> dict[str, list[dict[str, float]]]:
31
+ by_task: dict[str, list[dict[str, float]]] = {task: [] for task in TASKS}
32
+ with (HERE / "data.csv").open(newline="", encoding="utf-8") as stream:
33
+ for row in csv.DictReader(stream):
34
+ by_task[row["task"]].append({
35
+ "eval_latency": float(row["eval_latency"]),
36
+ "zero_latency_train": float(row["zero_latency_train"]),
37
+ "mixed_latency_train": float(row["mixed_latency_train"]),
38
+ })
39
+ for rows in by_task.values():
40
+ rows.sort(key=lambda item: item["eval_latency"])
41
+ return by_task
42
+
43
+
44
+ def compact_int(value: float, _position: int) -> str:
45
+ if abs(value) >= 1000:
46
+ return f"{value / 1000:g}k"
47
+ return f"{value:g}"
48
+
49
+
50
+ def main() -> None:
51
+ plt.style.use(PAPER / "plot_style.mplstyle")
52
+ plt.rcParams.update(paper_colors.RC_COLORS)
53
+ data = read_rows()
54
+
55
+ fig, axes = plt.subplots(1, 4, figsize=(7.2, 2.25), sharex=True)
56
+ fig.subplots_adjust(left=0.075, right=0.995, top=0.76, bottom=0.24, wspace=0.32)
57
+
58
+ for ax, task in zip(axes, TASKS):
59
+ rows = data[task]
60
+ xs = [row["eval_latency"] for row in rows]
61
+ max_value = max(row[key] for row in rows for key, _label, _color in SERIES)
62
+ ymin = 0
63
+ ymax = max_value * 1.18
64
+
65
+ for key, label, color in SERIES:
66
+ ys = [row[key] for row in rows]
67
+ ax.plot(
68
+ xs,
69
+ ys,
70
+ marker="o",
71
+ markersize=3.1,
72
+ linewidth=1.25,
73
+ color=color,
74
+ label=label,
75
+ )
76
+ ax.set_title(task, fontsize=8.4, weight="bold", pad=6)
77
+ ax.set_xlim(-0.2, 4.2)
78
+ ax.set_ylim(ymin, ymax)
79
+ ax.set_xticks((0, 2, 4))
80
+ ax.yaxis.set_major_formatter(FuncFormatter(compact_int))
81
+ ax.tick_params(axis="both", labelsize=6.5)
82
+ ax.grid(True, axis="y")
83
+ ax.grid(False, axis="x")
84
+
85
+ axes[0].set_ylabel("Mean return", fontsize=7.2)
86
+ fig.supxlabel("Evaluation latency (raw frames)", fontsize=7.2, y=0.07)
87
+ handles = [
88
+ Line2D([0], [0], color=color, marker="o", markersize=3.2, linewidth=1.25, label=label)
89
+ for _key, label, color in SERIES
90
+ ]
91
+ fig.legend(
92
+ handles=handles,
93
+ loc="upper center",
94
+ bbox_to_anchor=(0.52, 0.995),
95
+ ncols=2,
96
+ columnspacing=1.6,
97
+ handlelength=1.8,
98
+ fontsize=6.5,
99
+ )
100
+
101
+ for extension in ("pdf", "png"):
102
+ fig.savefig(HERE / f"fig.{extension}", dpi=300, bbox_inches="tight", pad_inches=0.025)
103
+ plt.close(fig)
104
+
105
+
106
+ if __name__ == "__main__":
107
+ main()
experiments/task-transfer/provenance/asset_identity_verification.json ADDED
@@ -0,0 +1,1766 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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