diff --git a/FOUNDATION_MODEL_PLAN.md b/FOUNDATION_MODEL_PLAN.md index 70cadd0f258d13ce23760c2d755529ca19d395bd..c70f53560cd6d59a63d20a7e11ca9b84f340fc53 100644 --- a/FOUNDATION_MODEL_PLAN.md +++ b/FOUNDATION_MODEL_PLAN.md @@ -5,9 +5,11 @@ Qwen3-Omni LoRA pilot. It separates immediate trainable work from later world-model and robot-policy branches, so the project can choose a backbone without mixing different research goals. -Current status: this is a planning artifact. The public repo has verified -single-episode task heads and setup-stage Qwen3-Omni scripts. It has not yet -run a held-out multi-episode foundation-model evaluation. +Current status: this remains the backbone-selection plan, but the repo now has +verified held-out multi-episode foundation-model diagnostics: Qwen3-Omni LoRA +for structured JSON tasks, Cosmos3-Nano for future-window compatibility, +Cosmos3-Super Reasoner as a base-weight JSON-task evaluation, and Cosmos3-Super +Forward-Dynamics LoRA as the first fine-tuned Super adapter branch. ## Backbone Decision @@ -102,8 +104,11 @@ The practical Cosmos 3 branch should start with three targets: 3. **Synthetic data expansion:** generate or score candidate futures, then test whether synthetic windows improve downstream task heads. -A Cosmos 3 branch is ready to publish only after committed manifests, generated -outputs, held-out metrics, and qualitative examples are available. +A Cosmos 3 branch is now represented by two public-safe verified packages: +Cosmos3-Nano future-window compatibility and Cosmos3-Super forward-dynamics +LoRA. The Super LoRA target is camera-pose-conditioned future vision velocity, +so it should be analyzed as a world-model loss result rather than a JSON-task +classifier. ## Policy-Model Branch @@ -136,17 +141,17 @@ The foundation-model stage should add metrics beyond the current 12-task suite: ## Execution Order -1. Finish selected multi-episode pilot preparation. -2. Run the Qwen3-Omni LoRA pilot exactly once as the first held-out baseline. -3. Run a model-selection dry run on 3-8 episodes: Qwen3-Omni prompt-only, - Qwen3-Omni LoRA, Cosmos 3 world-model preprocessing, and one policy baseline. -4. Promote Cosmos 3 to the first world-model experiment if video/sensor - preprocessing and storage fit. -5. Promote OpenVLA/openpi/GR00T only after action targets are explicit and +1. Keep the selected 96/16/16 split as the comparison spine. +2. Treat the verified Qwen3-Omni LoRA package as the structured JSON baseline. +3. Treat Cosmos3-Nano compatibility and Cosmos3-Super Forward-Dynamics LoRA as separate world-model branches with different metrics. +4. Run a model-selection dry run on 3-8 episodes for any next backbone before scaling beyond the selected split. +5. Promote Cosmos 3 to larger world-model experiments if video/sensor + preprocessing, storage, and loss metrics justify the extra cost. +6. Promote OpenVLA/openpi/GR00T only after action targets are explicit and retargeting artifacts are traceable. -6. Update public cards only when a branch has real manifests, predictions, +7. Update public cards only when a branch has real manifests, predictions, metrics, and qualitative examples. -7. Start Xperience-native pretraining only after smaller scaling stages, +8. Start Xperience-native pretraining only after smaller scaling stages, full-corpus storage, multi-node compute, and held-out evaluation protocols are in place. diff --git a/PROJECT_STATUS.md b/PROJECT_STATUS.md index d8fe8691debc64ffaad9041290dc3493de516e7e..d828e047e3a8547a648def6c3375ccda48b741cb 100644 --- a/PROJECT_STATUS.md +++ b/PROJECT_STATUS.md @@ -22,8 +22,9 @@ scale-up readiness; it is not presented as final full-dataset model quality. | Audio contribution study | Verified | `scripts/audio_ablation_and_raw_upgrade.py`, `results/audio_ablation/`, `docs/data/audio_ablation_summary.json` | Audio variants are compared across all 12 task contracts; audio improves the primary metric on 6 of 12 tasks, and a 588-d audio-window representation improves over the baseline audio variant on 6 of 12 tasks. | | Research takeaways | Verified | `RESEARCH_TAKEAWAYS.md`, `docs/data/research_takeaways.json`, `scripts/build_research_takeaways.py` | The main result interpretation is generated from committed metrics: chronological class shift, neural gains on dynamics/order/alignment, open retrieval/reconstruction problems, and the need for held-out episodes. | | Research roadmap | Current | `RESEARCH_ROADMAP.md`, `docs/data/research_roadmap.json` | The roadmap connects public-sample task development to the final verified Qwen3-Omni diagnostic result, same-split baseline alignment, action/subtask error analysis, robustness runs, world/policy branches, and the future Xperience-native pretraining goal. | -| Foundation-model plan | Current | `FOUNDATION_MODEL_PLAN.md`, `docs/data/foundation_model_plan.json` | Qwen3-Omni remains the first trainable held-out LoRA baseline; Cosmos 3 is added as the first world-model/action-generation branch; Cosmos3-Super now has camera-pose proxy action targets that pass the contract audit and a schema-only batch-packer smoke. The current target mode is forward-dynamics, so it supports vision-velocity training under action conditioning, not supervised action-token prediction. OpenVLA/openpi/GR00T are policy candidates after robot-compatible action targets are explicit. | -| Cosmos3-Super action-target contract | Ready for forward-dynamics trainer implementation | `scripts/omni/export_cosmos3_camera_pose_targets.py`, `scripts/omni/pack_cosmos3_super_action_batch.py`, `results/omni_finetune/xperience10m_cosmos3_camera_pose_targets_20260608/target_manifest.json`, `results/omni_finetune/xperience10m_cosmos3_super_training_contract_audit_camera_pose_20260608/training_contract_audit.json`, `results/omni_finetune/xperience10m_cosmos3_super_action_packer_schema_smoke_20260608/packer_summary.json` | The selected 128-episode JSONL is augmented with 3,808/3,808 valid `camera_pose` proxy `cosmos_action_target` records from SLAM pose deltas. The schema-only packer smoke confirms the current `forward_dynamics` target should supervise noisy vision tokens under camera-pose conditioning; it does not supervise `preds_action`. Remaining work is a pipeline-loaded packer check, one-sample forward-dynamics overfit, and a separate policy/inverse target export before claiming action-token prediction. | +| Foundation-model plan | Current | `FOUNDATION_MODEL_PLAN.md`, `docs/data/foundation_model_plan.json` | Qwen3-Omni remains the first structured JSON LoRA baseline; Cosmos3-Nano is verified as a future-window compatibility branch; Cosmos3-Super is represented by a base-weight Reasoner evaluation and a fine-tuned Forward-Dynamics LoRA branch. The Super LoRA target is camera-pose-conditioned future vision velocity, not supervised JSON action-token prediction. OpenVLA/openpi/GR00T remain policy candidates after robot-compatible action targets are explicit. | +| Cosmos3-Super action-target contract | Superseded by verified forward-dynamics LoRA | `scripts/omni/export_cosmos3_camera_pose_targets.py`, `scripts/omni/pack_cosmos3_super_action_batch.py`, `results/omni_finetune/xperience10m_cosmos3_camera_pose_targets_20260608/target_manifest.json`, `results/omni_finetune/xperience10m_cosmos3_super_training_contract_audit_camera_pose_20260608/training_contract_audit.json`, `results/omni_finetune/xperience10m_cosmos3_super_action_packer_schema_smoke_20260608/packer_summary.json` | The selected 128-episode JSONL is augmented with 3,808/3,808 valid `camera_pose` proxy `cosmos_action_target` records from SLAM pose deltas. The schema packer and contract audit are now supporting evidence for the trained forward-dynamics branch; they still do not supervise `preds_action`, so action-token prediction needs a separate policy or inverse-dynamics target export. | +| Cosmos3-Super Forward-Dynamics LoRA | Verified fine-tuned adapter branch | `configs/omni_backbones/cosmos3_super_forward_dynamics.json`, `scripts/omni/train_cosmos3_super_forward_dynamics_lora.py`, `scripts/omni/eval_cosmos3_super_forward_dynamics_lora.py`, `results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/verified_result_summary.json`, `results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/package_audit.json` | The first fine-tuned Cosmos3-Super adapter branch is locally verified as a public-safe package: 26.2M LoRA parameters, 2,848 train rows, 512 validation rows, 448 held-out test rows, validation MSE 4.0082, and test MSE 3.6853. The package excludes adapter safetensors; weights are published separately at `cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep`. | | Omni model extension contract | Current | `OMNI_MODEL_EXTENSION_CONTRACT.md`, `configs/omni_backbones/`, `scripts/omni/backbone_registry.py`, `scripts/omni/smoke_test_backbone_packaging.py` | Future model branches must keep the same episode split discipline, held-out metrics, validation gate, public-safe package contract, and explicit forbidden-artifact policy before reporting results. | | Xperience Embodied Foundation Model | Future goal | `XPERIENCE_EMBODIED_FOUNDATION_MODEL_PRETRAINING.md` | A future full-corpus pretraining plan describes target modules, objectives, staged scale-up, hardware ranges, and evaluation for a domain-specific embodied foundation model. | | Evaluation protocol | Verified | `EVALUATION_PROTOCOL.md`, `docs/data/evaluation_protocol.json`, `scripts/build_evaluation_protocol.py` | Windowing, chronological split, per-task metrics, leakage controls, and current limitations are generated from committed metric artifacts. | diff --git a/README.md b/README.md index b34a638a297050c93d32c15b0ded09977603e6d9..a996f60b86be97f3e8b8a30358bffa92156aa9c1 100644 --- a/README.md +++ b/README.md @@ -47,11 +47,11 @@ Ropedia/Xperience-10M access terms. The implemented public-sample task suite uses one public Xperience-10M sample episode. The selected 128-episode Qwen3-Omni final diagnostic result uses a gated local dataset copy and publishes only public-safe metrics, predictions, -manifests, reports, and audits. The public LoRA adapter weights are published -separately at `cy0307/ropedia-qwen3-omni-lora-128ep`. Cosmos3-Nano and -Cosmos3-Super are currently published here as artifacts-only diagnostics; create -a separate Cosmos model repository only after real Cosmos adapter or fine-tuned -weights exist. +manifests, reports, and audits. The Qwen3-Omni LoRA adapter weights are +published separately at `cy0307/ropedia-qwen3-omni-lora-128ep`. +Cosmos3-Nano remains an artifacts-only compatibility result. Cosmos3-Super +Forward-Dynamics LoRA has a separate weight-bearing model repo at +`cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep`. ## Derived Artifacts @@ -66,9 +66,9 @@ This bundle includes derived artifacts such as: action/subtask quality documented as the next error-analysis target. - Historical Qwen3-Omni packages, including the earlier v2 strict-JSON diagnostic, for regression and prompt-contract comparison. -- Verified Cosmos3-Nano future-window compatibility and Cosmos3-Super - base-weight/readiness packages for the same selected split family; these are - artifacts only, not new Cosmos fine-tuned weight releases. +- Verified Cosmos3-Nano future-window compatibility, Cosmos3-Super + base-weight Reasoner evaluation, and Cosmos3-Super Forward-Dynamics LoRA + public-safe packages for the same selected split family. - 128-episode same-split simple/NN metadata baselines for the same 12 task ids, with unsupported markers where raw 128 sensor feature blocks are still needed. - A model-family grouped comparison that pairs 1-episode and 128-episode entries @@ -83,6 +83,7 @@ This bundle includes derived artifacts such as: | Artifact dataset | https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts | | Baseline model repo | https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines | | Qwen3-Omni LoRA adapter repo | https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep | +| Cosmos3-Super Forward-Dynamics LoRA adapter repo | https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep | | GitHub repo | https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite | ## Citation diff --git a/RESEARCH_ROADMAP.md b/RESEARCH_ROADMAP.md index 6f730c96b10e5dcc7e69eed457876a6216cb69d1..9cf2a15b4b815fa08c5854410e58a12948294755 100644 --- a/RESEARCH_ROADMAP.md +++ b/RESEARCH_ROADMAP.md @@ -145,15 +145,14 @@ objectives: audio-visible alignment, future-window prediction, action-conditioned world modeling, synthetic-data usefulness tests, policy-style next action, contact, object relevance, and affordance reasoning. -Current Cosmos3-Super status: a camera-pose proxy action target export now -augments all 3,808 selected 128-episode windows and passes the contract audit. -A schema-only batch-packer smoke confirms the current `forward_dynamics` target -uses camera-pose actions as conditioning and should supervise noisy vision -tokens, not `preds_action`. This is a trainer-readiness artifact, not a -fine-tuned Cosmos weight release. The next Cosmos step is a pipeline-loaded -packer check and one-sample forward-dynamics overfit before any 96/16/16 Super -LoRA run; supervised action-token prediction needs a separate policy or -inverse-dynamics target export. +Current Cosmos3-Super status: a camera-pose proxy action target export augments +all 3,808 selected 128-episode windows, passes the contract audit, and now has +a verified 8-GPU FSDP forward-dynamics LoRA run. The full run trains 26.2M LoRA +parameters on 2,848 train rows and evaluates 512 validation plus 448 held-out +test rows. It supervises noisy future vision velocity under camera-pose action +conditioning, not semantic JSON labels or `preds_action`; supervised +action-token prediction still needs a separate policy or inverse-dynamics +target export. ### 7. Xperience Embodied Foundation Model Pretraining diff --git a/docs/data/artifact_index.json b/docs/data/artifact_index.json index 0f48000513412fc2ab8018ab21ba3644c914aff7..50043f772b30e6c5460119579caf67c76004cd33 100644 --- a/docs/data/artifact_index.json +++ b/docs/data/artifact_index.json @@ -1,19 +1,19 @@ { "title": "Ropedia Xperience-10M Task Suite Artifact Index", - "generated_at_utc": "2026-06-07T15:47:31+00:00", + "generated_at_utc": "2026-06-08T07:14:28+00:00", "status": "pass", - "artifact_count": 129, + "artifact_count": 140, "missing": [], "by_kind": { "project_path": 14, "scaleup_contract": 7, - "scaleup_status": 20, + "scaleup_status": 24, "publication_workflow": 5, "project_scope": 1, "source_alignment": 5, "evaluation_protocol": 3, "result_interpretation": 5, - "metrics_source": 18, + "metrics_source": 22, "website_data": 3, "visual_evidence": 7, "quality_gate": 12, @@ -31,8 +31,8 @@ "generated_figure_assets": 1, "citation": 1, "license": 1, - "verified_public_package": 6, - "publication_audit": 4 + "verified_public_package": 8, + "publication_audit": 5 }, "artifacts": [ { @@ -65,8 +65,8 @@ "surface": "repo_hf", "shows": "Gives a compact current-state table for first-pass readers.", "exists": true, - "bytes": 9926, - "sha256": "c7dfb7a45f0c1ea435c16d93208a82da4227336e34f56a96d4afa04fce42438c" + "bytes": 12184, + "sha256": "29689397ad66c4ff7040cbe72288ca33421513402819e4bff7ce0e52bb420372" }, { "id": "project_status_json", @@ -76,8 +76,8 @@ "surface": "website_hf", "shows": "Machine-readable copy of the current project status for website and HF mirrors.", "exists": true, - "bytes": 16455, - "sha256": "3590ee1e09ecf819080a7714ea9629db305e1fd68c99a65f62bb65061c0d766c" + "bytes": 19360, + "sha256": "a7ef3b7998a7fa10d1aa1a462caa3df122884fdaa54fe5812b439e18288ebd5c" }, { "id": "research_roadmap", @@ -87,8 +87,8 @@ "surface": "repo_hf", "shows": "Defines the path from public-sample task development to multi-episode held-out evaluation and larger omni-model extensions.", "exists": true, - "bytes": 12233, - "sha256": "020512aa647cef7d63eccf7bb8dd6cb86f0e5c457f3c0e3d5ef293e7b35a58bf" + "bytes": 12788, + "sha256": "36d051787142e640748360dbbc14805521d0e2f4f834030af5fed206d319e758" }, { "id": "research_roadmap_json", @@ -98,8 +98,8 @@ "surface": "website_hf", "shows": "Machine-readable research roadmap for the website and Hugging Face mirrors.", "exists": true, - "bytes": 10133, - "sha256": "45fd3a1bde93654ccfe14f9271928a67b36eb3f166826bfbdbb9c1092ad33bcf" + "bytes": 10502, + "sha256": "33725c2b41370e4d8b2df3d45f412ff75f398457ad81376eee1a2b0730101f6a" }, { "id": "foundation_model_plan", @@ -109,8 +109,8 @@ "surface": "repo_hf", "shows": "Defines the post-data-gate backbone choices: Qwen3-Omni first, Cosmos 3 for world modeling, and VLA/policy models after action-target conversion.", "exists": true, - "bytes": 9075, - "sha256": "444d13ab556d2e16a199a7fca191b87c85ab8685d167aab357bc6341839299a2" + "bytes": 9550, + "sha256": "5adb6a3be92ccde189176cc618eb0814ec63f094191a61f7695d3f55fae36b3d" }, { "id": "foundation_model_plan_json", @@ -120,8 +120,8 @@ "surface": "website_hf", "shows": "Machine-readable foundation-model selection matrix with source links, entry conditions, and evaluation additions.", "exists": true, - "bytes": 13193, - "sha256": "63529cbaf1d5c549f595b3ed49f49feda03edf96952b5cb321117fee340849c9" + "bytes": 13457, + "sha256": "7d17f3c6a2cd9954c9632d7063d3aab7d5753c709215239257f065274ab394f3" }, { "id": "omni_model_extension_contract", @@ -142,8 +142,8 @@ "surface": "repo_hf", "shows": "Stores the implemented Qwen3-Omni LoRA contract and planned Cosmos-style world-model and VLA/policy branch contracts.", "exists": true, - "file_count": 4, - "bytes": 12613 + "file_count": 5, + "bytes": 16418 }, { "id": "omni_backbone_registry_validator", @@ -219,8 +219,8 @@ "surface": "repo_hf", "shows": "Builds the upload-ready Hugging Face adapter folder from a verified Qwen3 LoRA result summary and adapter directory.", "exists": true, - "bytes": 10710, - "sha256": "c5f33f7030e6861ccab465b71d4c1b4209b8fbbcebdca882aa5c7e8d70e76b37" + "bytes": 11332, + "sha256": "e9f9909185c5c647a5df2444d0ce2c3d07dca719fdd92c9bf1c7964e19963fa1" }, { "id": "additional_development_directions", @@ -274,8 +274,8 @@ "surface": "website_hf", "shows": "Gives a short project path with scope status and public surfaces.", "exists": true, - "bytes": 8005, - "sha256": "2258fecb80850c745e60cb28733869c49a5182879d9d0461b666a5575e3c1610" + "bytes": 8656, + "sha256": "caa33f6a5dfbbbc8a96fc8b99db37a5ffd2fc48a133a9ddfcc08754ee3335793" }, { "id": "artifact_guide", @@ -351,8 +351,8 @@ "surface": "repo_hf", "shows": "Publishes prepared Space, artifact dataset, and model bundles, including an explicit model-binary upload batch.", "exists": true, - "bytes": 15927, - "sha256": "7b3e515763ccce08f72b4fd12a903c21f14b469c6af144524196ecad945da2ab" + "bytes": 18192, + "sha256": "2c30b289b31211f5ecf319c19eece74a15d883a9f62df893df5a68a3c22f8d4d" }, { "id": "github_package_dockerfile", @@ -582,8 +582,8 @@ "surface": "website_hf", "shows": "Machine-readable release-check summary for validators, mirrors, and public project surfaces.", "exists": true, - "bytes": 8099, - "sha256": "c67b1a3cbd1a355ffdecec22d22486c181f081b03286f4180acff7f9659402e0" + "bytes": 8097, + "sha256": "076f83cfdbad683b14d98ba32390a95a1ca71b4c020fa1cfbbbc20cc83e23c94" }, { "id": "public_surface_qa", @@ -605,7 +605,7 @@ "volatile": true, "shows": "Machine-readable report for SEO/social metadata, accessible tab semantics, public links, project links, and clear project presentation.", "exists": true, - "bytes": 5591, + "bytes": 5588, "hash_policy": "existence_and_size_only" }, { @@ -697,8 +697,8 @@ "surface": "repo", "shows": "Fetches the published GitHub/HF URLs and compares live hashes and public-card markers against the release assets.", "exists": true, - "bytes": 36201, - "sha256": "76f03885867a8ed7095958a6948cbce81b4958fb74a09df24c24ad7eb5b0d944" + "bytes": 38048, + "sha256": "94a9ff4afe666e96d3bd0d0265e16a4e26dca799a18de4ac8f42fca7836022db" }, { "id": "reproducibility_contract", @@ -742,7 +742,7 @@ "volatile": true, "shows": "Confirms public bundles exclude raw data, caches, heavy archives, and credential text.", "exists": true, - "bytes": 7212, + "bytes": 7213, "hash_policy": "existence_and_size_only" }, { @@ -754,7 +754,7 @@ "volatile": true, "shows": "Separates setup paths from completed held-out-episode results.", "exists": true, - "bytes": 21251, + "bytes": 21365, "hash_policy": "existence_and_size_only" }, { @@ -766,7 +766,7 @@ "volatile": true, "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.", "exists": true, - "bytes": 410374, + "bytes": 408299, "hash_policy": "existence_and_size_only" }, { @@ -778,7 +778,7 @@ "volatile": true, "shows": "Confirms local website links, anchors, JSON data files, and referenced images resolve.", "exists": true, - "bytes": 15375, + "bytes": 15392, "hash_policy": "existence_and_size_only" }, { @@ -811,8 +811,8 @@ "surface": "website_hf", "shows": "Mirrors task metrics for the static dashboard.", "exists": true, - "bytes": 27490, - "sha256": "159ed565571aa4215ef30a5ea8fce057481cf0f77ad50aec3ae15de6a38e12ba" + "bytes": 27604, + "sha256": "ebaf9d598b4cd91118f149cafa01fe4d17629499565b7be0c7ce4a0ffcd70f6b" }, { "id": "feature_manifest", @@ -965,8 +965,8 @@ "surface": "repo_hf", "shows": "Documents the final 128-episode LoRA adapter upload path, target model repo, package builder, and forbidden files.", "exists": true, - "bytes": 1886, - "sha256": "a8fa5a326e2dd91130c2e86b988e7afcfa4e043e48614191f0fc589158089c03" + "bytes": 1877, + "sha256": "d12d0b15eb6374b380940a95d13d87c8f840bb5118cf4b57e57965e018ec14e6" }, { "id": "multi_episode_access_status", @@ -1031,8 +1031,8 @@ "surface": "repo_hf", "shows": "Reader-facing comparison of the single-episode task suite, 128-episode aligned baselines, Qwen3-Omni packages, and Cosmos3 future-window branch.", "exists": true, - "bytes": 9231, - "sha256": "c38d12e138193f7200800d4dd8c149497de2c5f5895299e22fe81285b69fc62d" + "bytes": 11899, + "sha256": "df68cd54bb0d3c9cc410aa1779bbec9ef20f2aba4a0516c08ae1b8db9be5c652" }, { "id": "omni_model_comparison_json", @@ -1042,8 +1042,8 @@ "surface": "repo_hf", "shows": "Machine-readable comparison of the current result versions, per-task aligned baselines, verified Qwen3 packages, and Cosmos3 package.", "exists": true, - "bytes": 48296, - "sha256": "1c968bd58842af9a4e6159c1a8bd171aec08757bb77fce9f04c55030be08357f" + "bytes": 62577, + "sha256": "65b11e0a9eede70d71229737294ab15a729b421184b1c451237e5d820904e71b" }, { "id": "cosmos3_nano_verified_summary", @@ -1144,6 +1144,72 @@ "bytes": 1099, "sha256": "f11ccb167908d4f5bfb49c0be0b4bc6c9254901462aa52ae98a2a98e8af16558" }, + { + "id": 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"a1c1f81d4bb53a49b4e912450159c9872de66784aab4f3d41e20c40055daa11e" } ] } diff --git a/docs/data/foundation_model_plan.json b/docs/data/foundation_model_plan.json index a48e8796c2c65ac45e54907942f6a3f06301bc38..d548eac033c3b456bb8a2b8eaa7ac9e98e2d6b85 100644 --- a/docs/data/foundation_model_plan.json +++ b/docs/data/foundation_model_plan.json @@ -1,14 +1,19 @@ { "title": "Xperience-10M Foundation Model Plan", "status": "planning_artifact", - "current_boundary": "A final held-out multi-episode Qwen3-Omni diagnostic result is verified in this repo and meets the strict-JSON target, but it is not a strong action/subtask model result. The current foundation-model work should treat it as the baseline train/eval/package loop before Qwen action/subtask improvements, Cosmos-style world modeling, or policy/VLA branches.", + "current_boundary": "Verified held-out multi-episode foundation-model diagnostics now exist for Qwen3-Omni LoRA, Cosmos3-Nano future-window compatibility, Cosmos3-Super base-weight Reasoner evaluation, and Cosmos3-Super Forward-Dynamics LoRA. Qwen remains the structured JSON baseline; the Cosmos branches answer world-model or base-reasoner questions with separate metrics.", "backbone_registry": { "config_dir": "configs/omni_backbones", "validator": "scripts/omni/backbone_registry.py --validate --json", "extension_contract": "OMNI_MODEL_EXTENSION_CONTRACT.md", "implemented_backbone": "qwen3_omni_lora", - "planned_backbones": [ + "implemented_backbones": [ + "qwen3_omni_lora", "cosmos_world_model", + "cosmos3_super_reasoner", + "cosmos3_super_forward_dynamics" + ], + "planned_backbones": [ "policy_vla_branch" ] }, @@ -107,8 +112,8 @@ "Uses pose/SLAM, depth, mocap, IMU, and language as physical-world conditioning signals.", "Better aligned with prediction/generation objectives than simple label classification." ], - "current_decision": "add_as_first_world_model_branch_after_data_gate", - "entry_condition": "Multi-episode data plus enough storage/compute for generated or latent video-state outputs.", + "current_decision": "implemented_as_nano_future_window_and_super_forward_dynamics_branches", + "entry_condition": "Use separate metrics for Nano future-window retrieval and Super forward-dynamics MSE; do not compare them directly to Qwen JSON-task accuracy.", "public_source": "https://www.nvidia.com/en-us/ai/cosmos/" }, { @@ -211,12 +216,12 @@ { "step": 3, "name": "Model-selection dry run", - "action": "Run 3-8 episode dry runs for Qwen3-Omni prompt/LoRA, Cosmos 3 preprocessing, and one policy candidate." + "action": "Run 3-8 episode dry runs for any next backbone before scaling beyond the selected split." }, { "step": 4, "name": "World-model branch", - "action": "Promote Cosmos 3 if future-window/action-conditioned preprocessing fits storage and compute." + "action": "Promote Cosmos 3 beyond the current Nano compatibility and Super forward-dynamics runs only when loss metrics, preprocessing, and storage justify the added compute." }, { "step": 5, diff --git a/docs/data/omni_finetune_verified_result.json b/docs/data/omni_finetune_verified_result.json index 24861dea72ad7b5abd7b6792124fe0b35608d6cc..46d4df258a06840df811839bd8989633c070f6fa 100644 --- a/docs/data/omni_finetune_verified_result.json +++ b/docs/data/omni_finetune_verified_result.json @@ -80,7 +80,7 @@ "required_next_steps": [ "Use the v3 strict-label predictions for action/subtask error analysis and unseen-label debugging.", "Keep the existing Qwen LoRA adapter repository as the weight-bearing artifact; v3 is an evaluation/package refresh over the same adapter, not new weights.", - "Implement the Cosmos3-Super pipeline-loaded batch packer and one-sample forward-dynamics overfit before claiming Cosmos3 fine-tuning; camera-pose proxy targets are now exported, contract-audited, and schema-packed, but no Cosmos weights have been updated.", + "Use the verified Cosmos3-Super Forward-Dynamics LoRA package as a separate world-model branch: it updates adapter weights over camera-pose proxy future-vision-velocity targets, not Qwen-style JSON action labels.", "Use sharded Qwen eval for future long held-out passes to improve GPU utilization." ] } diff --git a/docs/data/omni_model_comparison.json b/docs/data/omni_model_comparison.json index c723572e4ef8629a5dcd68f172e780117f8c51f5..5a56cc54c78d8dd0e5cbae4ebfe3592ee4431a5d 100644 --- a/docs/data/omni_model_comparison.json +++ b/docs/data/omni_model_comparison.json @@ -1,14 +1,14 @@ { "title": "Ropedia Xperience-10M Current Result Versions and Model Groups", - "generated_at_utc": "2026-06-07T23:37:45+00:00", + "generated_at_utc": "2026-06-08T07:13:32+00:00", "status": "pass", "version_count": 3, - "model_group_count": 4, + "model_group_count": 5, "comparison_rule": "Compare only rows with the same scope and target. Single-episode raw-feature metrics, 128-episode metadata baselines, Qwen3 structured JSON metrics, and the two Cosmos3 targets answer different questions: Nano future-window retrieval versus Super structured JSON Reasoner evaluation.", "version_reading_notes": [ "Version 1 is the public-sample 12-task harness with minimal and neural heads.", "Version 2 is the selected 128-episode same-split simple/NN baseline alignment.", - "Version 3 is the verified model-branch layer: the current final Qwen3-Omni LoRA package is the JSON-task diagnostic result, Cosmos3-Nano is a future-window compatibility result, and Cosmos3-Super Reasoner is a base-weight JSON-task evaluation; Cosmos3-Super has a camera-pose forward-dynamics contract audit and schema-only packer smoke, but no new fine-tuned weight release." + "Version 3 is the verified model-branch layer: the current final Qwen3-Omni LoRA package is the JSON-task diagnostic result, Cosmos3-Nano is a future-window compatibility result, Cosmos3-Super Reasoner is a base-weight JSON-task evaluation, and Cosmos3-Super Forward-Dynamics LoRA is the first Super fine-tuned adapter branch." ], "versions": [ { @@ -313,16 +313,17 @@ "source": "results/omni_finetune/verified_public/", "split": "episode/session held-out split; exact task target depends on backbone contract", "counts": { - "verified_branch_count": 7, + "verified_branch_count": 8, "qwen3_verified_package_count": 5, - "cosmos3_verified_package_count": 2, + "cosmos3_verified_package_count": 3, "cosmos3_nano_verified_package_count": 1, - "cosmos3_super_verified_package_count": 1 + "cosmos3_super_verified_package_count": 2 }, "models": [ "Qwen3-Omni LoRA", "Cosmos3-Nano future-window compatibility branch", - "Cosmos3-Super Reasoner base-weight evaluation" + "Cosmos3-Super Reasoner base-weight evaluation", + "Cosmos3-Super forward-dynamics LoRA" ], "branches": [ { @@ -370,6 +371,49 @@ "is_current": true, "weights_repository": "planned separate Cosmos3 model repo after a real Cosmos diffusion/LoRA fine-tune exists; current result remains artifacts-only" }, + { + "id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp", + "title": "Cosmos3-Super Forward-Dynamics LoRA", + "status": "verified", + "backbone": "cosmos3_super_forward_dynamics", + "dataset_contract": "xperience10m_camera_pose_forward_dynamics_v1", + "training_objective": "camera_pose_conditioned_future_vision_velocity_lora", + "source": "results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/verified_result_summary.json", + "dataset_run_id": "xperience10m_cosmos3_camera_pose_targets_20260608", + "train_run_id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608", + "eval_run_id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp", + "counts": { + "dataset_samples": 3808, + "dataset_episodes": 119, + "split_counts": { + "test": 448, + "train": 2848, + "val": 512 + }, + "train_samples": 2848, + "val_samples": 512, + "eval_samples": 448, + "held_out_episode_count": 14, + "num_processes": 8 + }, + "primary_metrics": { + "adapter_parameter_numel": 26214400, + "held_out_episode_count": 14, + "test_forward_dynamics_mse": 3.6853174321087345, + "train_final_loss": 1.0785235166549683, + "val_forward_dynamics_mse": 4.008244896889664 + }, + "history": [ + { + "epoch": 1, + "note": "FSDP 8-GPU LoRA over camera-pose-conditioned future vision velocity loss; adapter weights are excluded from this public package.", + "train_loss": 1.0785235166549683, + "val_loss": 4.008244896889664 + } + ], + "is_current": true, + "weights_repository": "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep" + }, { "id": "xperience10m_cosmos3_super_reasoner_128ep_test_full_20260607", "title": "Cosmos3-Super Reasoner", @@ -670,7 +714,7 @@ "weights_repository": "https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep" } ], - "interpretation": "This layer contains the held-out foundation-model packages. Qwen3-Omni packages evaluate structured JSON task prediction; Cosmos3-Nano evaluates a future-window world-model compatibility adapter; Cosmos3-Super Reasoner evaluates staged base weights through vLLM on the JSON task. Neither Cosmos branch is a new fine-tuned weight release yet." + "interpretation": "This layer contains the held-out foundation-model packages. Qwen3-Omni packages evaluate structured JSON task prediction; Cosmos3-Nano evaluates a future-window world-model compatibility adapter; Cosmos3-Super Reasoner evaluates staged base weights through vLLM on the JSON task; Cosmos3-Super Forward-Dynamics LoRA is the first Super adapter branch and evaluates camera-pose-conditioned future vision velocity loss." } ], "model_groups": [ @@ -1239,7 +1283,70 @@ "weights_repository": "none for this run: staged base nv-community/Cosmos3-Super weights were evaluated through vLLM; create a separate repo only after new adapter or fine-tuned weights exist" } ], - "comparison_note": "Cosmos3-Super is now represented by a verified 448-window held-out Reasoner evaluation on the same JSON task as Qwen3. It uses staged base weights through vLLM, so it is a model-branch diagnostic, not a weight release. A camera-pose proxy forward-dynamics target export now passes the contract audit and schema-only packer smoke; true Cosmos3-Super fine-tuning is still blocked until a trainable multi-GPU/offload path produces adapter or fine-tuned weights." + "comparison_note": "Cosmos3-Super is now represented by a verified 448-window held-out Reasoner evaluation on the same JSON task as Qwen3. It uses staged base weights through vLLM, so it is a model-branch diagnostic, not a weight release. A camera-pose proxy forward-dynamics target export now passes the contract audit and schema-only packer smoke; the separate Forward-Dynamics LoRA group records the trainable adapter run and loss-based held-out evaluation." + }, + { + "id": "cosmos3_super_forward_dynamics", + "model_family": "Cosmos3-Super Forward-Dynamics LoRA", + "model_type": "PEFT LoRA over nv-community/Cosmos3-Super for camera-pose-conditioned future vision velocity", + "weight_repository": "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep", + "one_episode_runs": [ + { + "id": "cosmos3_super_forward_dynamics_overfit_smoke", + "title": "Cosmos3-Super Forward-Dynamics Overfit Smoke", + "scope": "small overfit smoke before 128-episode scale-up", + "status": "verified_smoke", + "source": "results/omni_finetune/xperience10m_cosmos3_super_forward_dynamics_lora_overfit_after_qwen_v4_20260608_fsdp8_attn256_gradfix_savefix2/", + "weights": "local repaired LoRA smoke adapter, not public packaged as final", + "interpretation": "Validated the trainable adapter path, FSDP save repair, and Diffusers load before the full 128-episode run." + } + ], + "multi_episode_128_runs": [ + { + "id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp", + "title": "Cosmos3-Super Forward-Dynamics LoRA", + "status": "verified", + "backbone": "cosmos3_super_forward_dynamics", + "dataset_contract": "xperience10m_camera_pose_forward_dynamics_v1", + "training_objective": "camera_pose_conditioned_future_vision_velocity_lora", + "source": "results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/verified_result_summary.json", + "dataset_run_id": "xperience10m_cosmos3_camera_pose_targets_20260608", + "train_run_id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608", + "eval_run_id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp", + "counts": { + "dataset_samples": 3808, + "dataset_episodes": 119, + "split_counts": { + "test": 448, + "train": 2848, + "val": 512 + }, + "train_samples": 2848, + "val_samples": 512, + "eval_samples": 448, + "held_out_episode_count": 14, + "num_processes": 8 + }, + "primary_metrics": { + "adapter_parameter_numel": 26214400, + "held_out_episode_count": 14, + "test_forward_dynamics_mse": 3.6853174321087345, + "train_final_loss": 1.0785235166549683, + "val_forward_dynamics_mse": 4.008244896889664 + }, + "history": [ + { + "epoch": 1, + "note": "FSDP 8-GPU LoRA over camera-pose-conditioned future vision velocity loss; adapter weights are excluded from this public package.", + "train_loss": 1.0785235166549683, + "val_loss": 4.008244896889664 + } + ], + "is_current": true, + "weights_repository": "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep" + } + ], + "comparison_note": "This is the first verified Cosmos3-Super fine-tuned adapter branch. Its metric is forward-dynamics MSE, so compare it to world-model loss or future-prediction targets, not to Qwen JSON classification accuracy." } ], "model_group_reading_notes": [ @@ -1247,10 +1354,10 @@ "Task-head baselines have both a one-episode public-sample run and a 128-episode same-split metadata/text run.", "Qwen3-Omni has a one-episode sensor-adapter smoke test and separate 128-episode LoRA diagnostic packages; the newest verified full-eval 128-episode adapter belongs in the Qwen LoRA model repo.", "Cosmos3-Nano has a 128-episode future-window compatibility package.", - "Cosmos3-Super has a 128-episode base-weight Reasoner evaluation on the JSON task plus a camera-pose forward-dynamics contract audit; create a separate Cosmos model repo only after a trainable multi-GPU/offload run produces real Cosmos adapter or fine-tuned weights." + "Cosmos3-Super now has both a 128-episode base-weight Reasoner evaluation on the JSON task and a fine-tuned forward-dynamics LoRA branch over camera-pose proxy targets." ], "pending": [ "Use the verified Qwen3 v4 4-epoch full-eval package as the current Qwen row; older Qwen package rows remain historical diagnostics for comparison.", - "Promote Cosmos3 from Nano compatibility, Super base-weight evaluation, and the camera-pose forward-dynamics contract to true fine-tuning only after a trainable Cosmos3-Super run produces new weights." + "Verify the live Cosmos3-Super forward-dynamics adapter model repo after upload; the public-safe verified_public package still excludes safetensors by design." ] } diff --git a/docs/data/project_packet.json b/docs/data/project_packet.json index a6503b2b6cb1763411b9babc667e262fc3d24f99..b7bccd04920025fc9c0d36f20f2bf4824010f604 100644 --- a/docs/data/project_packet.json +++ b/docs/data/project_packet.json @@ -12,7 +12,8 @@ "raw_xperience10m_data_in_repo": false, "audio_feature_status": "Audio is one of the synchronized source modalities in the current task representation.", "qwen3_omni_32_episode_claim": false, - "qwen3_omni_status": "The selected 96/16/16 Qwen3-Omni final diagnostic result is verified, meets the strict-JSON target, and still has weak action/subtask metrics that guide the next error-analysis pass." + "qwen3_omni_status": "The selected 96/16/16 Qwen3-Omni final diagnostic result is verified, meets the strict-JSON target, and still has weak action/subtask metrics that guide the next error-analysis pass.", + "cosmos3_super_forward_dynamics_lora_status": "The first Cosmos3-Super fine-tuned adapter branch is verified as a forward-dynamics LoRA over camera-pose proxy targets; it reports loss metrics, not JSON action-label accuracy." }, "reading_path": [ { @@ -41,7 +42,7 @@ "docs/data/scope_claims_audit.json", "docs/data/website_integrity.json" ], - "readout": "The project status table and roadmap give the compact current-state summary. Single-episode task engineering, metrics, visualizations, public website integrity, mirror parity, same-split 128-episode baselines, the final selected-episode Qwen3-Omni diagnostic result, the Cosmos3-Nano compatibility package, the Cosmos3-Super base-weight Reasoner evaluation, and the Cosmos3-Super camera-pose forward-dynamics contract audit plus schema-only packer smoke are implemented; stronger action/subtask and real Cosmos fine-tuned model quality remain follow-ups." + "readout": "The project status table and roadmap give the compact current-state summary. Single-episode task engineering, metrics, visualizations, public website integrity, mirror parity, same-split 128-episode baselines, the final selected-episode Qwen3-Omni diagnostic result, the Cosmos3-Nano compatibility package, the Cosmos3-Super base-weight Reasoner evaluation, and the Cosmos3-Super Forward-Dynamics LoRA package are implemented; stronger action/subtask quality and policy-compatible action targets remain follow-ups." }, { "step": 2, @@ -116,7 +117,7 @@ "scripts/omni/discover_xperience10m_sources.py", "docs/data/omni_finetune_verified_result.json" ], - "readout": "The selected-episode held-out Qwen3-Omni final diagnostic result is verified and JSON-format reliability meets the 98% target. The next milestone is action/subtask error analysis and a stronger model-quality run on the same split." + "readout": "The selected-episode held-out Qwen3-Omni final diagnostic result is verified and JSON-format reliability meets the 98% target. The same public comparison also includes the verified 128-episode baselines, Cosmos3-Nano compatibility result, Cosmos3-Super Reasoner evaluation, and Cosmos3-Super Forward-Dynamics LoRA package. The next milestone is action/subtask error analysis and stronger model-quality runs on the same split." } ], "project_status": "PROJECT_STATUS.md", @@ -142,7 +143,8 @@ "hf_model_baselines": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines" }, "current_reading_notes": [ - "The first cross-episode Qwen3-Omni diagnostic pilot is verified, but strong model quality is not yet shown.", + "The first cross-episode Qwen3-Omni diagnostic pilot is verified, but strong model quality is not yet shown; action/subtask metrics remain weak.", + "Cosmos3-Super Forward-Dynamics LoRA is verified as a loss-based world-model adapter branch, not as JSON action-token prediction.", "Older Qwen3-Omni setup artifacts are separate from the verified selected-episode diagnostic package.", "Feature-vector reconstruction is separate from pixel-depth, mesh, NeRF, or Gaussian reconstruction.", "Raw Xperience-10M data is not redistributed in this repo." diff --git a/docs/data/project_status.json b/docs/data/project_status.json index cb62dbfc61a5d3878fb974b43ac71f2867ea6e70..41a86d11810c3f42bb2db35e9341f5a7e4e201a6 100644 --- a/docs/data/project_status.json +++ b/docs/data/project_status.json @@ -34,6 +34,12 @@ "cosmos3_super_reasoner_verified": true, "cosmos3_super_reasoner_test_predictions": 448, "cosmos3_super_reasoner_json_validity_rate": 0.5111607142857143, + "cosmos3_super_forward_dynamics_lora_verified": true, + "cosmos3_super_forward_dynamics_train_rows": 2848, + "cosmos3_super_forward_dynamics_val_rows": 512, + "cosmos3_super_forward_dynamics_test_rows": 448, + "cosmos3_super_forward_dynamics_test_mse": 3.6853174321087345, + "cosmos3_super_forward_dynamics_adapter_params": 26214400, "omni_model_comparison_available": true, "multi_episode_128_aligned_baselines": true, "multi_episode_128_baseline_window_counts": { @@ -119,7 +125,7 @@ "FOUNDATION_MODEL_PLAN.md", "docs/data/foundation_model_plan.json" ], - "readout": "Qwen3-Omni remains the first trainable held-out LoRA baseline; Cosmos 3 is now represented by a verified Cosmos3-Nano future-window compatibility package, a verified Cosmos3-Super base-weight Reasoner evaluation, and a Cosmos3-Super camera-pose proxy forward-dynamics contract audit plus schema-only packer smoke. The current target supports vision-velocity training under action conditioning, not supervised action-token prediction; OpenVLA/openpi/GR00T are policy candidates after robot-compatible action targets are explicit." + "readout": "Qwen3-Omni remains the first structured JSON LoRA baseline; Cosmos 3 is now represented by a verified Cosmos3-Nano future-window compatibility package, a verified Cosmos3-Super base-weight Reasoner evaluation, and a verified Cosmos3-Super Forward-Dynamics LoRA over camera-pose proxy targets. The Super LoRA target supports vision-velocity training under action conditioning, not supervised action-token prediction; OpenVLA/openpi/GR00T remain policy candidates after robot-compatible action targets are explicit." }, { "area": "Omni model extension contract", @@ -207,7 +213,7 @@ "results/omni_finetune/OMNI_MODEL_COMPARISON.md", "scripts/omni/build_omni_model_comparison.py" ], - "readout": "The public comparison now has two views: the three result layers and a model-family grouping. The model grouping pairs 1-episode and 128-episode entries for task-head baselines, separates Qwen3-Omni sensor-adapter smoke from 128-episode LoRA diagnostics, and separates Cosmos3-Nano future-window compatibility from Cosmos3-Super base-weight Reasoner evaluation." + "readout": "The public comparison now has two views: the three result layers and a model-family grouping. The model grouping pairs 1-episode and 128-episode entries for task-head baselines, separates Qwen3-Omni sensor-adapter smoke from 128-episode LoRA diagnostics, separates Cosmos3-Nano future-window compatibility from Cosmos3-Super base-weight Reasoner evaluation, and adds Cosmos3-Super Forward-Dynamics LoRA as a loss-based fine-tuned adapter branch." }, { "area": "Qwen3-Omni fine-tuning", @@ -246,7 +252,7 @@ }, { "area": "Cosmos3-Super action-target contract", - "status": "ready_for_forward_dynamics_trainer_implementation", + "status": "superseded_by_verified_forward_dynamics_lora", "evidence": [ "scripts/omni/export_cosmos3_camera_pose_targets.py", "scripts/omni/pack_cosmos3_super_action_batch.py", @@ -254,7 +260,19 @@ "results/omni_finetune/xperience10m_cosmos3_super_training_contract_audit_camera_pose_20260608/training_contract_audit.json", "results/omni_finetune/xperience10m_cosmos3_super_action_packer_schema_smoke_20260608/packer_summary.json" ], - "readout": "The selected 128-episode JSONL is augmented with 3,808/3,808 valid camera_pose proxy cosmos_action_target records from SLAM pose deltas. The schema-only packer smoke confirms the current forward_dynamics target should supervise noisy vision tokens under camera-pose conditioning; it does not supervise preds_action. Remaining work is a pipeline-loaded packer check, one-sample forward-dynamics overfit, and a separate policy/inverse target export before claiming action-token prediction." + "readout": "The selected 128-episode JSONL is augmented with 3,808/3,808 valid camera_pose proxy cosmos_action_target records from SLAM pose deltas. The contract and packer smoke enabled the verified forward-dynamics LoRA run; it supervises noisy vision tokens under camera-pose conditioning and does not supervise preds_action." + }, + { + "area": "Cosmos3-Super Forward-Dynamics LoRA", + "status": "verified_fine_tuned_adapter_result", + "evidence": [ + "configs/omni_backbones/cosmos3_super_forward_dynamics.json", + "scripts/omni/train_cosmos3_super_forward_dynamics_lora.py", + "scripts/omni/eval_cosmos3_super_forward_dynamics_lora.py", + "results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/verified_result_summary.json", + "results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/package_audit.json" + ], + "readout": "The first fine-tuned Cosmos3-Super adapter branch is verified as a public-safe package: 8-GPU FSDP LoRA, 26.2M adapter parameters, 2,848 train rows, 512 validation rows, 448 held-out test rows, validation MSE 4.0082, and test MSE 3.6853. The package excludes adapter safetensors; weights are published separately at cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep." }, { "area": "Raw Xperience-10M redistribution", @@ -288,11 +306,11 @@ "Use docs/data/omni_model_comparison.json to compare both views: the single-episode/128-baseline/model-branch result layers and the model-family grouping for task heads, Qwen3-Omni LoRA, Cosmos3-Nano, and Cosmos3-Super.", "Use docs/data/omni_finetune_verified_result.json and the latest verified_public final Qwen package for current held-out results.", "The 128-episode aligned simple/NN baselines use metadata/text features from the derived Qwen JSONL export; they align the split and task ids but do not replace raw-modality baselines for trajectory, retrieval, reconstruction, or misalignment tasks.", - "The Cosmos3-Nano future-window branch is verified as a compatibility adapter result, Cosmos3-Super Reasoner is verified as a base-weight evaluation, and Cosmos3-Super camera-pose forward-dynamics targets now pass the contract audit plus a schema-only packer smoke; one-episode Cosmos fine-tuning and full Cosmos adapter/diffusion-weight fine-tuning remain pending, so no Cosmos weight repo should be published yet.", + "The Cosmos3-Nano future-window branch is verified as a compatibility adapter result, Cosmos3-Super Reasoner is verified as a base-weight evaluation, and Cosmos3-Super Forward-Dynamics LoRA is verified as the first fine-tuned Super adapter branch. Cosmos3-Super adapter weights belong in cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep; verified_public packages exclude safetensors.", "The current reconstruction task reconstructs feature vectors, not pixel-depth, mesh, NeRF, or Gaussian reconstruction.", "Audio is one of the synchronized source modalities in the current task representation.", "The audio ablation report compares audio/no-audio variants across all 12 task contracts in results/audio_ablation/.", - "Foundation-model selection is explicit: Qwen3-Omni is the immediate trainable pilot, Cosmos 3 is the first world-model branch, Cosmos3-Super has a camera-pose proxy forward-dynamics contract ready for trainer implementation, and policy models such as OpenVLA/openpi/GR00T wait for robot-compatible action-target conversion.", + "Foundation-model selection is explicit: Qwen3-Omni is the structured JSON baseline, Cosmos 3 is the world-model branch with Nano compatibility and Super forward-dynamics LoRA results, and policy models such as OpenVLA/openpi/GR00T wait for robot-compatible action-target conversion.", "Future model branches should be added through the backbone registry and verified package contract, not as one-off result folders with incompatible metrics or publication rules.", "The Xperience Embodied Foundation Model is a future native-pretraining goal, not a completed model or current benchmark." ] diff --git a/docs/data/public_surface_qa.json b/docs/data/public_surface_qa.json index 50cce43771c4a120aa42bbae8fddcf22ec7b0bf8..b2935376226b7ab6f69c896fb1c1cbf34226d56c 100644 --- a/docs/data/public_surface_qa.json +++ b/docs/data/public_surface_qa.json @@ -1,7 +1,7 @@ { "title": "Ropedia Xperience-10M Public Project Surface", "status": "pass", - "generated_at_utc": "2026-06-04T16:48:58+00:00", + "generated_at_utc": "2026-06-08T07:13:54+00:00", "scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.", "checks": [ { @@ -18,7 +18,7 @@ "website_integrity": { "exists": true, "status": "pass", - "generated_at_utc": "2026-06-04T16:42:53+00:00" + "generated_at_utc": "2026-06-08T06:57:50+00:00" }, "rendered_site_check": { "exists": true, @@ -28,27 +28,27 @@ "task_surface_integrity": { "exists": true, "status": "pass", - "generated_at_utc": "2026-06-03T20:36:23+00:00" + "generated_at_utc": "2026-06-07T15:47:30+00:00" }, "source_alignment": { "exists": true, "status": "pass", - "generated_at_utc": "2026-06-04T16:42:48+00:00" + "generated_at_utc": "2026-06-04T16:48:58+00:00" }, "scale_up_status": { "exists": true, "status": "pass", - "generated_at_utc": "2026-06-04T16:42:49+00:00" + "generated_at_utc": "2026-06-08T06:57:51+00:00" }, "publication_package": { "exists": true, "status": "pass", - "generated_at_utc": "2026-06-04T16:42:56+00:00" + "generated_at_utc": "2026-06-08T06:59:58+00:00" }, "mirror_parity": { "exists": true, "status": "pass", - "generated_at_utc": "2026-06-04T16:34:37+00:00" + "generated_at_utc": "2026-06-08T07:00:45+00:00" }, "live_publication": { "exists": true, @@ -81,7 +81,7 @@ "marker_counts": { "role=\"tablist\"": 3, "role=\"tab\"": 10, - "role=\"tabpanel\"": 25, + "role=\"tabpanel\"": 26, "aria-selected": 13, "aria-controls": 11, "moveProjectTabFocus": 2, @@ -101,10 +101,10 @@ "reason": "Public copy should consistently present the project as Ropedia Xperience-10M, with the Qwen3-Omni scale-up status.", "marker_counts": { "Ropedia Xperience-10M Task Suite": 15, - "Xperience-10M": 142, - "12-task": 33, - "Qwen3-Omni": 108, - "128-episode pilot": 11 + "Xperience-10M": 149, + "12-task": 32, + "Qwen3-Omni": 142, + "128-episode pilot": 1 } }, { @@ -112,12 +112,12 @@ "status": "pass", "reason": "Public cards should link the repo, Space, artifacts, model baselines, upstream dataset, and Ropedia dataset page.", "marker_counts": { - "https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite": 66, - "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite": 8, - "https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts": 4, - "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines": 4, - "https://huggingface.co/datasets/ropedia-ai/xperience-10m": 26, - "https://ropedia.com/dataset": 4 + "https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite": 78, + "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite": 10, + "https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts": 7, + "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines": 10, + "https://huggingface.co/datasets/ropedia-ai/xperience-10m": 28, + "https://ropedia.com/dataset": 5 } }, { @@ -125,14 +125,14 @@ "status": "pass", "reason": "Readers should be able to find website reference, release package, mirror, and public presentation files from public copy.", "marker_counts": { - "data/project_brief.json": 9, - "data/website_integrity.json": 13, - "data/rendered_site_check.json": 8, - "data/task_surface_integrity.json": 23, - "data/publication_audit.json": 18, - "data/mirror_parity.json": 12, - "data/public_surface_qa.json": 12, - "data/research_roadmap.json": 23 + "data/project_brief.json": 8, + "data/website_integrity.json": 2, + "data/rendered_site_check.json": 2, + "data/task_surface_integrity.json": 11, + "data/publication_audit.json": 2, + "data/mirror_parity.json": 2, + "data/public_surface_qa.json": 2, + "data/research_roadmap.json": 11 } }, { diff --git a/docs/data/publication_audit.json b/docs/data/publication_audit.json index 022a52bcdf9d5adce96b42b54bb01f8b9517e4da..8fa1b427d8b8f0444c9fea6a3d668b0063ad554c 100644 --- a/docs/data/publication_audit.json +++ b/docs/data/publication_audit.json @@ -1,6 +1,6 @@ { "status": "pass", - "generated_at_utc": "2026-06-07T23:40:56+00:00", + "generated_at_utc": "2026-06-08T07:14:01+00:00", "checks": [ { "name": "required_publication_assets_present", @@ -182,8 +182,8 @@ "github_repo": { "root": "repo", "exists": true, - "file_count": 745, - "text_file_count": 624, + "file_count": 831, + "text_file_count": 680, "largest_file": { "path": "tmp/omni_128_dataset_fetch/dataset.jsonl", "bytes": 582271586 @@ -193,8 +193,8 @@ "hf_space_bundle": { "root": "hf_publish/space", "exists": true, - "file_count": 603, - "text_file_count": 499, + "file_count": 634, + "text_file_count": 520, "largest_file": { "path": "results/episode_task_suite/modality_reconstruction/predictions.npz", "bytes": 55702978 @@ -204,8 +204,8 @@ "hf_artifact_bundle": { "root": "hf_publish/artifacts", "exists": true, - "file_count": 787, - "text_file_count": 659, + "file_count": 818, + "text_file_count": 680, "largest_file": { "path": "results/episode_task_suite/modality_reconstruction/predictions.npz", "bytes": 55702978 @@ -215,8 +215,8 @@ "hf_model_bundle": { "root": "hf_publish/model", "exists": true, - "file_count": 975, - "text_file_count": 812, + "file_count": 1006, + "text_file_count": 833, "largest_file": { "path": "pytorch_model.bin", "bytes": 93495480 diff --git a/docs/data/quality_gates.json b/docs/data/quality_gates.json index 240bb2d92723f52aabc16f51a7be78856ca9738b..7f3bc8b9ad0d35038f438a37ca2beaf4a2cb99e3 100644 --- a/docs/data/quality_gates.json +++ b/docs/data/quality_gates.json @@ -1,7 +1,7 @@ { "title": "Ropedia Xperience-10M Release Checks", "status": "pass", - "generated_at_utc": "2026-06-04T07:39:12+00:00", + "generated_at_utc": "2026-06-08T07:14:19+00:00", "rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.", "automated_gates": [ { @@ -154,7 +154,7 @@ "command": "python scripts/validate_mirror_parity.py", "report": "docs/data/mirror_parity.json", "blocks_if": "Prepared HF Space, artifact dataset, or model bundle diverges from the repo for critical files.", - "shows": "The files prepared for GitHub and Hugging Face are synchronized before upload.", + "shows": "The files staged for GitHub and Hugging Face are synchronized before upload.", "current_report": { "exists": true, "status": "pass" diff --git a/docs/data/research_roadmap.json b/docs/data/research_roadmap.json index 7cbde461ba304c3521e3fb81558bc7acd649bf34..1a54e3621e04c347b31a86b740d1769d5a72897d 100644 --- a/docs/data/research_roadmap.json +++ b/docs/data/research_roadmap.json @@ -1,7 +1,7 @@ { "title": "Ropedia Xperience-10M Research Roadmap", - "summary": "Staged path from the public-sample task lab to a final verified Qwen3-Omni diagnostic result, same-split 128-episode baseline alignment, action/subtask error analysis, foundation-model selection, world/policy branches, and a future Xperience-native embodied foundation model.", - "current_decision_point": "Keep the public-sample task suite as the development harness, use the final verified selected-episode Qwen3-Omni diagnostic result and the same-split 128-episode simple/NN metadata baselines as the first cross-episode references, improve action/subtask quality through error analysis, then branch into Cosmos 3 world modeling and policy-model experiments after their targets are implemented. The Xperience Embodied Foundation Model is a later full-corpus pretraining goal, not a current result.", + "summary": "Staged path from the public-sample task lab to verified Qwen3-Omni, Cosmos3-Nano, and Cosmos3-Super diagnostics, same-split 128-episode baseline alignment, action/subtask error analysis, world/policy branches, and a future Xperience-native embodied foundation model.", + "current_decision_point": "Keep the public-sample task suite as the development harness, use the final verified selected-episode Qwen3-Omni diagnostic result and same-split 128-episode simple/NN metadata baselines as structured-task references, read Cosmos3-Nano and Cosmos3-Super Forward-Dynamics LoRA as separate world-model results, improve action/subtask quality through error analysis, and defer policy-model experiments until robot-compatible targets are implemented. The Xperience Embodied Foundation Model is a later full-corpus pretraining goal, not a current result.", "additional_development_directions": { "source_document": "ADDITIONAL_DEVELOPMENT_DIRECTIONS.md", "source_json": "docs/data/additional_development_directions.json", @@ -119,11 +119,12 @@ { "id": "foundation_model_selection_matrix", "name": "Foundation-Model Selection Matrix", - "status": "next", + "status": "current", "entry_condition": "The selected episodes are prepared or a 3-8 episode dry run is available for preprocessing checks.", "deliverables": [ "backbone registry", "Cosmos 3 world-model branch plan", + "Cosmos3-Super Forward-Dynamics LoRA verified package", "Qwen3-Omni LoRA baseline plan", "OpenVLA/openpi/GR00T policy-branch candidates", "model-specific evaluation additions" @@ -133,12 +134,12 @@ "docs/data/foundation_model_plan.json", "research_roadmap_interactive.json" ], - "reader_takeaway": "Qwen3-Omni remains the first trainable held-out pilot; Cosmos 3 is the first world-model branch. Cosmos3-Super now has camera-pose proxy forward-dynamics targets ready for trainer implementation, while VLA/policy models wait for robot-compatible action targets." + "reader_takeaway": "Qwen3-Omni remains the structured JSON held-out pilot; Cosmos 3 is the first world-model branch. Cosmos3-Super now has a verified forward-dynamics LoRA over camera-pose proxy targets, while VLA/policy models wait for robot-compatible action targets." }, { "id": "robustness_run_64_128_episode", "name": "64-128 Episode Robustness Run", - "status": "planned", + "status": "partially_implemented", "entry_condition": "The selected-episode pilot trains and evaluates cleanly.", "deliverables": [ "split-by-session metrics", @@ -161,7 +162,7 @@ "status": "planned", "entry_condition": "Enough multi-episode data, compute budget, and model-specific action/world-state targets.", "deliverables": [ - "Cosmos 3 future-window or action-conditioned world-model probe", + "Cosmos 3 future-window and action-conditioned world-model probes", "OpenVLA/openpi/GR00T action-policy baseline", "audio/video/depth/pose/mocap conditioning checks", "affordance and object-interaction tasks", @@ -169,10 +170,11 @@ ], "completion_evidence": [ "task-specific held-out evaluations", + "verified Cosmos3-Super forward-dynamics LoRA package", "qualitative inspection", "updated model cards" ], - "reader_takeaway": "The long-term direction is richer multimodal representation learning for embodied-AI reasoning, with model branches chosen by task fit rather than by a single default backbone." + "reader_takeaway": "The Cosmos branch now includes Nano future-window compatibility and Super forward-dynamics LoRA; the long-term direction remains richer multimodal representation learning with model branches chosen by task fit rather than by a single default backbone." }, { "id": "xperience_embodied_foundation_pretraining", diff --git a/docs/data/research_roadmap_interactive.json b/docs/data/research_roadmap_interactive.json index 36a0319a690cf0bb7faeb3eae62a22cde3407beb..1eb4f1155730fe699278013d2843d03f0c419fc0 100644 --- a/docs/data/research_roadmap_interactive.json +++ b/docs/data/research_roadmap_interactive.json @@ -2040,12 +2040,12 @@ "step": 2 }, { - "action": "Run 3-8 episode dry runs for Qwen3-Omni prompt/LoRA, Cosmos 3 preprocessing, and one policy candidate.", + "action": "Run 3-8 episode dry runs for any next backbone before scaling beyond the selected split.", "name": "Model-selection dry run", "step": 3 }, { - "action": "Promote Cosmos 3 if future-window/action-conditioned preprocessing fits storage and compute.", + "action": "Promote Cosmos 3 beyond the current Nano compatibility and Super forward-dynamics runs only when loss metrics, preprocessing, and storage justify the added compute.", "name": "World-model branch", "step": 4 }, @@ -2084,8 +2084,8 @@ { "best_role": "Embodied world modeling, action generation, future-window prediction, and synthetic-data expansion.", "category": "world_foundation_model", - "current_decision": "add_as_first_world_model_branch_after_data_gate", - "entry_condition": "Multi-episode data plus enough storage/compute for generated or latent video-state outputs.", + "current_decision": "implemented_as_nano_future_window_and_super_forward_dynamics_branches", + "entry_condition": "Use separate metrics for Nano future-window retrieval and Super forward-dynamics MSE; do not compare them directly to Qwen JSON-task accuracy.", "family": "Cosmos 3", "openness": "track_official_nvidia_release_and_available_weights", "priority": 2, @@ -2222,7 +2222,7 @@ ], "status": "planning_artifact" }, - "generated_at_utc": "2026-06-06T23:26:13+00:00", + "generated_at_utc": "2026-06-08T06:50:10+00:00", "omni_plan": { "adapter": "LoRA rank 16, alpha 32, dropout 0.05", "backbone": "Qwen/Qwen3-Omni-30B-A3B-Instruct", @@ -2362,6 +2362,7 @@ "deliverables": [ "backbone registry", "Cosmos 3 world-model branch plan", + "Cosmos3-Super Forward-Dynamics LoRA verified package", "Qwen3-Omni LoRA baseline plan", "OpenVLA/openpi/GR00T policy-branch candidates", "model-specific evaluation additions" @@ -2369,9 +2370,9 @@ "entry_condition": "The selected episodes are prepared or a 3-8 episode dry run is available for preprocessing checks.", "id": "foundation_model_selection_matrix", "name": "Foundation-Model Selection Matrix", - "reader_takeaway": "Qwen3-Omni remains the first trainable held-out pilot; Cosmos 3 is the first world-model branch. Cosmos3-Super now has camera-pose proxy forward-dynamics targets ready for trainer implementation, while VLA/policy models wait for robot-compatible action targets.", - "stage": "omni", - "status": "next" + "reader_takeaway": "Qwen3-Omni remains the structured JSON held-out pilot; Cosmos 3 is the first world-model branch. Cosmos3-Super now has a verified forward-dynamics LoRA over camera-pose proxy targets, while VLA/policy models wait for robot-compatible action targets.", + "stage": "future", + "status": "current" }, { "completion_evidence": [ @@ -2392,16 +2393,17 @@ "name": "64-128 Episode Robustness Run", "reader_takeaway": "The robustness run tests whether the pilot conclusions survive broader sessions and missing modalities.", "stage": "future", - "status": "planned" + "status": "partially_implemented" }, { "completion_evidence": [ "task-specific held-out evaluations", + "verified Cosmos3-Super forward-dynamics LoRA package", "qualitative inspection", "updated model cards" ], "deliverables": [ - "Cosmos 3 future-window or action-conditioned world-model probe", + "Cosmos 3 future-window and action-conditioned world-model probes", "OpenVLA/openpi/GR00T action-policy baseline", "audio/video/depth/pose/mocap conditioning checks", "affordance and object-interaction tasks", @@ -2410,7 +2412,7 @@ "entry_condition": "Enough multi-episode data, compute budget, and model-specific action/world-state targets.", "id": "foundation_world_model_extensions", "name": "Cosmos 3 and Policy-Model Extensions", - "reader_takeaway": "The long-term direction is richer multimodal representation learning for embodied-AI reasoning, with model branches chosen by task fit rather than by a single default backbone.", + "reader_takeaway": "The Cosmos branch now includes Nano future-window compatibility and Super forward-dynamics LoRA; the long-term direction remains richer multimodal representation learning with model branches chosen by task fit rather than by a single default backbone.", "stage": "future", "status": "planned" }, diff --git a/docs/data/scope_claims_audit.json b/docs/data/scope_claims_audit.json index 7e208554e0a759ffba1bbc71b3e3e1b981ef6d4f..dde83b973a5fbdef689dd6f8f1d3b0161ea36089 100644 --- a/docs/data/scope_claims_audit.json +++ b/docs/data/scope_claims_audit.json @@ -1,6 +1,6 @@ { "status": "pass", - "generated_at_utc": "2026-06-07T15:47:31+00:00", + "generated_at_utc": "2026-06-08T07:13:56+00:00", "summary": { "qwen3_omni_verified_diagnostic_pilot": true, "dataset_manifest_num_episodes": 119, @@ -9,7 +9,7 @@ "eval_num_samples": 448, "eval_json_validity_rate": 1.0, "quality_target_met": true, - "historical_identifier_count": 1545, + "historical_identifier_count": 1619, "public_32_episode_status_file_count": 1, "failure_count": 0 }, @@ -25,7 +25,7 @@ { "name": "summary_metrics_preserves_verified_diagnostic_status", "status": "pass", - "detail": "The selected-episode Qwen3-Omni diagnostic pilot is verified on the 96/16/16 split and now meets the 98% target for JSON validity; action/subtask quality remains weak, so current results are diagnostic baselines, not strong model-quality claims.", + "detail": "The selected-episode Qwen3-Omni diagnostic pilot is verified on the 96/16/16 split and meets the 98% target for JSON validity; action/subtask quality remains weak, so it is a structured-task baseline. Cosmos3-Nano future-window compatibility and Cosmos3-Super Forward-Dynamics LoRA are also verified as separate world-model diagnostics with different metrics.", "evidence": [ "docs/data/summary_metrics.json" ] @@ -84,7 +84,7 @@ { "name": "historical_32ep_identifiers_are_confined_to_readiness_artifacts", "status": "pass", - "detail": "historical identifiers found in result provenance files=1545", + "detail": "historical identifiers found in result provenance files=1619", "evidence": [ "results/omni_finetune/" ] @@ -424,6 +424,6 @@ "example": "{\"id\": \"xperience-10m-sample:qa:53\", \"episode_id\": \"xperience-10m-sample\", \"split\": \"train\", \"target\": \"episode_qa\", \"prompt_type\": \"json_episode_understanding\", \"center_window\": {\"start_frame\": 1060, \"end_frame\": 1079, \"num_frames\": 20}, \"media\": {\"video_path" } ], - "historical_identifier_total_count": 1545, + "historical_identifier_total_count": 1619, "failures": [] } diff --git a/docs/data/summary_metrics.json b/docs/data/summary_metrics.json index e0da4f105545f3a72d67569c4ec0e1935935bcb9..d440c4b979cb2aea326b02e05b350fac2c976c8b 100644 --- a/docs/data/summary_metrics.json +++ b/docs/data/summary_metrics.json @@ -14,7 +14,7 @@ "visualization.rrd" ], "access_status": "The gated Xperience-10M dataset is available for selected multi-episode pilot preparation.", - "current_scope": "The selected-episode Qwen3-Omni diagnostic pilot is verified on the 96/16/16 split and now meets the 98% target for JSON validity; action/subtask quality remains weak, so current results are diagnostic baselines, not strong model-quality claims." + "current_scope": "The selected-episode Qwen3-Omni diagnostic pilot is verified on the 96/16/16 split and meets the 98% target for JSON validity; action/subtask quality remains weak, so it is a structured-task baseline. Cosmos3-Nano future-window compatibility and Cosmos3-Super Forward-Dynamics LoRA are also verified as separate world-model diagnostics with different metrics." }, "models": { "motion_action": { diff --git a/docs/data/website_integrity.json b/docs/data/website_integrity.json index 6a4457fb8274b85480a9a540782841b136d764c7..0f48e2b3ba9139da8c320e1c65855360768873d2 100644 --- a/docs/data/website_integrity.json +++ b/docs/data/website_integrity.json @@ -1,12 +1,12 @@ { "status": "pass", - "generated_at_utc": "2026-06-07T23:40:56+00:00", + "generated_at_utc": "2026-06-08T07:13:56+00:00", "docs_root": "docs", "site_base": "/ropedia-xperience-10m-task-suite/", "summary": { "html_pages": 4, - "local_references": 137, - "external_reference_count": 106, + "local_references": 136, + "external_reference_count": 107, "json_files": 35, "image_assets_referenced": 22, "failure_count": 0 @@ -75,7 +75,7 @@ "status": "pass", "reason": "The project overview should appear before the deeper progress ledger.", "overview_index": 67412, - "evidence_index": 90659 + "evidence_index": 90718 }, { "name": "project_status_links_json", @@ -140,8 +140,8 @@ "verified_baseline", "verified_companion_result", "active_next_step", - "next", - "planned", + "current", + "partially_implemented", "planned", "future" ], @@ -153,8 +153,8 @@ "status": "pass", "reason": "The evaluation protocol should appear before the deeper evidence ledger.", "overview_index": 67412, - "protocol_index": 87218, - "evidence_index": 90659 + "protocol_index": 87277, + "evidence_index": 90718 }, { "name": "evaluation_protocol_links_json", @@ -228,7 +228,7 @@ { "path": "index.html", "id_count": 77, - "reference_count": 114, + "reference_count": 113, "image_count": 24 }, { @@ -252,7 +252,7 @@ }, { "path": "data/artifact_index.json", - "bytes": 67401, + "bytes": 75435, "top_level_type": "dict" }, { @@ -282,7 +282,7 @@ }, { "path": "data/foundation_model_plan.json", - "bytes": 13193, + "bytes": 13457, "top_level_type": "dict" }, { @@ -292,7 +292,7 @@ }, { "path": "data/mirror_parity.json", - "bytes": 352006, + "bytes": 408299, "top_level_type": "dict" }, { @@ -302,12 +302,12 @@ }, { "path": "data/omni_finetune_verified_result.json", - "bytes": 3768, + "bytes": 3724, "top_level_type": "dict" }, { "path": "data/omni_model_comparison.json", - "bytes": 56941, + "bytes": 62577, "top_level_type": "dict" }, { @@ -322,27 +322,27 @@ }, { "path": "data/project_packet.json", - "bytes": 8098, + "bytes": 8656, "top_level_type": "dict" }, { "path": "data/project_status.json", - "bytes": 18062, + "bytes": 19360, "top_level_type": "dict" }, { "path": "data/public_surface_qa.json", - "bytes": 5591, + "bytes": 5588, "top_level_type": "dict" }, { "path": "data/publication_audit.json", - "bytes": 7212, + "bytes": 7213, "top_level_type": "dict" }, { "path": "data/quality_gates.json", - "bytes": 8099, + "bytes": 8097, "top_level_type": "dict" }, { @@ -367,12 +367,12 @@ }, { "path": "data/research_roadmap.json", - "bytes": 10246, + "bytes": 10502, "top_level_type": "dict" }, { "path": "data/research_roadmap_interactive.json", - "bytes": 143673, + "bytes": 144016, "top_level_type": "dict" }, { @@ -382,7 +382,7 @@ }, { "path": "data/scope_claims_audit.json", - "bytes": 21251, + "bytes": 21365, "top_level_type": "dict" }, { @@ -397,7 +397,7 @@ }, { "path": "data/summary_metrics.json", - "bytes": 27490, + "bytes": 27604, "top_level_type": "dict" }, { @@ -412,7 +412,7 @@ }, { "path": "data/website_integrity.json", - "bytes": 15375, + "bytes": 15393, "top_level_type": "dict" }, { diff --git a/docs/index.html b/docs/index.html index 7e491c87e849b39095687b62163f78eec3c9a965..a16950ebd3283e00e2d21bfed6a3a8125941aa32 100644 --- a/docs/index.html +++ b/docs/index.html @@ -2236,7 +2236,7 @@
What comes next -

The next model-quality stage is a held-out episode pilot over selected multi-episode data, with no train/test episode leakage and a completed omni-model evaluation report.

+

The next model-quality stage is stronger action/subtask modeling on the same held-out split, plus policy-compatible action targets beyond the verified Qwen3-Omni and Cosmos3 diagnostics.

@@ -2254,7 +2254,7 @@
Scale-up readiness -

Connects the same data contract to 32/128-episode held-out pilots, Qwen3-Omni LoRA, Cosmos-style world modeling, policy-model branches, and the later Xperience-native pretraining goal.

+

Connects the same data contract to 128-episode baselines, Qwen3-Omni LoRA, Cosmos-style world modeling, policy-model branches, and the later Xperience-native pretraining goal.

@@ -2314,7 +2314,7 @@
verified

Public research artifacts

-

Metrics, figures, walkthroughs, baseline weights, and the Qwen3-Omni pilot status are packaged across GitHub, GitHub Pages, and Hugging Face.

+

Metrics, figures, walkthroughs, baseline weights, Qwen3-Omni results, and Cosmos3 public-safe packages are staged across GitHub, GitHub Pages, and Hugging Face.

tasks 12 baselines minimal + neural @@ -2406,8 +2406,8 @@ Evidence

Updated quality-target report, error-analysis tables, held-out metrics, and public-safe package.

-
- next +
+ current

Foundation-Model Selection Matrix

Keep Qwen3-Omni as the first trainable held-out pilot, use Cosmos 3 for world modeling and forward-dynamics trainer development, and stage policy candidates after robot-compatible action targets are explicit.

@@ -2415,8 +2415,8 @@ Evidence

Foundation model plan, source links, model-specific entry conditions, and evaluation additions.

-
- planned +
+ partially implemented

64-128 Episode Robustness Run

Test whether pilot conclusions survive broader sessions, missing modalities, and stronger ablations.

@@ -2489,7 +2489,7 @@

Leakage controls

Scalers fit on train windows only; future labels, target-side signals, caption/object labels, and contact labels stay on the target side unless explicitly queried.

builder script

Audio ablation

Audio and no-audio variants are evaluated across all 12 task contracts under the same chronological split.

audio summary

Foundation branch selection

Qwen3-Omni is the first trainable baseline, Cosmos 3 becomes the world-model branch with a camera-pose proxy forward-dynamics contract ready for trainer work, policy models wait for robot-compatible action targets, and Xperience-native pretraining remains a later full-corpus goal.

backbone plan
-

Next evaluation stage

This public-sample run covers single-episode task development. The selected multi-episode Qwen3-Omni final diagnostic result is verified and meets the JSON-validity target; Cosmos3-Nano has a verified future-window compatibility package; and Cosmos3-Super has a verified base-weight JSON-task evaluation plus a camera-pose forward-dynamics contract audit. The next stage is action/subtask error analysis, true Cosmos fine-tuning, and policy-target conversion.

result comparison
+

Next evaluation stage

This public-sample run covers single-episode task development. The selected multi-episode Qwen3-Omni final diagnostic result is verified and meets the JSON-validity target; Cosmos3-Nano has a verified future-window compatibility package; and Cosmos3-Super has a verified base-weight JSON-task evaluation plus a fine-tuned forward-dynamics LoRA branch. The next stage is action/subtask error analysis, stronger model-quality runs, and policy-target conversion.

result comparison

Scale-up requirement

Future Omni, Cosmos, and policy branches use the same episode split discipline, training metadata, held-out predictions, metrics, run report, and public-safe package gate.

scale-up status
@@ -2552,7 +2552,7 @@
verified diagnostic

Qwen3-Omni and Cosmos3 branches

-

The selected 96/16/16 episode split produced verified Qwen3-Omni packages with 448 held-out test predictions. Cosmos3-Nano has 378 held-out future-window predictions, and Cosmos3-Super Reasoner has 448 held-out base-weight JSON-task predictions plus a camera-pose forward-dynamics contract audit.

+

The selected 96/16/16 episode split produced verified Qwen3-Omni packages with 448 held-out test predictions. Cosmos3-Nano has 378 held-out future-window predictions, Cosmos3-Super Reasoner has 448 held-out base-weight JSON-task predictions, and Cosmos3-Super Forward-Dynamics LoRA has 448 held-out loss records.

result comparison pilot result @@ -3160,7 +3160,7 @@

Foundation-model plan

Backbone selection matrix covering Qwen3-Omni, Cosmos 3, GR00T, OpenVLA/openpi, Gemini Robotics, Octo, SmolVLA-style policy candidates, and the future Xperience-native pretraining goal.

foundation model plan

Multi-episode data access

Public data-access path, selected 128-episode pilot plan, and preparation requirements.

data access

Qwen3-Omni LoRA group

Separates the 1-episode sensor-adapter smoke test from the current 128-episode LoRA adapter package and older diagnostics.

Qwen group
-

Cosmos3 groups

Shows the verified Nano future-window compatibility package, the Super base-weight Reasoner JSON-task evaluation, and the Super camera-pose forward-dynamics contract audit; none is a new fine-tuned Cosmos weight release.

Cosmos groups
+

Cosmos3 groups

Shows the verified Nano future-window compatibility package, the Super base-weight Reasoner JSON-task evaluation, and the Super fine-tuned forward-dynamics LoRA branch with separate loss metrics.

Cosmos groups

Scale-up requirement

Future runs need validation tracking, held-out predictions, quality-target reporting, and the same public-safe package gate.

training requirements

Xperience-native pretraining

Future plan for a domain-specific embodied foundation model trained from scratch over full-corpus video, audio, geometry, motion, inertial, and language streams.

pretraining plan
@@ -3198,7 +3198,7 @@

Selection

128 complete episodes selected from 128 unique top-level sessions, balanced across episode-size bands and split 96/16/16 for train/val/test.

Transfer

Download raw episodes only from official gated sources, exclude visualization.rrd, validate files, then stage them for training.

Current LoRA artifact

The current Qwen3-Omni LoRA artifact is the selected 128-episode diagnostic adapter. The 1-episode Qwen entry is only a sensor-adapter smoke test.

model groups
-

Backbone branches

Qwen3-Omni uses a separate LoRA model repo; Cosmos3-Nano and Cosmos3-Super remain artifacts-only diagnostics until real Cosmos adapter or fine-tuned weights exist.

backbone plan
+

Backbone branches

Qwen3-Omni uses a separate LoRA model repo; Cosmos3-Nano remains a compatibility package; Cosmos3-Super now has a verified forward-dynamics LoRA branch with weights in a dedicated model repo.

Cosmos3-Super weights

Native foundation model

The long-term goal is a full-corpus Xperience Embodied Foundation Model trained on synchronized perception, geometry, motion, inertial, audio, and language streams after smaller scaling stages validate the approach.

pretraining plan
@@ -3250,7 +3250,7 @@ python scripts/validate_publication_package.py diff --git a/results/omni_finetune/OMNI_MODEL_COMPARISON.md b/results/omni_finetune/OMNI_MODEL_COMPARISON.md index ab9bf548ed838ad59fd8867d87f4ab2e40003b01..9638c9e0531a1015fb7e8215ad753b0f89ede7ff 100644 --- a/results/omni_finetune/OMNI_MODEL_COMPARISON.md +++ b/results/omni_finetune/OMNI_MODEL_COMPARISON.md @@ -1,6 +1,6 @@ # Omni Model Comparison -Generated: `2026-06-07T23:37:45+00:00` +Generated: `2026-06-08T07:13:32+00:00` Compare only rows with the same scope and target. Single-episode raw-feature metrics, 128-episode metadata baselines, Qwen3 structured JSON metrics, and the two Cosmos3 targets answer different questions: Nano future-window retrieval versus Super structured JSON Reasoner evaluation. @@ -16,7 +16,7 @@ Read the three rows this way: - Version 1 is the public-sample 12-task harness with minimal and neural heads. - Version 2 is the selected 128-episode same-split simple/NN baseline alignment. -- Version 3 is the verified model-branch layer: the current final Qwen3-Omni LoRA package is the JSON-task diagnostic result, Cosmos3-Nano is a future-window compatibility result, and Cosmos3-Super Reasoner is a base-weight JSON-task evaluation; Cosmos3-Super has a camera-pose forward-dynamics contract audit and schema-only packer smoke, but no new fine-tuned weight release. +- Version 3 is the verified model-branch layer: the current final Qwen3-Omni LoRA package is the JSON-task diagnostic result, Cosmos3-Nano is a future-window compatibility result, Cosmos3-Super Reasoner is a base-weight JSON-task evaluation, and Cosmos3-Super Forward-Dynamics LoRA is the first Super fine-tuned adapter branch. ## Model-Family Grouped View @@ -24,7 +24,7 @@ Read the three rows this way: - Task-head baselines have both a one-episode public-sample run and a 128-episode same-split metadata/text run. - Qwen3-Omni has a one-episode sensor-adapter smoke test and separate 128-episode LoRA diagnostic packages; the newest verified full-eval 128-episode adapter belongs in the Qwen LoRA model repo. - Cosmos3-Nano has a 128-episode future-window compatibility package. -- Cosmos3-Super has a 128-episode base-weight Reasoner evaluation on the JSON task plus a camera-pose forward-dynamics contract audit; create a separate Cosmos model repo only after a trainable multi-GPU/offload run produces real Cosmos adapter or fine-tuned weights. +- Cosmos3-Super now has both a 128-episode base-weight Reasoner evaluation on the JSON task and a fine-tuned forward-dynamics LoRA branch over camera-pose proxy targets. ### Minimal and Neural Task Heads @@ -45,7 +45,7 @@ The one-episode Qwen entry is only a sensor-adapter smoke test with Qwen3 weight | scope | status | run | counts | metrics | source | | --- | --- | --- | --- | --- | --- | -| 1 episode | verified_smoke | Qwen3-Omni Sensor-Adapter Smoke | 1 episodes, 59 windows/samples | accuracy=0.0000, macro_f1=0.0000 | `results/omni_exploration/qwen3_adapter_smoke/metrics.json` | +| 1 episode | verified_smoke | Qwen3-Omni Sensor-Adapter Smoke | 1 episodes, 59 windows/samples | train_final_loss=1.4479, accuracy=0.0000, macro_f1=0.0000 | `results/omni_exploration/qwen3_adapter_smoke/metrics.json` | | 128 episode | verified | Qwen3-Omni LoRA | 119 episodes, 3808 windows/samples, 448 eval | json_validity_rate=0.8750, action_macro_f1=0.0027, transition_accuracy=0.8504, contact_accuracy=0.6451 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_eval/verified_result_summary.json` | | 128 episode | verified | Qwen3-Omni LoRA | 119 episodes, 3808 windows/samples, 448 eval | json_validity_rate=0.8527, action_macro_f1=0.0021, transition_accuracy=0.8281, contact_accuracy=0.6518 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_fullsplit_fast8gpu_lora_fsdp_full_train_noval_tail_logits_fullstatesave_v6_eval_test_full/verified_result_summary.json` | | 128 episode | verified | Qwen3-Omni LoRA | 119 episodes, 3808 windows/samples, 448 eval | json_validity_rate=0.9978, action_macro_f1=0.0024, transition_accuracy=0.9710, contact_accuracy=0.7188 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v2_reuse_full8gpu_lora_eval_test_full/verified_result_summary.json` | @@ -65,7 +65,7 @@ The current 128-episode Cosmos result is a public-safe future-window compatibili ### Cosmos3-Super Reasoner -Cosmos3-Super is now represented by a verified 448-window held-out Reasoner evaluation on the same JSON task as Qwen3. It uses staged base weights through vLLM, so it is a model-branch diagnostic, not a weight release. A camera-pose proxy forward-dynamics target export now passes the contract audit and schema-only packer smoke; true Cosmos3-Super fine-tuning is still blocked until a trainable multi-GPU/offload path produces adapter or fine-tuned weights. +Cosmos3-Super is now represented by a verified 448-window held-out Reasoner evaluation on the same JSON task as Qwen3. It uses staged base weights through vLLM, so it is a model-branch diagnostic, not a weight release. A camera-pose proxy forward-dynamics target export now passes the contract audit and schema-only packer smoke; the separate Forward-Dynamics LoRA group records the trainable adapter run and loss-based held-out evaluation. - Weight repo policy: none for this run; staged base weights only, no new fine-tuned weights @@ -77,6 +77,17 @@ Cosmos3-Super is now represented by a verified 448-window held-out Reasoner eval | batch packer | pass | Cosmos3-Super Action Batch Packer Smoke | 1 windows/samples | mode=forward_dynamics, loss_surface=vision_velocity_conditioned_on_camera_pose, pipeline_loaded=False, weights_updated=False | `results/omni_finetune/xperience10m_cosmos3_super_action_packer_schema_smoke_20260608/packer_summary.json` | | 128 episode | verified current | Cosmos3-Super Reasoner | 119 episodes, 3808 windows/samples, 448 eval | json_validity_rate=0.5112, action_macro_f1=0.0008, transition_accuracy=0.3683, contact_accuracy=0.3214 | `results/omni_finetune/verified_public/xperience10m_cosmos3_super_reasoner_128ep_test_full_20260607/verified_result_summary.json` | +### Cosmos3-Super Forward-Dynamics LoRA + +This is the first verified Cosmos3-Super fine-tuned adapter branch. Its metric is forward-dynamics MSE, so compare it to world-model loss or future-prediction targets, not to Qwen JSON classification accuracy. + +- Weight repo policy: https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep + +| scope | status | run | counts | metrics | source | +| --- | --- | --- | --- | --- | --- | +| 1 episode | verified_smoke | Cosmos3-Super Forward-Dynamics Overfit Smoke | | | `results/omni_finetune/xperience10m_cosmos3_super_forward_dynamics_lora_overfit_after_qwen_v4_20260608_fsdp8_attn256_gradfix_savefix2/` | +| 128 episode | verified current | Cosmos3-Super Forward-Dynamics LoRA | 119 episodes, 3808 windows/samples, 448 eval | test_forward_dynamics_mse=3.6853, val_forward_dynamics_mse=4.0082, train_final_loss=1.0785, adapter_parameter_numel=26214400 | `results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/verified_result_summary.json` | + ## 128-Episode Task Baselines | task | simple | neural | @@ -99,6 +110,7 @@ Cosmos3-Super is now represented by a verified 448-window held-out Reasoner eval | branch | backbone | eval samples | held-out episodes | key metrics | | --- | --- | ---: | ---: | --- | | Cosmos3-Nano Future-Window World Model | `cosmos_world_model` | 378 | 14 | future_retrieval_mrr=0.0221, temporal_consistency=0.0952, transition_accuracy=0.9683, contact_accuracy=0.7434 | +| Cosmos3-Super Forward-Dynamics LoRA | `cosmos3_super_forward_dynamics` | 448 | 14 | adapter_parameter_numel=26214400, test_forward_dynamics_mse=3.6853, train_final_loss=1.0785, val_forward_dynamics_mse=4.0082 | | Cosmos3-Super Reasoner | `cosmos3_super_reasoner` | 448 | 14 | json_validity_rate=0.5112, action_macro_f1=0.0008, transition_accuracy=0.3683, contact_accuracy=0.3214 | | Qwen3-Omni LoRA | `qwen3_omni_lora` | 448 | 14 | json_validity_rate=0.8750, action_macro_f1=0.0027, transition_accuracy=0.8504, contact_accuracy=0.6451 | | Qwen3-Omni LoRA | `qwen3_omni_lora` | 448 | 14 | json_validity_rate=0.8527, action_macro_f1=0.0021, transition_accuracy=0.8281, contact_accuracy=0.6518 | @@ -109,4 +121,4 @@ Cosmos3-Super is now represented by a verified 448-window held-out Reasoner eval ## Pending - Use the verified Qwen3 v4 4-epoch full-eval package as the current Qwen row; older Qwen package rows remain historical diagnostics for comparison. -- Promote Cosmos3 from Nano compatibility, Super base-weight evaluation, and the camera-pose forward-dynamics contract to true fine-tuning only after a trainable Cosmos3-Super run produces new weights. +- Verify the live Cosmos3-Super forward-dynamics adapter model repo after upload; the public-safe verified_public package still excludes safetensors by design. diff --git a/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/PUBLIC_RESULT_SUMMARY.md b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/PUBLIC_RESULT_SUMMARY.md new file mode 100644 index 0000000000000000000000000000000000000000..3d4fae20be92a8207c0b18f7a2fd8ad774bdd22d --- /dev/null +++ b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/PUBLIC_RESULT_SUMMARY.md @@ -0,0 +1,17 @@ +# Cosmos3-Super Forward-Dynamics LoRA Result + +- Backbone: `cosmos3_super_forward_dynamics` +- Training run: `xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608` +- Evaluation run: `xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp` +- Status: `verified` +- Train rows: `2848` +- Val rows: `512` +- Test rows: `448` +- Train final loss: `1.0785235166549683` +- Val forward-dynamics MSE: `4.008244896889664` +- Test forward-dynamics MSE: `3.6853174321087345` +- Adapter parameters: `26214400` + +This is a camera-pose proxy forward-dynamics LoRA over Cosmos3-Super. It supervises future vision velocity tokens, not semantic JSON labels. + +Raw Xperience-10M media/annotations, base-model weights, LoRA adapter weights, checkpoints, and large archives are not included. diff --git a/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/dataset/dataset_manifest.json b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/dataset/dataset_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..5e29f896c1d498985c16b0945ddd0e50e226d7d3 --- /dev/null +++ b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/dataset/dataset_manifest.json @@ -0,0 +1,9694 @@ +{ + "run_id": "xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_dataset", + "dataset_path": "/results/omni_finetune/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_dataset/dataset.jsonl", + "num_samples": 3808, + "num_episodes": 119, + "split_counts": { + "train": 2848, + "val": 512, + "test": 448 + }, + "label_counts": { + "Fold paper strip": 84, + "Cut cardboard": 76, + "Manipulate paper strip": 51, + "Cut cardboard shape": 50, + "Draw line on cardboard": 29, + "Cut cardboard piece": 27, + "Place cardboard piece": 23, + "Pick up phone": 23, + "Sort beads": 23, + "Hold smartphone": 19, + "Pick up scissors": 18, + "Manipulate paper star": 18, + "Mark cardboard with pen": 17, + "Use phone": 17, + "Fold paper strip into lucky star": 17, + "Observe workspace": 17, + "Sort beads by color": 16, + "Reach for beads": 16, + "Pick up smartphone": 15, + "Mark cardboard piece": 15, + "Mark cardboard": 14, + "Trim cardboard piece": 14, + "Fold paper strip into star": 14, + "Place product on shelf": 13, + "Cut cardboard with scissors": 13, + "Pick up product": 12, + "Release paper strip": 12, + "Place item on shelf": 12, + "Hold paper strip": 12, + "Pick up container": 12, + "Cut cardboard square": 12, + "Pick up product from box": 11, + "Place can on shelf": 11, + "Place phone on desk": 11, + "Fold cardboard": 11, + "Use smartphone": 11, + "Move phone": 11, + "Reposition ruler": 11, + "Type on smartphone": 10, + "Draw lines on cardboard": 10, + "Pick up paper strip": 10, + "Fold paper star": 10, + "Hold product": 9, + "Cut cardboard with utility knife": 9, + "Approach desk": 9, + "Pick up utility knife": 9, + "Adjust item on shelf": 9, + "Adjust ruler position": 9, + "Approach workstation": 9, + "Cut cardboard triangle": 9, + "Cut cardboard strip": 9, + "Hold cardboard piece": 9, + "Marking cardboard piece": 9, + "Hold ruler and mark cardboard": 9, + "Grasp paper strip": 9, + "Place down scissors": 8, + "Continue folding paper strip": 8, + "Fold paper strip into knot": 8, + "Inflate paper star": 8, + "Pick up canned food": 8, + "Move towards shelf": 8, + "Move ruler": 8, + "Mark cardboard with marker": 8, + "Inspect jar": 8, + "Organize cardboard pieces": 8, + "Interact with smartphone": 8, + "Place scissors on table": 8, + "Arrange buttons": 8, + "Write on paper": 8, + "Write on notepad": 8, + "Writing on notepad": 8, + "Mark line on cardboard": 7, + "Reach for phone": 7, + "Walk towards table": 7, + "Place canned food on shelf": 7, + "Cut along the marked line": 7, + "Pick up can": 7, + "Adjust puzzle piece": 7, + "Carry cardboard piece": 7, + "Fold cardboard shape": 7, + "Arrange Mahjong tiles": 7, + "Cut newspaper": 7, + "Finish wiping and inspect jar": 7, + "Hold items and inspect shelf": 7, + "Hold and mark cardboard piece": 7, + "Move away from workstation": 6, + "Remove ruler": 6, + "Reach for product": 6, + "Pick up pen": 6, + "Holding marker": 6, + "Pick up cardboard": 6, + "Pick up cardboard strip": 6, + "Pick up new cardboard piece": 6, + "Place puzzle piece": 6, + "Manipulate puzzle pieces": 6, + "Mark lines on cardboard": 6, + "Release cardboard shape": 6, + "Hold water bottle": 6, + "Hold phone": 6, + "Rearrange Mahjong tiles": 6, + "Release cardboard": 6, + "Browsing smartphone content": 6, + "Wipe the plastic jar": 6, + "Pick up tin can": 6, + "Pick up stapler": 6, + "Draw grid line with pen": 6, + "Draw grid line": 6, + "Sort buttons": 6, + "Reach for next item": 5, + "Reach into box": 5, + "Move product to shelf": 5, + "Reach for button": 5, + "Release scissors": 5, + "Interact with phone": 5, + "Place phone down": 5, + "Separate cardboard piece": 5, + "Move smartphone": 5, + "Hold ruler on cardboard": 5, + "Reposition hands": 5, + "Move along shelf": 5, + "Hold ruler": 5, + "Cut cardboard piece with scissors": 5, + "Position cardboard piece": 5, + "Place marker down": 5, + "Sort paper star": 5, + "Sort paper stars": 5, + "Release puzzle piece": 5, + "Search for puzzle piece": 5, + "Hold beads": 5, + "Move along the shelves": 5, + "Manipulate small component": 5, + "Manipulate component on strip": 5, + "Place strip on table": 5, + "Manipulate component": 5, + "Align canned goods on shelf": 5, + "Drawing grid line with ruler": 5, + "Drawing grid line with pen and ruler": 5, + "Drawing grid line": 5, + "Fold lucky star": 5, + "Sort colored tiles": 5, + "Pick up colored tile": 5, + "Place colored tile": 5, + "Sort tiles": 5, + "Sort tiles by color": 5, + "Initiate star folding": 5, + "Manipulate paper decoration": 5, + "Manipulate paper edge": 5, + "Manipulate adhesive strip": 5, + "Place jar on shelf": 4, + "Place product in box": 4, + "Pick up button": 4, + "Place button": 4, + "Put down scissors": 4, + "Mark cardboard with pen and ruler": 4, + "Hold cardboard pieces": 4, + "Hold portable charger": 4, + "Fold purple paper strip": 4, + "Fold purple paper": 4, + "Hold and crease purple paper": 4, + "Release paper": 4, + "Retrieve paper strips": 4, + "Fold and organize paper strips": 4, + "Reach into bag": 4, + "Position hands for work": 4, + "Manipulate quilling strip": 4, + "Begin rolling quilling strip": 4, + "Examine item": 4, + "Move cardboard box": 4, + "Walk towards aisle": 4, + "Hold cardboard": 4, + "Walk through workspace": 4, + "Manipulate quilled paper strip": 4, + "Cut cardboard tube": 4, + "Cut cardboard into triangles": 4, + "Reach for container": 4, + "Move container toward shelf": 4, + "Move away from shelf": 4, + "Pick up marker": 4, + "Walk away": 4, + "Pick up paper star": 4, + "Marking lines on cardboard": 4, + "Adjusting a puzzle piece": 4, + "Draw line along ruler": 4, + "Cap marker": 4, + "Manipulate craft piece": 4, + "Manipulate craft paper strips": 4, + "Operate smartphone": 4, + "Pick up item from shelf": 4, + "Sort star-shaped beads": 4, + "Sort beads on table": 4, + "Hold instructional sign": 4, + "Pick up star-shaped bead": 4, + "Place bead on table": 4, + "Draw lines with ruler": 4, + "Grasp origami stars": 4, + "Place water bottle on table": 4, + "Vacuum the carpet": 4, + "Push vacuum cleaner": 4, + "Adjust vacuum cleaner position": 4, + "Vacuum edge of carpet": 4, + "Move vacuum cleaner": 4, + "Place finished star on table": 4, + "Adjust Mahjong tiles": 4, + "Reach for Mahjong tiles": 4, + "Rearrange Mahjong tile": 4, + "Adjust Mahjong tile": 4, + "Align Mahjong tiles": 4, + "Move Mahjong tile": 4, + "Fold ribbon": 4, + "Hold small piece of ribbon": 4, + "Manipulate ribbon piece": 4, + "Fold and manipulate ribbon": 4, + "Manipulate ribbon knot": 4, + "Continue cutting newspaper": 4, + "Adjust tile row alignment": 4, + "Adjust Mahjong tile alignment": 4, + "Adjust Mahjong tile on the stack": 4, + "Measure and mark cardboard": 4, + "Cut cardboard strip with scissors": 4, + "Scroll on smartphone": 4, + "Align ruler and mark cardboard": 4, + "Assemble cardboard pieces": 4, + "Arrange cardboard piece": 4, + "Cut along the line": 4, + "Place cardboard piece on stack": 4, + "Arrange buttons on the table": 4, + "Move hand over button pile": 4, + "Arrange orange buttons": 4, + "Move pen away": 4, + "Gathering star beads": 4, + "Manipulate paper stars": 4, + "Adjust cardboard": 4, + "Set down scissors and pick up power bank": 4, + "Reposition cardboard for cutting": 4, + "Arrange cardboard pieces": 4, + "Mark cardboard strip with pen": 4, + "Pick up pink water bottle": 4, + "Place down pink water bottle": 4, + "Place star in row": 4, + "Pick up star": 4, + "Begin folding paper strip": 4, + "Fold paper strip into a star": 4, + "Manipulate folded paper star": 4, + "Reaching for beads": 4, + "Place cardboard square": 4, + "Arrange buttons in a line": 4, + "Approaching and pressing the door switch": 4, + "Bend and manipulate plastic strip": 4, + "Pick up and sort cardboard": 4, + "Move camera over surface": 4, + "Observe sorting progress": 4, + "Lock phone": 4, + "Reach for cardboard box": 4, + "Reach for object": 4, + "Move to desk": 4, + "Gathering items": 4, + "Place items on table": 4, + "Gathering colored beads": 4, + "Arrange beads by color": 4, + "Sort star-shaped objects by color": 4, + "Sort star-shaped objects": 4, + "Sort yellow star-shaped objects": 4, + "Sort purple star-shaped objects": 4, + "View phone screen": 4, + "Viewing phone screen": 4, + "Placing phone down": 4, + "Place button in group": 4, + "Move away from table": 4, + "Placing paper strip": 4, + "Securing paper structure": 4, + "Secure paper edges with adhesive": 4, + "Pick up product from bin": 3, + "Reach for next product": 3, + "Arrange canned products on shelf": 3, + "Move bin to shelf area": 3, + "Hold item and adjust posture": 3, + "Grasp product from box": 3, + "Grasp product from shelf": 3, + "Move product to box": 3, + "Manipulate cardboard piece": 3, + "Position ruler on cardboard": 3, + "Stack cardboard pieces": 3, + "Place cardboard": 3, + "Place down paper pieces": 3, + "Release folded paper": 3, + "Release quilling strip": 3, + "Inspect cardboard piece": 3, + "Reposition hand": 3, + "Touch shelf edge": 3, + "Release label": 3, + "Remove shelf label": 3, + "Carry stool to next shelf": 3, + "Place stool on floor": 3, + "Observe shelf": 3, + "Adjust hand position": 3, + "Arrange star-shaped beads": 3, + "Move pen": 3, + "Move towards table": 3, + "Observe room": 3, + "Check watch": 3, + "Manipulate and inspect colorful pieces": 3, + "Manipulate colorful pieces": 3, + "Hold power bank and cable": 3, + "Interact with colleagues": 3, + "Hold small white box": 3, + "Adjust smartphone and sort pieces": 3, + "Pick up cardboard piece": 3, + "Release cardboard piece": 3, + "Walk across office": 3, + "Pick up cardboard cutout": 3, + "Walk with cardboard cutout": 3, + "Finish placing cardboard cutouts": 3, + "Organize tools and materials": 3, + "Move cardboard piece": 3, + "Hold cardboard strip": 3, + "Reposition scissors": 3, + "Move away from desk": 3, + "Move to shelf": 3, + "Move marker and adjust hand": 3, + "Identify next cardboard piece": 3, + "Reach for can": 3, + "Open door": 3, + "Hold craft tool": 3, + "Approach table": 3, + "Arrange paper strips": 3, + "Hold and bend paper strip": 3, + "Scan for next piece": 3, + "Positioning puzzle piece": 3, + "Move puzzle piece": 3, + "Adjusting puzzle piece": 3, + "Hold ruler and pen steady": 3, + "Moving ruler": 3, + "Approach packing area": 3, + "Deposit beads into box": 3, + "Combine bead piles": 3, + "Cut light green fabric": 3, + "Continue cutting fabric": 3, + "Cut fabric with scissors": 3, + "Adjusting fabric for cutting": 3, + "Adjusting fabric position": 3, + "Cutting fabric": 3, + "Mark fabric with pen": 3, + "Mark fabric": 3, + "Manipulate cardboard shape": 3, + "Hold small cardboard pieces": 3, + "sort craft materials": 3, + "Release smartphone": 3, + "Sort small craft pieces": 3, + "Move product towards shelf": 3, + "Move to box": 3, + "Place container on shelf": 3, + "Place item in shopping bag": 3, + "Sort beads on the table": 3, + "Reposition ruler and pen": 3, + "Reposition pen and prepare for next line": 3, + "Place pen on cardboard": 3, + "Draw straight lines on cardboard": 3, + "Sort origami stars": 3, + "Walk in hallway": 3, + "Reach for stars": 3, + "Walk towards desk": 3, + "Sort light blue origami stars": 3, + "Sort origami stars by color": 3, + "Move origami stars": 3, + "Hold and view phone": 3, + "Cut cardboard pieces with scissors": 3, + "Vacuuming carpet edge": 3, + "Vacuuming carpet corner": 3, + "Vacuuming the carpet edge": 3, + "Vacuuming along the wall edge": 3, + "Hold product package": 3, + "Check phone": 3, + "Hold charging cable": 3, + "Hold items in hand": 3, + "Hold and examine item": 3, + "Pick up pack from shelf": 3, + "fold purple ribbon": 3, + "Position ribbon piece": 3, + "Place ribbon onto project": 3, + "Secure ribbon with needle": 3, + "Reach for shelf": 3, + "Place smartphone on desk": 3, + "Reach for water bottle": 3, + "Hold scissors": 3, + "Move scissors away": 3, + "Place scissors down": 3, + "Arrange tiles into row": 3, + "Pick up Mahjong tile": 3, + "Place Mahjong tile on the stack": 3, + "Place Mahjong tile on stack": 3, + "Hold ruler and draw line": 3, + "Draw line": 3, + "Hold ruler and marker": 3, + "Tap smartphone screen": 3, + "Scroll through photo gallery": 3, + "Typing message on smartphone": 3, + "Typing on smartphone": 3, + "Tapping smartphone screen": 3, + "Tapping on smartphone screen": 3, + "Putting away smartphone": 3, + "Stop measuring and put down tools": 3, + "Positioning ruler on cardboard": 3, + "Draw line with pen": 3, + "Prepare to draw lines": 3, + "Remove ruler and marker": 3, + "Walking through classroom": 3, + "Move marker away": 3, + "Position ruler and mark cardboard": 3, + "Mark cardboard with ruler": 3, + "Reposition utility knife": 3, + "Tear off cardboard segment": 3, + "Reach for craft items": 3, + "Sort craft items": 3, + "Place hand on table": 3, + "Browse smartphone screen": 3, + "Scroll smartphone screen": 3, + "Put down smartphone": 3, + "Place smartphone down": 3, + "Adjust container on shelf": 3, + "Adjust cans in container": 3, + "Adjust cans in tray": 3, + "Adjusting canned goods on shelf": 3, + "Sorting buttons": 3, + "Sort orange buttons": 3, + "Sort orange button": 3, + "Move orange buttons": 3, + "Sort purple beads": 3, + "Sort beads by hand": 3, + "Count and record paper stars": 3, + "Connect cable to device": 3, + "Count and arrange paper stars": 3, + "Count paper stars": 3, + "Pick up puzzle piece": 3, + "Place piece into puzzle": 3, + "Manipulate puzzle piece": 3, + "Observe puzzle progress": 3, + "Attempt to fit puzzle piece": 3, + "Hold tray of canned goods": 3, + "Position tray": 3, + "Carry crate of cans": 3, + "Place crate on floor": 3, + "Wipe item": 3, + "Place item back": 3, + "Reach for retail item": 3, + "Grasp retail item": 3, + "Adjust retail items on shelf": 3, + "Pick up retail item": 3, + "Align and place retail item": 3, + "Arrange items on shelf": 3, + "Adjust retail item position": 3, + "Reach for star": 3, + "Retrieve star": 3, + "Cut cardboard grid": 3, + "Prepare paper strip": 3, + "Place star on table": 3, + "Place phone on table": 3, + "Cut along the edge of the newspaper": 3, + "Cut along the newspaper edge": 3, + "Browsing mobile phone": 3, + "Browse mobile phone": 3, + "Cut newspaper with scissors": 3, + "Gather pieces": 3, + "Move pieces into box": 3, + "Gather pieces into box": 3, + "Scrolling or navigating on phone": 3, + "Scrolling and viewing content on phone": 3, + "Sort and arrange buttons": 3, + "Sort button": 3, + "Sort and adjust button line": 3, + "Sort and place buttons": 3, + "Walking in the hallway": 3, + "Entering the VR training room": 3, + "Greeting/acknowledging participants": 3, + "Move through the training room": 3, + "Manipulate plastic strips": 3, + "Manipulate plastic strip": 3, + "Hold and bend plastic strip": 3, + "Fold plastic strip": 3, + "Pick up charging cable": 3, + "Hold electronic item": 3, + "Pick up electronic item": 3, + "Inspect electronic item": 3, + "Inspect smartphone box": 3, + "Hold smartphone box": 3, + "Examine product": 3, + "Move plastic storage bin": 3, + "Hold container of canned food": 3, + "Move towards aisle": 3, + "Approach restocking supplies": 3, + "Move pineapple chips": 3, + "Sort and arrange cardboard pieces": 3, + "Reach for cardboard piece": 3, + "Sort and stack cardboard pieces": 3, + "Walking towards workstation": 3, + "Sort small objects": 3, + "Sort buttons by color": 3, + "Sort button by color": 3, + "Reach for item in box": 2, + "Pick up nut bar box": 2, + "Place canned product on shelf": 2, + "Pick up canned product": 2, + "Reach for next canned product": 2, + "Pick up plastic bin": 2, + "Retract hand": 2, + "Hold and wipe product": 2, + "Wipe down shelf": 2, + "Wipe product": 2, + "Place jar in box": 2, + "Wipe shelf": 2, + "Pick up pickle jar": 2, + "Hold pickle jar": 2, + "Hold cleaning cloth": 2, + "Pick up product from shelf": 2, + "Move to next section": 2, + "Prepare to place product": 2, + "Grasp next item": 2, + "Position scissors to cut cardboard": 2, + "Position scissors": 2, + "Walk through corridor": 2, + "Arrive at a different workstation": 2, + "Move vacuum cleaner hose": 2, + "Mark cardboard with ruler and pen": 2, + "Hold ruler steady": 2, + "Move marker and ruler": 2, + "Align ruler on cardboard": 2, + "Plug cable into portable charger": 2, + "Pick up portable charger": 2, + "Place charger on table": 2, + "Hold charger and cable": 2, + "Manipulate power cable plug": 2, + "Insert plug into power adapter": 2, + "Hold power adapter": 2, + "Align charging cable": 2, + "Insert charging cable": 2, + "Observe desktop layout": 2, + "Pick up yellow paper strip": 2, + "Adjust paper strip": 2, + "Hold charger": 2, + "Open small case": 2, + "Measure cardboard with ruler": 2, + "Pick up yellow item": 2, + "Hold blue product box": 2, + "Wipe shelf surface": 2, + "Inspect product": 2, + "Clean shelf": 2, + "Place ketchup bottle on shelf": 2, + "Draw line with marker": 2, + "Draw straight line": 2, + "Mark straight line": 2, + "Move ruler and tools": 2, + "Pick up small cardboard piece": 2, + "Cut cardboard along line": 2, + "Align ruler with crease": 2, + "Cut cardboard strip with utility knife": 2, + "Hold container lid": 2, + "Closing the door": 2, + "Grasp cleaning bottle": 2, + "Grasping cleaning cloth": 2, + "Adjust pot position": 2, + "Start cutting": 2, + "Organize products": 2, + "Close cardboard box": 2, + "Grasp package": 2, + "Observe shelf status": 2, + "Inspect product lid": 2, + "Reach for another item": 2, + "Discard item into bin": 2, + "Walk towards next aisle": 2, + "Reach for product labels": 2, + "Hold product labels": 2, + "Examine labels": 2, + "Pick up bottled sauce": 2, + "Pick up supplement bottle": 2, + "Hold supplement bottle": 2, + "Open supplement bottle": 2, + "Pick up item": 2, + "Place item in container": 2, + "Pick up another item": 2, + "Adjust grip on container": 2, + "Pick up oil bottle": 2, + "Inspect supplement bottle": 2, + "Pick up spice jar": 2, + "Stand up and walk away": 2, + "Prepare to sort beads": 2, + "Align ruler": 2, + "Adjust grip": 2, + "Drawing lines on cardboard": 2, + "Reposition marker": 2, + "Mark lines with marker": 2, + "Position the ruler": 2, + "Insert charging cable into power bank": 2, + "Sort colorful pieces": 2, + "Touch pieces in box": 2, + "Place white box on table": 2, + "Sort small colorful pieces": 2, + "Sorting colorful paper pieces": 2, + "Manipulate paper piece": 2, + "Use phone to check instructions": 2, + "Trace pattern on cardboard": 2, + "Remove cardboard pattern": 2, + "Remove cardboard pattern piece": 2, + "Cut out cardboard pattern": 2, + "Cut cardboard pattern": 2, + "Adjust cardboard position": 2, + "Interact with smartphone screen": 2, + "Pick up metal ruler": 2, + "Move pen aside": 2, + "Reposition and cut": 2, + "Hold quilling paper": 2, + "Hold quilled paper coil": 2, + "Manipulate small paper segment": 2, + "Place down paper segment": 2, + "Browse and interact with phone interface": 2, + "Interacting with phone screen": 2, + "Pick up light blue strip": 2, + "Inspect strip": 2, + "Manipulate light blue strip": 2, + "Place scissors aside": 2, + "Stacking cardboard pieces": 2, + "Moving hand towards cardboard stack": 2, + "Moving hand": 2, + "Position cardboard for cutting": 2, + "Put down water bottle": 2, + "Placing piece on stack": 2, + "Reach for and pick up smartphone": 2, + "Pick up item from bin": 2, + "Pick up next item from bin": 2, + "Hold item": 2, + "Inspect and place item on shelf": 2, + "Check smart watch": 2, + "Withdraw hand": 2, + "Pick up jar": 2, + "Pick up sauce bottle": 2, + "Hold empty container": 2, + "Assess shelf arrangement": 2, + "Observe and walk through store": 2, + "Inspect shelf condition": 2, + "Observe colleague and workspace": 2, + "Walk towards shelves": 2, + "Approach boxes": 2, + "Extract wire hangers from box": 2, + "Bundle display hooks": 2, + "Move through aisle": 2, + "Pick up items from the shopping bag": 2, + "Place items on the shelf": 2, + "Place marked piece down": 2, + "Release cardboard piece and gesture": 2, + "Observe and pause": 2, + "Gesturing": 2, + "Resume observation": 2, + "Place cans into box": 2, + "Arrange cans in box": 2, + "Arrange cans on shelf": 2, + "Adjust position": 2, + "Place container in bin": 2, + "Adjust cans in bin": 2, + "Hold and inspect can": 2, + "Adjust perspective": 2, + "Inspect shelf and organize stock": 2, + "Picking up stock": 2, + "Placing stock on shelf": 2, + "Hold small product bag": 2, + "Carry container": 2, + "Pick up cleaning cloth": 2, + "Pick up product box": 2, + "Place box on shelf": 2, + "Place plush toy on shelf": 2, + "Adjust placement on shelf": 2, + "Move plush toy": 2, + "Arrange cardboard": 2, + "Walk with marker": 2, + "Pick up small object": 2, + "Walk across room": 2, + "Place cardboard square on stack": 2, + "Arrange cardboard squares": 2, + "Stacking cardboard squares": 2, + "Positioning cardboard on 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ruler": 2, + "Gather cardboard pieces": 2, + "Examine canned goods": 2, + "Pick up Dior gift box": 2, + "Inspect Dior gift box": 2, + "Place back Dior gift box": 2, + "Move along the shelf": 2, + "Pick up another bottle": 2, + "Inspect bottle": 2, + "Inspect almond package": 2, + "Move along the supermarket aisle": 2, + "Pick up canned good": 2, + "Prepare to place cardboard": 2, + "Prepare to resume cutting": 2, + "Hold canned food": 2, + "Align canned food on shelf": 2, + "Place another canned food on shelf": 2, + "Adjust canned food on shelf": 2, + "Move hand away from shelf": 2, + "Move hand away": 2, + "Hold earbud case": 2, + "Open earbud case": 2, + "Hold electronic accessory": 2, + "Pick up accessory": 2, + "Pick up electronic accessory": 2, + "Move hand back to box": 2, + "Move towards box": 2, + "Hold items": 2, + "Place items on shelf": 2, + "Grasp snack package": 2, + "Hold snack package": 2, + "Hold snack packages": 2, + "Adjust snack package": 2, + "Align plastic 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2, + "Carry cereal towards aisle": 2, + "Carry pasta box towards aisle": 2, + "Hold container": 2, + "Carry item to shelf": 2, + "Inspect shelf": 2, + "Move to stock products": 2, + "Move to shelf base": 2, + "Pick up gift box": 2, + "Pick up next gift box": 2, + "Pick up snack pouch": 2, + "Move storage bin": 2, + "Hold bin and move through aisle": 2, + "Grasp plastic bag on shelf": 2, + "Arrange plastic containers": 2, + "Arrange container on shelf": 2, + "Sort Mahjong tiles": 2, + "Mark lines with pen along ruler": 2, + "Pick up charging case": 2, + "Inspect charging case": 2, + "Place charging case down": 2, + "Place ruler on cardboard": 2, + "Hold and align cardboard": 2, + "Reposition tools": 2, + "Position cardboard tube": 2, + "Position scissors for next cut": 2, + "Place canned good on shelf": 2, + "Move canned goods container": 2, + "Position container near shelf": 2, + "Place canned food in container": 2, + "Reach for next canned food item": 2, + "Move cardboard": 2, + "Labeling cardboard squares": 2, + "Labeling cardboard square": 2, + "Labeling cardboard piece": 2, + "Marking cardboard with pen": 2, + "Folding cardboard": 2, + "Manipulate cardboard sheet": 2, + "Record count on notepad": 2, + "Record star count on paper": 2, + "Pick up electronic device": 2, + "Place device on lap": 2, + "Move hand to paper stars": 2, + "Resume counting stars": 2, + "Reviewing count record": 2, + "Write on paper record": 2, + "Update paper record": 2, + "Reach for puzzle piece": 2, + "Sort puzzle pieces": 2, + "Approaching the table": 2, + "Preparing to craft": 2, + "Picking up crafting material": 2, + "Pick up small piece of material": 2, + "Manipulate material": 2, + "Place material": 2, + "Manipulate yellow strip": 2, + "Manipulating paper strips": 2, + "Manipulate bead": 2, + "Manipulate beads": 2, + "Hold and manipulate paper strip": 2, + "Sort canned goods in tray": 2, + "Move can towards shelf": 2, + "Wipe retail item": 2, + "Hold recording sheet and pen": 2, + "Record star count": 2, + "Hold pen and paper": 2, + "Observe surroundings": 2, + "Observe paper and count objects": 2, + "Write count on paper": 2, + "Place pen on table": 2, + "Place smartphone on table": 2, + "Resume writing on paper": 2, + "Place paper star in row": 2, + "Manipulate star": 2, + "Arrange paper stars": 2, + "Pick up power bank": 2, + "Pick up small item": 2, + "Walking to sink": 2, + "Washing hands": 2, + "Rub hands together": 2, + "Finish washing hands": 2, + "Pick up paper towel": 2, + "Dry hands": 2, + "Discard paper towel": 2, + "Release paper star": 2, + "Cut section from newspaper": 2, + "Tear newspaper": 2, + "Hold newspaper": 2, + "Hold and align newspaper": 2, + "Fold newspaper": 2, + "Reposition newspaper": 2, + "Sort blue star-shaped pieces": 2, + "Sort small plastic pieces": 2, + "Reach for more pieces": 2, + "Sort plastic pieces": 2, + "Typing on phone": 2, + "Repositioning ruler": 2, + "Place down ruler and pen": 2, + "Walk through hallway": 2, + "Fold cardboard edge": 2, + "Drop cardboard square into box": 2, + "Deposit cardboard squares": 2, + "Approaching work table": 2, + "Cut cardboard sheet with scissors": 2, + "Cut cardboard sheet": 2, + "Wipe electronic item": 2, + "Place item in bag": 2, + "Select another item": 2, + "Pick up canned item": 2, + "Pick up another canned item": 2, + "Carry plastic container": 2, + "Pick up canned goods": 2, + "Move bin": 2, + "Walking along the aisle": 2, + "Observe stocking": 2, + "Place canned food in bin": 2, + "Pick up plastic container": 2, + "Forming quilled paper shape": 2, + "Manipulate quilled paper shape": 2, + "Place quilled paper shape": 2, + "Retrieve paper strip": 2, + "Select paper strip": 2, + "Manipulate quilled paper strips": 2, + "Transition to standing position": 2, + "Observe paper quilling station": 2, + "Sort quilled paper pieces": 2, + "Walk towards storage area": 2, + "Hold device and cable": 2, + "Move piece to pile": 2, + "Manipulate quilled paper": 2, + "Mark list with pen": 2, + "Mark paper list": 2, + "Adjust bead piles": 2, + "Sort blue beads": 2, + "Move blue beads": 2, + "Place down pen": 2, + "Walking through the office": 2, + "Place controller on table": 2, + "Resume sorting blue beads": 2, + "Finishing coil": 2, + "Folding paper strip": 2, + "Manipulate quilling paper": 2, + "Grasp electronic object": 2, + "Interaction with coworker": 2, + "Manipulate small object": 2, + "Manipulate paper quilling piece": 2, + "Hold quilled paper piece": 2, + "Hold and align paper strip": 2, + "Hold and rotate paper strip": 2, + "Move cardboard sheet": 2, + "Trim cardboard": 2, + "Return to sorting": 2, + "Record count": 2, + "Counting and organizing beads": 2, + "Pick up star bead": 2, + "Place and count bead": 2, + "Arrange star beads": 2, + "Counting star beads": 2, + "Retrieving more beads": 2, + "Adjust paper": 2, + "Gather star beads": 2, + "Arrange star beads for counting": 2, + "Sort and count beads": 2, + "Wipe food product": 1, + "Wipe jar": 1, + "Place pickle jar in box": 1, + "Release pickle jar": 1, + "Wipe the shelf": 1, + "Wipe the product jar": 1, + "Place jar into shelf box": 1, + "Wipe grocery shelf": 1, + "Align button in row": 1, + "Place button in row": 1, + "Pick up orange button": 1, + "Arrange small buttons": 1, + "Align button": 1, + "Align buttons": 1, + "Arrange button cluster": 1, + "Align button row": 1, + "Arrange buttons on table": 1, + "Look around the table": 1, + "Adjust red button in row": 1, + "Adjust red button": 1, + "Pull back hand": 1, + "Align red buttons": 1, + "Reach for black button": 1, + "Arrange black buttons": 1, + "Pick up black button": 1, + "Move black button": 1, + "Pick up red button": 1, + "Place red button": 1, + "Move and place black buttons": 1, + "Arrange buttons in row": 1, + "Arrange red buttons": 1, + "Align red button in row": 1, + "Reach and sort buttons": 1, + "Adjust red button position": 1, + "Place and align button": 1, + "Move hand": 1, + "Move button to line": 1, + "Reach for utility knife": 1, + "Place smartphone on cardboard": 1, + "Walk towards room": 1, + "Retract camera/reposition view": 1, + "Switch to scissors": 1, + "Retract hand from bag": 1, + "Reach for canned food": 1, + "Walk towards shelf": 1, + "Select product from box": 1, + "Wipe ketchup bottle": 1, + "Prepare to place bottle on shelf": 1, + "Walk through office": 1, + "Transition to cutting": 1, + "Reposition hands and ruler": 1, + "Press fold": 1, + "Position utility knife on cardboard": 1, + "Place smartphone on stand": 1, + "Pick up dustpan": 1, + "Move dustpan to side": 1, + "Move towards the stove": 1, + "Open stove pot lid": 1, + "Walking towards door": 1, + "Picking up bottle": 1, + "Wipe kitchen counter": 1, + "Rinse cloth in sink": 1, + "Move towards kitchen area": 1, + "Place cloth on floor": 1, + "Reach for cleaning supplies": 1, + "Remove cleaning bottle": 1, + "Washing hands in sink": 1, + "Wiping countertop": 1, + "Lift pot lid": 1, + "Stir contents": 1, + "Place lid back": 1, + "Move pot": 1, + "Place towel": 1, + "Use phone to check stock": 1, + "Place phone on shelf": 1, + "Remove item from shelf": 1, + "Sweep debris": 1, + "Sweep floor debris": 1, + "Place sauce in container": 1, + "Walk through store": 1, + "Reach for item on shelf": 1, + "Place oil in container": 1, + "Place supplement bottle in container": 1, + "Place spice jar in container": 1, + "Walking in the workspace": 1, + "Roll quilling paper": 1, + "Release paper coil": 1, + "Release and prepare new strip": 1, + "Reach for paper strips": 1, + "Place item into bag": 1, + "Position utility knife": 1, + "Lift utility knife": 1, + "Fold cut cardboard": 1, + "Look away": 1, + "Align scissors": 1, + "Position cardboard strip": 1, + "Inspect cardboard strip": 1, + "Pick up cut cardboard piece": 1, + "Move cardboard to pile": 1, + "Align cardboard piece": 1, + "Fold cardboard sheet": 1, + "Complete the cut": 1, + "Put down utility knife": 1, + "Hold utility knife": 1, + "Place cardboard strip": 1, + "Place sauce bottle on shelf": 1, + "Align foam piece": 1, + "Pick up bottle": 1, + "Observe craft layout": 1, + "Assemble foam strips": 1, + "Adjust foam strip": 1, + "Align foam strip": 1, + "Attach foam strip": 1, + "Curve foam strip into loop": 1, + "Fold foam piece": 1, + "Pick up blue foam piece": 1, + "Hold foam pieces": 1, + "Peel foam strip": 1, + "Move small blue foam piece towards the strip": 1, + "Align blue strip": 1, + "Lift blue strip": 1, + "Hold blue strip": 1, + "Peel blue strip": 1, + "Fold blue strip": 1, + "Align paper strip": 1, + "Interlock paper strips": 1, + "Pick up craft material": 1, + "Attach material to paper strip": 1, + "Pick up tool": 1, + "Enter workspace": 1, + "Grasp door handle": 1, + "Pick up supplies from box": 1, + "Enter the room": 1, + "Approach work table": 1, + "Reach for wire hangers": 1, + "Release hook": 1, + "Walk towards other aisles": 1, + "Reach for additional items": 1, + "Prepare to pick up item": 1, + "Reach for shelving divider": 1, + "Position shelving divider": 1, + "Rearrange shelf item": 1, + "Reach for product on shelf": 1, + "Release food item": 1, + "Reach for and examine canned goods": 1, + "Select and pick up a canned item": 1, + "Place item back on shelf": 1, + "Select a bottle": 1, + "Place bottle back on shelf": 1, + "Release bottle": 1, + "Scan supermarket shelves": 1, + "Reach for canned goods": 1, + "Touch canned goods": 1, + "Reach for next can": 1, + "Retrieve next canned food item": 1, + "Reach for next canned food": 1, + "Retrieve canned food from box": 1, + "Pick up electronic accessory from box": 1, + "Place accessory on shelf": 1, + "Reach towards shelf": 1, + "Place accessory into box": 1, + "Place accessory box": 1, + "Pick up new electronic product": 1, + "Pick up electronic product": 1, + "Release product on shelf": 1, + "Pick up new product from box": 1, + "Pick up shopping bag": 1, + "Walk with shopping bag": 1, + "Pick up item from box": 1, + "Move box to next position": 1, + "Place snack package on shelf": 1, + "Place snack package in box": 1, + "Place snack in box": 1, + "Place snack packages on shelf": 1, + "Pick up snack packages": 1, + "Pick up snack package": 1, + "Organize snacks in box": 1, + "Reach for snack package": 1, + "Open cardboard box": 1, + "Remove cardboard flap": 1, + "Reach for item": 1, + "Pick up plush toy": 1, + "Place plush toy into bag": 1, + "Prepare to place item in bag": 1, + "Place item into shopping bag": 1, + "Realign Mahjong tiles": 1, + "Release lantern": 1, + "Pick up packaged paper lantern component": 1, + "Remove paper lantern part from packaging": 1, + "Remove plastic packaging": 1, + "Pick up food item": 1, + "Pick up cereal boxes": 1, + "Pick up pasta box": 1, + "Pick up container from box": 1, + "Reach for items in box": 1, + "Pick up grocery item": 1, + "Pick up snack packs": 1, + "Place snack on shelf": 1, + "Retrieve snack from container": 1, + "Place gift box into bin": 1, + "Place gift box on shelf": 1, + "Place snack pouch in container": 1, + "Reach for snack pouch": 1, + "Place snack pouch on shelf": 1, + "Remove storage bin from shelf": 1, + "Reach for empty shelf space": 1, + "Remove plastic container from shelf": 1, + "Remove plastic container from storage box": 1, + "Retrieve another container": 1, + "Stabilize cardboard": 1, + "Stabilize ruler": 1, + "Moving cardboard square": 1, + "Placing labeled square": 1, + "Starting to label next square": 1, + "Placing labeled cardboard square": 1, + "Switching marker": 1, + "Reach for next piece": 1, + "Placing pen on table": 1, + "Repositioning ruler and cardboard": 1, + "Walking across the room": 1, + "Use phone while crafting": 1, + "View content on smartphone": 1, + "Pick up cardboard square": 1, + "Retrieve hand to table": 1, + "Pick up cardboard stack": 1, + "Walk with cardboard": 1, + "Move away from collection box": 1, + "Walking through office hallway": 1, + "Grasp cardboard sheet": 1, + "Set down utility knife": 1, + "Sort cut cardboard": 1, + "Prepare to cut cardboard": 1, + "Score cardboard": 1, + "Place container on floor": 1, + "Reach for another container": 1, + "Place storage container on floor": 1, + "Release container": 1, + "Pick up storage container": 1, + "Position container on shelf": 1, + "Remove lid from container": 1, + "Place canned goods in container": 1, + "Pick up next product from bin": 1, + "Reorganize bin contents": 1, + "Rolling paper strip": 1, + "Selecting new paper strip": 1, + "Start folding paper strip": 1, + "Positioning paper strip": 1, + "Walk towards workspace": 1, + "Reach for paper strip": 1, + "Pull paper strip": 1, + "Sort beads and write count": 1 + }, + "action_options": [ + "Adjust Mahjong tile", + "Adjust Mahjong tile alignment", + "Adjust Mahjong tile on the stack", + "Adjust Mahjong tiles", + "Adjust bead piles", + "Adjust canned food on shelf", + "Adjust cans in bin", + "Adjust cans in container", + "Adjust cans in tray", + "Adjust cardboard", + "Adjust cardboard divider", + "Adjust cardboard position", + "Adjust container on shelf", + "Adjust container position", + "Adjust containers on shelf", + "Adjust foam strip", + "Adjust grip", + "Adjust grip on container", + "Adjust hand position", + "Adjust item on shelf", + "Adjust lantern shape", + "Adjust lantern string", + "Adjust paper", + "Adjust paper strip", + "Adjust perspective", + "Adjust placement on shelf", + "Adjust position", + "Adjust pot position", + "Adjust puzzle piece", + "Adjust red button", + "Adjust red button in row", + "Adjust red button position", + "Adjust retail item position", + "Adjust retail items on shelf", + "Adjust ruler position", + "Adjust smartphone and sort pieces", + "Adjust snack package", + "Adjust tile row alignment", + "Adjust vacuum cleaner position", + "Adjusting a puzzle piece", + "Adjusting canned goods on shelf", + "Adjusting fabric for cutting", + "Adjusting fabric position", + "Adjusting puzzle piece", + "Align Mahjong tiles", + "Align and place retail item", + "Align blue strip", + "Align button", + "Align button in row", + "Align button row", + "Align buttons", + "Align canned food on shelf", + "Align canned goods on shelf", + "Align cardboard piece", + "Align cardboard strip", + "Align charging cable", + "Align edges of paper lantern", + "Align foam piece", + "Align foam strip", + "Align paper lantern edges", + "Align paper strip", + "Align plastic containers", + "Align red button in row", + "Align red buttons", + "Align ruler", + "Align ruler and mark cardboard", + "Align ruler on cardboard", + "Align ruler with crease", + "Align scissors", + "Apply adhesive tape to lantern", + "Approach boxes", + "Approach desk", + "Approach packing area", + "Approach restocking supplies", + "Approach table", + "Approach work table", + "Approach workstation", + "Approaching and pressing the door switch", + "Approaching the table", + "Approaching work table", + "Arrange Mahjong tiles", + "Arrange beads by color", + "Arrange black buttons", + "Arrange button cluster", + "Arrange buttons", + "Arrange buttons in a line", + "Arrange buttons in row", + "Arrange buttons on table", + "Arrange buttons on the table", + "Arrange canned products on shelf", + "Arrange cans in box", + "Arrange cans on shelf", + "Arrange cardboard", + "Arrange cardboard piece", + "Arrange cardboard pieces", + "Arrange cardboard squares", + "Arrange container on shelf", + "Arrange items on shelf", + "Arrange orange buttons", + "Arrange paper stars", + "Arrange paper strips", + "Arrange plastic containers", + "Arrange red buttons", + "Arrange small buttons", + "Arrange star beads", + "Arrange star beads for counting", + "Arrange star-shaped beads", + "Arrange tiles into row", + "Arrive at a different workstation", + "Assemble cardboard pieces", + "Assemble foam strips", + "Assess shelf arrangement", + "Attach foam strip", + "Attach material to paper strip", + "Attempt to fit puzzle piece", + "Begin folding paper strip", + "Begin rolling quilling strip", + "Bend and manipulate plastic strip", + "Browse and interact with phone interface", + "Browse mobile phone", + "Browse smartphone screen", + "Browsing mobile phone", + "Browsing smartphone content", + "Bundle display hooks", + "Cap marker", + "Carry cardboard piece", + "Carry cereal boxes", + "Carry cereal towards aisle", + "Carry container", + "Carry crate of cans", + "Carry item to shelf", + "Carry pasta box towards aisle", + "Carry plastic container", + "Carry stool to next shelf", + "Check phone", + "Check smart watch", + "Check watch", + "Clean shelf", + "Close cardboard box", + "Closing the door", + "Combine bead piles", + "Complete the cut", + "Connect cable to device", + "Continue cutting fabric", + "Continue cutting newspaper", + "Continue folding paper strip", + "Count and arrange paper stars", + "Count and record paper stars", + "Count paper stars", + "Counting and organizing beads", + "Counting star beads", + "Curve foam strip into loop", + "Cut along the edge of the newspaper", + "Cut along the line", + "Cut along the marked line", + "Cut along the newspaper edge", + "Cut cardboard", + "Cut cardboard along line", + "Cut cardboard grid", + "Cut cardboard into triangles", + "Cut cardboard pattern", + "Cut cardboard piece", + "Cut cardboard piece with scissors", + "Cut cardboard pieces with scissors", + "Cut cardboard shape", + "Cut cardboard sheet", + "Cut cardboard sheet with scissors", + "Cut cardboard square", + "Cut cardboard strip", + "Cut cardboard strip with scissors", + "Cut cardboard strip with utility knife", + "Cut cardboard triangle", + "Cut cardboard tube", + "Cut cardboard with scissors", + "Cut cardboard with utility knife", + "Cut fabric with scissors", + "Cut light green fabric", + "Cut newspaper", + "Cut newspaper with scissors", + "Cut out cardboard pattern", + "Cut section from newspaper", + "Cutting fabric", + "Deposit beads into box", + "Deposit cardboard squares", + "Discard item into bin", + "Discard paper towel", + "Draw grid line", + "Draw grid line with pen", + "Draw line", + "Draw line along ruler", + "Draw line on cardboard", + "Draw line with marker", + "Draw line with pen", + "Draw lines on cardboard", + "Draw lines with pen and ruler", + "Draw lines with ruler", + "Draw straight line", + "Draw straight lines on cardboard", + "Drawing grid line", + "Drawing grid line with pen and ruler", + "Drawing grid line with ruler", + "Drawing lines on cardboard", + "Drop cardboard square into box", + "Dry hands", + "Enter the room", + "Enter workspace", + "Entering the VR training room", + "Examine canned goods", + "Examine item", + "Examine labels", + "Examine product", + "Expand paper lantern", + "Extract wire hangers from box", + "Finish placing cardboard cutouts", + "Finish washing hands", + "Finish wiping and inspect jar", + "Finishing coil", + "Fold and manipulate ribbon", + "Fold and organize paper strips", + "Fold blue strip", + "Fold cardboard", + "Fold cardboard edge", + "Fold cardboard shape", + "Fold cardboard sheet", + "Fold cut cardboard", + "Fold foam piece", + "Fold lucky star", + "Fold newspaper", + "Fold paper lantern", + "Fold paper star", + "Fold paper strip", + "Fold paper strip into a star", + "Fold paper strip into knot", + "Fold paper strip into lucky star", + "Fold paper strip into star", + "Fold plastic strip", + "Fold purple paper", + "Fold purple paper strip", + "Fold ribbon", + "Folding cardboard", + "Folding paper strip", + "Forming quilled paper shape", + "Gather cardboard pieces", + "Gather pieces", + "Gather pieces into box", + "Gather star beads", + "Gathering colored beads", + "Gathering items", + "Gathering star beads", + "Gesturing", + "Grasp and retrieve item", + "Grasp cardboard sheet", + "Grasp cleaning bottle", + "Grasp door handle", + "Grasp electronic object", + "Grasp item", + "Grasp lantern", + "Grasp lantern component", + "Grasp next item", + "Grasp origami stars", + "Grasp package", + "Grasp paper strip", + "Grasp plastic bag on shelf", + "Grasp product from box", + "Grasp product from shelf", + "Grasp retail item", + "Grasp shopping bag", + "Grasp snack package", + "Grasping cleaning cloth", + "Greeting/acknowledging participants", + "Guide utility knife along ruler", + "Handle paper lantern component", + "Hold and align cardboard", + "Hold and align newspaper", + "Hold and align paper strip", + "Hold and bend paper strip", + "Hold and bend plastic strip", + "Hold and crease purple paper", + "Hold and examine item", + "Hold and inspect can", + "Hold and manipulate paper strip", + "Hold and mark cardboard piece", + "Hold and rotate paper strip", + "Hold and view phone", + "Hold and wipe product", + "Hold beads", + "Hold bin and move through aisle", + "Hold blue product box", + "Hold blue strip", + "Hold canned food", + "Hold cardboard", + "Hold cardboard piece", + "Hold cardboard pieces", + "Hold cardboard strip", + "Hold cardboard with ruler", + "Hold charger", + "Hold charger and cable", + "Hold charging cable", + "Hold cleaning cloth", + "Hold container", + "Hold container lid", + "Hold container of canned food", + "Hold craft tool", + "Hold device and cable", + "Hold earbud case", + "Hold electronic accessory", + "Hold electronic item", + "Hold empty container", + "Hold foam pieces", + "Hold instructional sign", + "Hold item", + "Hold item and adjust posture", + "Hold items", + "Hold items and inspect shelf", + "Hold items in hand", + "Hold newspaper", + "Hold paper lantern", + "Hold paper strip", + "Hold pen and paper", + "Hold phone", + "Hold pickle jar", + "Hold portable charger", + "Hold power adapter", + "Hold power bank and cable", + "Hold product", + "Hold product labels", + "Hold product package", + "Hold quilled paper coil", + "Hold quilled paper piece", + "Hold quilling paper", + "Hold recording sheet and pen", + "Hold ruler", + "Hold ruler and draw line", + "Hold ruler and mark cardboard", + "Hold ruler and marker", + "Hold ruler and pen steady", + "Hold ruler on cardboard", + "Hold ruler steady", + "Hold scissors", + "Hold small cardboard pieces", + "Hold small object", + "Hold small piece of ribbon", + "Hold small product bag", + "Hold small white box", + "Hold smartphone", + "Hold smartphone box", + "Hold snack package", + "Hold snack packages", + "Hold supplement bottle", + "Hold tray of canned goods", + "Hold utility knife", + "Hold water bottle", + "Holding marker", + "Identify next cardboard piece", + "Inflate paper star", + "Initiate star folding", + "Insert charging cable", + "Insert charging cable into power bank", + "Insert plug into power adapter", + "Inspect Dior gift box", + "Inspect almond package", + "Inspect and place item on shelf", + "Inspect bottle", + "Inspect cardboard piece", + "Inspect cardboard strip", + "Inspect charging case", + "Inspect electronic item", + "Inspect jar", + "Inspect product", + "Inspect product lid", + "Inspect shelf", + "Inspect shelf and organize stock", + "Inspect shelf condition", + "Inspect smartphone box", + "Inspect strip", + "Inspect supplement bottle", + "Interact with colleagues", + "Interact with phone", + "Interact with smartphone", + "Interact with smartphone screen", + "Interacting with phone screen", + "Interaction with coworker", + "Interlock paper strips", + "Labeling cardboard piece", + "Labeling cardboard square", + "Labeling cardboard squares", + "Lift blue strip", + "Lift pen and shift ruler", + "Lift pot lid", + "Lift utility knife", + "Lock phone", + "Look around the table", + "Look away", + "Manipulate adhesive strip", + "Manipulate and inspect colorful pieces", + "Manipulate bead", + "Manipulate beads", + "Manipulate cardboard piece", + "Manipulate cardboard shape", + "Manipulate cardboard sheet", + "Manipulate colorful pieces", + "Manipulate component", + "Manipulate component on strip", + "Manipulate craft paper strips", + "Manipulate craft piece", + "Manipulate folded paper star", + "Manipulate light blue strip", + "Manipulate material", + "Manipulate paper decoration", + "Manipulate paper edge", + "Manipulate paper piece", + "Manipulate paper quilling piece", + "Manipulate paper star", + "Manipulate paper stars", + "Manipulate paper strip", + "Manipulate paper strips", + "Manipulate plastic strip", + "Manipulate plastic strips", + "Manipulate power cable plug", + "Manipulate puzzle piece", + "Manipulate puzzle pieces", + "Manipulate quilled paper", + "Manipulate quilled paper shape", + "Manipulate quilled paper strip", + "Manipulate quilled paper strips", + "Manipulate quilling paper", + "Manipulate quilling strip", + "Manipulate ribbon knot", + "Manipulate ribbon piece", + "Manipulate small component", + "Manipulate small object", + "Manipulate small paper segment", + "Manipulate star", + "Manipulate yellow strip", + "Manipulating paper strips", + "Mark cardboard", + "Mark cardboard piece", + "Mark cardboard strip with pen", + "Mark cardboard with marker", + "Mark cardboard with pen", + "Mark cardboard with pen and ruler", + "Mark cardboard with ruler", + "Mark cardboard with ruler and pen", + "Mark fabric", + "Mark fabric with pen", + "Mark fabric with pen and ruler", + "Mark line on cardboard", + "Mark lines on cardboard", + "Mark lines with marker", + "Mark lines with pen along ruler", + "Mark list with pen", + "Mark paper list", + "Mark straight line", + "Marking cardboard piece", + "Marking cardboard with pen", + "Marking lines on cardboard", + "Measure and mark cardboard", + "Measure cardboard with ruler", + "Move Mahjong tile", + "Move along shelf", + "Move along the shelf", + "Move along the shelves", + "Move along the supermarket aisle", + "Move and place black buttons", + "Move away from collection box", + "Move away from desk", + "Move away from shelf", + "Move away from table", + "Move away from workstation", + "Move bin", + "Move bin to shelf area", + "Move black button", + "Move blue beads", + "Move box to next position", + "Move button to line", + "Move camera over surface", + "Move can towards shelf", + "Move canned goods container", + "Move cardboard", + "Move cardboard box", + "Move cardboard piece", + "Move cardboard sheet", + "Move cardboard to pile", + "Move container toward shelf", + "Move dustpan to side", + "Move hand", + "Move hand away", + "Move hand away from shelf", + "Move hand away from workspace", + "Move hand back to box", + "Move hand over button pile", + "Move hand to paper stars", + "Move hand toward craft materials", + "Move item to bag", + "Move marker and adjust hand", + "Move marker and ruler", + "Move marker away", + "Move orange buttons", + "Move origami stars", + "Move pen", + "Move pen aside", + "Move pen away", + "Move phone", + "Move piece to pile", + "Move pieces into box", + "Move pineapple chips", + "Move plastic storage bin", + "Move plush toy", + "Move pot", + "Move product to box", + "Move product to shelf", + "Move product towards shelf", + "Move puzzle piece", + "Move ruler", + "Move ruler and tools", + "Move scissors away", + "Move small blue foam piece towards the strip", + "Move smartphone", + "Move storage bin", + "Move through aisle", + "Move through the training room", + "Move to box", + "Move to desk", + "Move to next section", + "Move to shelf", + "Move to shelf base", + "Move to stock products", + "Move towards aisle", + "Move towards box", + "Move towards kitchen area", + "Move towards shelf", + "Move towards table", + "Move towards the stove", + "Move tray towards packing area", + "Move utility knife along ruler", + "Move vacuum cleaner", + "Move vacuum cleaner hose", + "Moving cardboard square", + "Moving hand", + "Moving hand towards cardboard stack", + "Moving ruler", + "Observe and pause", + "Observe and walk through store", + "Observe colleague and workspace", + "Observe craft layout", + "Observe desktop layout", + "Observe paper and count objects", + "Observe paper quilling station", + "Observe puzzle progress", + "Observe room", + "Observe shelf", + "Observe shelf status", + "Observe sorting progress", + "Observe stocking", + "Observe surroundings", + "Observe workspace", + "Open cardboard box", + "Open door", + "Open earbud case", + "Open folded paper lantern", + "Open paper lantern", + "Open paper lantern component", + "Open small case", + "Open stove pot lid", + "Open supplement bottle", + "Operate smartphone", + "Organize bag contents", + "Organize cardboard pieces", + "Organize item on shelf", + "Organize products", + "Organize snacks in box", + "Organize tools and materials", + "Pack beads into box", + "Peel blue strip", + "Peel foam strip", + "Pick up Dior gift box", + "Pick up Mahjong tile", + "Pick up accessory", + "Pick up and sort cardboard", + "Pick up another bottle", + "Pick up another canned item", + "Pick up another item", + "Pick up beads", + "Pick up black button", + "Pick up blue foam piece", + "Pick up blue paper strip", + "Pick up bottle", + "Pick up bottled sauce", + "Pick up button", + "Pick up can", + "Pick up canned food", + "Pick up canned good", + "Pick up canned goods", + "Pick up canned item", + "Pick up canned product", + "Pick up cardboard", + "Pick up cardboard cutout", + "Pick up cardboard piece", + "Pick up cardboard square", + "Pick up cardboard stack", + "Pick up cardboard strip", + "Pick up cardboard tray", + "Pick up cereal boxes", + "Pick up charging cable", + "Pick up charging case", + "Pick up cleaning cloth", + "Pick up colored tile", + "Pick up container", + "Pick up container from box", + "Pick up craft material", + "Pick up cut cardboard piece", + "Pick up dustpan", + "Pick up electronic accessory", + "Pick up electronic accessory from box", + "Pick up electronic device", + "Pick up electronic item", + "Pick up electronic product", + "Pick up food item", + "Pick up gift box", + "Pick up grocery item", + "Pick up item", + "Pick up item from bin", + "Pick up item from box", + "Pick up item from shelf", + "Pick up items from the shopping bag", + "Pick up jar", + "Pick up light blue strip", + "Pick up marker", + "Pick up metal ruler", + "Pick up new cardboard piece", + "Pick up new electronic product", + "Pick up new product from box", + "Pick up next gift box", + "Pick up next item from bin", + "Pick up next product from bin", + "Pick up nut bar box", + "Pick up object", + "Pick up oil bottle", + "Pick up orange button", + "Pick up pack from shelf", + "Pick up packaged paper lantern component", + "Pick up paper star", + "Pick up paper strip", + "Pick up paper towel", + "Pick up pasta box", + "Pick up pen", + "Pick up phone", + "Pick up pickle jar", + "Pick up pink water bottle", + "Pick up plastic bin", + "Pick up plastic container", + "Pick up plush toy", + "Pick up portable charger", + "Pick up power bank", + "Pick up product", + "Pick up product box", + "Pick up product from bin", + "Pick up product from box", + "Pick up product from shelf", + "Pick up puzzle piece", + "Pick up red button", + "Pick up retail item", + "Pick up sauce bottle", + "Pick up scissors", + "Pick up shopping bag", + "Pick up small cardboard piece", + "Pick up small item", + "Pick up small object", + "Pick up small piece of material", + "Pick up smartphone", + "Pick up snack package", + "Pick up snack packages", + "Pick up snack packs", + "Pick up snack pouch", + "Pick up spice jar", + "Pick up stapler", + "Pick up star", + "Pick up star bead", + "Pick up star-shaped bead", + "Pick up storage container", + "Pick up supplement bottle", + "Pick up supplies from box", + "Pick up tin can", + "Pick up tool", + "Pick up utility knife", + "Pick up water bottle", + "Pick up yellow item", + "Pick up yellow paper strip", + "Picking up bottle", + "Picking up crafting material", + "Picking up stock", + "Place Mahjong tile on stack", + "Place Mahjong tile on the stack", + "Place accessory box", + "Place accessory into box", + "Place accessory on shelf", + "Place and align button", + "Place and count bead", + "Place another canned food on shelf", + "Place back Dior gift box", + "Place bead on table", + "Place bottle back on shelf", + "Place box on shelf", + "Place button", + "Place button in group", + "Place button in row", + "Place can on shelf", + "Place canned food in bin", + "Place canned food in container", + "Place canned food on shelf", + "Place canned good on shelf", + "Place canned goods in container", + "Place canned product on shelf", + "Place cans into box", + "Place cardboard", + "Place cardboard piece", + "Place cardboard piece on stack", + "Place cardboard square", + "Place cardboard square on stack", + "Place cardboard strip", + "Place charger on table", + "Place charging case down", + "Place cloth on floor", + "Place colored tile", + "Place container in bin", + "Place container on floor", + "Place container on shelf", + "Place controller on table", + "Place crate on floor", + "Place device on lap", + "Place down paper pieces", + "Place down paper segment", + "Place down pen", + "Place down pink water bottle", + "Place down ruler and pen", + "Place down scissors", + "Place down strip", + "Place finished star on table", + "Place gift box into bin", + "Place gift box on shelf", + "Place hand on table", + "Place item back", + "Place item back on shelf", + "Place item in bag", + "Place item in container", + "Place item in shopping bag", + "Place item into bag", + "Place item into shopping bag", + "Place item on shelf", + "Place item on table", + "Place items on shelf", + "Place items on table", + "Place items on the shelf", + "Place jar in box", + "Place jar into shelf box", + "Place jar on shelf", + "Place ketchup bottle on shelf", + "Place knife down", + "Place lid back", + "Place marked piece down", + "Place marker down", + "Place material", + "Place oil in container", + "Place paper star", + "Place paper star in row", + "Place pen on cardboard", + "Place pen on table", + "Place phone down", + "Place phone on desk", + "Place phone on shelf", + "Place phone on table", + "Place pickle jar in box", + "Place piece into puzzle", + "Place plush toy into bag", + "Place plush toy on shelf", + "Place product in box", + "Place product on shelf", + "Place puzzle piece", + "Place quilled paper shape", + "Place red button", + "Place ribbon onto project", + "Place ruler on cardboard", + "Place sauce bottle on shelf", + "Place sauce in container", + "Place scissors aside", + "Place scissors down", + "Place scissors on table", + "Place smartphone down", + "Place smartphone on cardboard", + "Place smartphone on desk", + "Place smartphone on stand", + "Place smartphone on table", + "Place snack in box", + "Place snack on shelf", + "Place snack package in box", + "Place snack package on shelf", + "Place snack packages on shelf", + "Place snack pouch in container", + "Place snack pouch on shelf", + "Place spice jar in container", + "Place star", + "Place star in row", + "Place star on table", + "Place stars in container", + "Place stool on floor", + "Place storage container on floor", + "Place strip on table", + "Place supplement bottle in container", + "Place tool on table", + "Place towel", + "Place water bottle on table", + "Place white box on table", + "Placing labeled cardboard square", + "Placing labeled square", + "Placing paper strip", + "Placing pen on table", + "Placing phone down", + "Placing piece on stack", + "Placing stock on shelf", + "Plug cable into portable charger", + "Position cardboard for cutting", + "Position cardboard piece", + "Position cardboard strip", + "Position cardboard tray", + "Position cardboard tube", + "Position container near shelf", + "Position container on shelf", + "Position hands for work", + "Position ribbon piece", + "Position ruler and mark cardboard", + "Position ruler on cardboard", + "Position scissors", + "Position scissors for next cut", + "Position scissors to cut cardboard", + "Position shelving divider", + "Position the ruler", + "Position tray", + "Position utility knife", + "Position utility knife on cardboard", + "Positioning cardboard on workspace", + "Positioning paper strip", + "Positioning puzzle piece", + "Positioning ruler on cardboard", + "Prepare paper strip", + "Prepare to cut cardboard", + "Prepare to draw lines", + "Prepare to pick up item", + "Prepare to place bottle on shelf", + "Prepare to place cardboard", + "Prepare to place item in bag", + "Prepare to place product", + "Prepare to resume cutting", + "Prepare to sort beads", + "Preparing to craft", + "Press fold", + "Pull back hand", + "Pull paper strip", + "Push vacuum cleaner", + "Put down phone", + "Put down scissors", + "Put down smartphone", + "Put down utility knife", + "Put down water bottle", + "Putting away smartphone", + "Reach and sort buttons", + "Reach for Mahjong tiles", + "Reach for additional items", + "Reach for and examine canned goods", + "Reach for and pick up smartphone", + "Reach for another container", + "Reach for another item", + "Reach for beads", + "Reach for black button", + "Reach for button", + "Reach for can", + "Reach for canned food", + "Reach for canned goods", + "Reach for cardboard box", + "Reach for cardboard piece", + "Reach for cleaning supplies", + "Reach for container", + "Reach for craft items", + "Reach for empty shelf space", + "Reach for item", + "Reach for item in box", + "Reach for item on shelf", + "Reach for items", + "Reach for items in box", + "Reach for more pieces", + "Reach for next can", + "Reach for next canned food", + "Reach for next canned food item", + "Reach for next canned product", + "Reach for next item", + "Reach for next piece", + "Reach for next product", + "Reach for object", + "Reach for paper strip", + "Reach for paper strips", + "Reach for phone", + "Reach for product", + "Reach for product labels", + "Reach for product on shelf", + "Reach for puzzle piece", + "Reach for retail item", + "Reach for shelf", + "Reach for shelving divider", + "Reach for snack package", + "Reach for snack pouch", + "Reach for star", + "Reach for stars", + "Reach for utility knife", + "Reach for water bottle", + "Reach for wire hangers", + "Reach into bag", + "Reach into box", + "Reach towards shelf", + "Reaching for beads", + "Realign Mahjong tiles", + "Rearrange Mahjong tile", + "Rearrange Mahjong tiles", + "Rearrange shelf item", + "Record count", + "Record count on notepad", + "Record star count", + "Record star count on paper", + "Release and prepare new strip", + "Release bottle", + "Release cardboard", + "Release cardboard piece", + "Release cardboard piece and gesture", + "Release cardboard shape", + "Release container", + "Release folded paper", + "Release food item", + "Release hook", + "Release label", + "Release lantern", + "Release paper", + "Release paper coil", + "Release paper star", + "Release paper strip", + "Release pickle jar", + "Release product on shelf", + "Release puzzle piece", + "Release quilling strip", + "Release scissors", + "Release smartphone", + "Remove cardboard flap", + "Remove cardboard pattern", + "Remove cardboard pattern piece", + "Remove cleaning bottle", + "Remove item from bag", + "Remove item from shelf", + "Remove lid from container", + "Remove paper lantern part from packaging", + "Remove plastic container from shelf", + "Remove plastic container from storage box", + "Remove plastic packaging", + "Remove ruler", + "Remove ruler and marker", + "Remove shelf label", + "Remove storage bin from shelf", + "Reorganize bin contents", + "Reposition and cut", + "Reposition cardboard for cutting", + "Reposition hand", + "Reposition hands", + "Reposition hands and ruler", + "Reposition marker", + "Reposition newspaper", + "Reposition pen and prepare for next line", + "Reposition ruler", + "Reposition ruler and pen", + "Reposition scissors", + "Reposition sign and organize beads", + "Reposition tools", + "Reposition utility knife", + "Repositioning ruler", + "Repositioning ruler and cardboard", + "Resume counting stars", + "Resume observation", + "Resume sorting blue beads", + "Resume writing on paper", + "Retract camera/reposition view", + "Retract hand", + "Retract hand from bag", + "Retrieve another container", + "Retrieve canned food from box", + "Retrieve hand to table", + "Retrieve items from bag", + "Retrieve next canned food item", + "Retrieve paper strip", + "Retrieve paper strips", + "Retrieve snack from container", + "Retrieve star", + "Retrieving more beads", + "Return to sorting", + "Reviewing count record", + "Rinse cloth in sink", + "Roll quilling paper", + "Rolling paper strip", + "Rub hands together", + "Scan for next piece", + "Scan supermarket shelves", + "Score cardboard", + "Scroll on smartphone", + "Scroll smartphone screen", + "Scroll through photo gallery", + "Scrolling and viewing content on phone", + "Scrolling or navigating on phone", + "Search for puzzle piece", + "Secure paper edges with adhesive", + "Secure ribbon with needle", + "Securing paper structure", + "Select a bottle", + "Select and pick up a canned item", + "Select another item", + "Select paper strip", + "Select product from box", + "Selecting new paper strip", + "Separate cardboard piece", + "Set down scissors and pick up power bank", + "Set down utility knife", + "Slide utility knife along ruler", + "Sort Mahjong tiles", + "Sort and adjust button line", + "Sort and arrange buttons", + "Sort and arrange cardboard pieces", + "Sort and count beads", + "Sort and place buttons", + "Sort and place paper star", + "Sort and stack cardboard pieces", + "Sort beads", + "Sort beads and write count", + "Sort beads by color", + "Sort beads by hand", + "Sort beads on table", + "Sort beads on the table", + "Sort blue beads", + "Sort blue star-shaped pieces", + "Sort button", + "Sort button by color", + "Sort buttons", + "Sort buttons by color", + "Sort canned goods in tray", + "Sort colored tiles", + "Sort colorful pieces", + "Sort craft items", + "Sort cut cardboard", + "Sort light blue origami stars", + "Sort orange button", + "Sort orange buttons", + "Sort origami stars", + "Sort origami stars by color", + "Sort paper star", + "Sort paper stars", + "Sort plastic pieces", + "Sort purple beads", + "Sort purple star-shaped objects", + "Sort puzzle pieces", + "Sort quilled paper pieces", + "Sort small colorful pieces", + "Sort small craft pieces", + "Sort small objects", + "Sort small plastic pieces", + "Sort star-shaped beads", + "Sort star-shaped objects", + "Sort star-shaped objects by color", + "Sort tiles", + "Sort tiles by color", + "Sort yellow star-shaped objects", + "Sorting buttons", + "Sorting colorful paper pieces", + "Sorting paper stars", + "Stabilize cardboard", + "Stabilize ruler", + "Stack cardboard pieces", + "Stack cardboard square", + "Stack cardboard squares", + "Stacking cardboard pieces", + "Stacking cardboard square", + "Stacking cardboard squares", + "Stand up and walk away", + "Start cutting", + "Start folding paper strip", + "Starting to label next square", + "Stir contents", + "Stop measuring and put down tools", + "Stop sorting stars", + "Sweep debris", + "Sweep floor debris", + "Switch to scissors", + "Switching marker", + "Tap smartphone screen", + "Tapping on smartphone screen", + "Tapping smartphone screen", + "Tear newspaper", + "Tear off cardboard segment", + "Touch canned goods", + "Touch pieces in box", + "Touch shelf edge", + "Trace pattern on cardboard", + "Transition to cutting", + "Transition to standing position", + "Trim cardboard", + "Trim cardboard piece", + "Type on smartphone", + "Typing message on smartphone", + "Typing on phone", + "Typing on smartphone", + "Update paper record", + "Use phone", + "Use phone to check instructions", + "Use phone to check stock", + "Use phone while crafting", + "Use smartphone", + "Vacuum edge of carpet", + "Vacuum the carpet", + "Vacuuming along the wall edge", + "Vacuuming carpet corner", + "Vacuuming carpet edge", + "Vacuuming the carpet edge", + "View content on smartphone", + "View phone screen", + "Viewing phone screen", + "Walk across office", + "Walk across room", + "Walk across the room", + "Walk away", + "Walk in hallway", + "Walk through corridor", + "Walk through doorway", + "Walk through hallway", + "Walk through office", + "Walk through store", + "Walk through workspace", + "Walk towards aisle", + "Walk towards desk", + "Walk towards next aisle", + "Walk towards other aisles", + "Walk towards room", + "Walk towards shelf", + "Walk towards shelves", + "Walk towards storage area", + "Walk towards table", + "Walk towards workspace", + "Walk with cardboard", + "Walk with cardboard cutout", + "Walk with marker", + "Walk with shopping bag", + "Walking across the room", + "Walking along the aisle", + "Walking in the hallway", + "Walking in the workspace", + "Walking through classroom", + "Walking through office hallway", + "Walking through the office", + "Walking to sink", + "Walking towards door", + "Walking towards workstation", + "Washing hands", + "Washing hands in sink", + "Wipe down shelf", + "Wipe electronic item", + "Wipe food product", + "Wipe grocery shelf", + "Wipe item", + "Wipe jar", + "Wipe ketchup bottle", + "Wipe kitchen counter", + "Wipe product", + "Wipe retail item", + "Wipe shelf", + "Wipe shelf surface", + "Wipe the plastic jar", + "Wipe the product jar", + "Wipe the shelf", + "Wiping countertop", + "Withdraw hand", + "Write count on paper", + "Write on notepad", + "Write on paper", + "Write on paper record", + "Writing on notepad", + "fold purple ribbon", + "sort craft materials" + ], + "subtask_options": [ + "Adding items to shopping container", + "Adjust Mahjong tiles", + "Adjust and align Mahjong tiles", + "Adjust and cut fabric", + "Adjust fabric for cutting", + "Adjust lantern string and handle components", + "Adjust position and check phone", + "Adjust tile alignment", + "Adjust tiles on stack", + "Adjust, move, and realign Mahjong tiles", + "Adjusting a puzzle piece", + "Adjusting and folding cardboard", + "Adjusting and placing down paper pieces", + "Adjusting and securing paper structure", + "Adjusting canned goods on the shelf", + "Adjusting cardboard divider", + "Adjusting cardboard layout", + "Adjusting container positions", + "Adjusting cookware", + "Adjusting edge and marking cardboard", + "Adjusting items and reaching for stock", + "Adjusting items on shelf", + "Adjusting items on the shelf", + "Adjusting marker and ruler", + "Adjusting paper edge and placing strip", + "Adjusting posture while holding item", + "Adjusting puzzle piece", + "Adjusting retail items on shelf", + "Adjusting ruler position", + "Adjusting snack package", + "Adjusting stock and finishing placement", + "Align and fold newspaper", + "Align canned goods on shelf", + "Align paper lantern edges", + "Align ruler and draw line", + "Aligning button rows", + "Aligning canned goods on the shelf", + "Aligning cardboard for cutting", + "Aligning cardboard strip", + "Aligning plastic containers on the shelf", + "Aligning ruler for final measurements", + "Approach inventory boxes", + "Approaching restocking supplies", + "Approaching the stove", + "Approaching workstation", + "Arrange Mahjong tiles", + "Arrange buttons", + "Arrange buttons in a line", + "Arrange paper strips", + "Arrange tiles into row", + "Arranging and marking cardboard strips", + "Arranging buttons", + "Arranging buttons on the table", + "Arranging cardboard squares", + "Arranging items on shelf", + "Arranging orange buttons", + "Arranging paper stars", + "Arranging products on shelf", + "Arranging shelf display", + "Arranging star-shaped beads", + "Assembling cardboard base", + "Assembling cardboard boxes", + "Assembling material pieces", + "Assembling small decorative components", + "Assembling the foam base loop", + "Assessing shelf arrangement", + "Assessing shelf status and relocating", + "Attaching and folding blue foam strips", + "Bagging a held electronic item", + "Beginning to roll the quilling strip", + "Bend and shape paper strips", + "Bending plastic strip", + "Boxing pieces and picking up phone", + "Browse and interact with phone interface", + "Browse mobile phone", + "Browse mobile phone and cut newspaper", + "Browsing and selecting canned goods", + "Browsing phone interface", + "Browsing photo gallery", + "Browsing smartphone", + "Browsing smartphone content", + "Bundle display hooks", + "Cap marker and place down", + "Capping marker and positioning ruler", + "Carry cereal boxes to aisle", + "Carry shopping bag", + "Charging power bank", + "Check instructions on phone", + "Checking cooking pot", + "Checking smartphone", + "Checking smartwatch while reaching for product", + "Checking stock information", + "Clean and inspect shelf", + "Clean shelf and stock product", + "Clean shelf surface", + "Cleaning and boxing jars", + "Cleaning and organizing products in boxes", + "Cleaning cloth maintenance", + "Cleaning kitchen surfaces", + "Cleaning products and retrieving items from boxes", + "Cleaning shelves and handling pickle jars", + "Cleaning shelves and rearranging products", + "Cleaning shelves and relocating", + "Cleaning up workspace and moving items", + "Cleaning up workstation", + "Cleaning workspace", + "Cleaning, bagging, and selecting another item", + "Cleaning, inspecting, and bagging an electronic item", + "Clear workspace and pick up phone", + "Clearing space on the shelf", + "Collecting canned food into bin", + "Collecting origami stars", + "Comparing and replacing bottles", + "Complete folding and place star on table", + "Completing list and moving away from desk", + "Completing marking and stepping away", + "Connecting power cables to a portable charger", + "Cooking at the stove", + "Count beads and retrieve more", + "Counting and recording paper stars", + "Counting and recording stars", + "Crafting with paper strips", + "Cut along the marked line", + "Cut along the newspaper edge", + "Cut and fold cardboard", + "Cut and release cardboard", + "Cut and reposition utility knife", + "Cut and tear off cardboard segment", + "Cut cardboard", + "Cut cardboard pattern", + "Cut cardboard with utility knife", + "Cut fabric with scissors", + "Cut light green fabric", + "Cut light green fabric and reposition scissors", + "Cut newspaper and place scissors on table", + "Cut out cardboard pattern", + "Cut section from newspaper", + "Cutting and adjusting cardboard", + "Cutting and adjusting cardboard pieces", + "Cutting and adjusting cardboard sheet", + "Cutting and adjusting scissors", + "Cutting and folding cardboard", + "Cutting and folding cardboard shapes", + "Cutting and gathering cardboard", + "Cutting and measuring cardboard", + "Cutting and organizing cardboard pieces", + "Cutting and pausing", + "Cutting and picking up new cardboard", + "Cutting and placing cardboard", + "Cutting and placing cardboard piece", + "Cutting and placing cardboard squares", + "Cutting and preparing cardboard pieces", + "Cutting and releasing cardboard piece", + "Cutting and releasing cardboard shapes", + "Cutting and repositioning cardboard", + "Cutting and separating cardboard pieces", + "Cutting and sorting cardboard squares", + "Cutting and stacking cardboard pieces", + "Cutting cardboard", + "Cutting cardboard and picking up smartphone", + "Cutting cardboard and placing down scissors", + "Cutting cardboard and placing knife down", + "Cutting cardboard and putting down scissors", + "Cutting cardboard and retrieving power bank", + "Cutting cardboard into strips", + "Cutting cardboard into triangles", + "Cutting cardboard piece", + "Cutting cardboard pieces", + "Cutting cardboard pieces with scissors", + "Cutting cardboard shapes", + "Cutting cardboard sheet", + "Cutting cardboard square", + "Cutting cardboard strip", + "Cutting cardboard strips", + "Cutting cardboard strips with scissors", + "Cutting cardboard triangles", + "Cutting cardboard tube", + "Cutting cardboard tube and setting aside scissors", + "Cutting cardboard with a utility knife", + "Cutting cardboard with scissors", + "Cutting cardboard with scissors and checking phone", + "Cutting cardboard with utility knife", + "Cutting initial cardboard pieces", + "Cutting newspaper", + "Cutting triangular cardboard pieces", + "Depositing cardboard squares", + "Document bead counts", + "Draw and reposition ruler", + "Draw lines and patterns on cardboard", + "Draw lines using a ruler", + "Drawing grid lines", + "Drawing grid lines and repositioning cardboard", + "Drawing grid lines with a pen", + "Drawing grid lines with a ruler", + "Drawing grid lines with a ruler and pen", + "Drawing guide lines on cardboard", + "Drawing lines along ruler", + "Drawing lines and checking smartphone", + "Drawing lines on cardboard", + "Entering the training area", + "Examine yellow item", + "Examining a product", + "Expand and adjust lantern shape", + "Expand paper lantern", + "Extract wire hangers from inventory", + "Fetching materials", + "Final alignment and marking", + "Final alignment of lantern edges", + "Final button arrangement", + "Final cardboard cutting", + "Final component assembly", + "Final trimming of cardboard", + "Finalize wiping and placement of ketchup bottle", + "Finalizing and releasing folded paper", + "Finalizing cuts and storing tools", + "Finalizing item placement into shopping bag", + "Finalizing marks on cardboard", + "Finalizing paper star", + "Finalizing shelf organization", + "Finalizing shelf placement", + "Finalizing shelf placement and moving bin", + "Finalizing the craft assembly", + "Fine-tuning bead placement", + "Finish and place origami star", + "Finish cutting along the marked line and reposition", + "Finishing coil and selecting new strip", + "Finishing cut and placing scissors down", + "Finishing cutting and switching to phone", + "Finishing segment and placing scissors", + "Fold and grasp lantern", + "Fold paper star", + "Fold paper strip", + "Fold paper strip into knot", + "Fold paper strip into lucky star", + "Fold paper strip into star", + "Folding and organizing paper strips", + "Folding and positioning cardboard", + "Folding and shaping ribbon", + "Folding and sorting paper stars", + "Folding and sorting paper stars while handling a water bottle", + "Folding cardboard", + "Folding cardboard and checking phone", + "Folding cardboard and handling utility knife", + "Folding cardboard and preparing marker", + "Folding cardboard edge", + "Folding lucky star", + "Folding paper strip", + "Folding paper strip into lucky star", + "Folding paper strips", + "Folding paper strips while using phone", + "Folding plastic strip", + "Folding purple paper strip", + "Folding purple ribbon", + "Form paper strip into a star", + "Forming quilled paper shapes", + "Forming ribbon knot", + "Gather and hold beads", + "Gathering and boxing inventory", + "Gathering and boxing plastic pieces", + "Gathering cardboard pieces", + "Gathering colored beads", + "Gathering items", + "Gathering materials and walking", + "Gathering star beads", + "Grasp lantern component", + "Grasp paper strip", + "Grasping and placing products on shelf", + "Greeting participants", + "Guiding utility knife along ruler", + "Handle and prepare paper coil", + "Handle container from box", + "Handle crate of cans", + "Handle paper lantern component", + "Handle power bank and cable", + "Handling and organizing containers", + "Handling charging cables", + "Handling container lid", + "Handling earbud case", + "Handling electronic device", + "Handling miscellaneous items", + "Handling plastic strip", + "Handling shipping box", + "Handling snack packages", + "Hang shopping bag and exit area", + "Hold and carry tray of canned goods", + "Hold and cut newspaper with scissors", + "Hold and mark cardboard piece", + "Hold blue product box", + "Hold instructional sign", + "Hold newspaper", + "Hold paper strip", + "Hold quilling paper", + "Hold small object", + "Hold small white box", + "Holding a smartphone", + "Holding and adjusting cardboard", + "Holding and aligning paper strip", + "Holding and bagging a smartphone box", + "Holding and creasing purple paper", + "Holding and grasping product bags", + "Holding and inspecting product", + "Holding and organizing product packages", + "Holding and retrieving paper strips", + "Holding and rotating paper strip", + "Holding cardboard pieces", + "Holding cardboard with ruler", + "Holding container of canned food", + "Holding pen and paper", + "Holding smartphone", + "Holding writing materials", + "Inflate paper star", + "Initiating assembly", + "Inspect product", + "Inspect shelf condition", + "Inspect shelf condition and observe surroundings", + "Inspecting Dior gift box", + "Inspecting almond package and scanning shelves", + "Inspecting and approaching shelf", + "Inspecting and bagging a smartphone box", + "Inspecting and folding cardboard pieces", + "Inspecting and packing supplement bottle", + "Inspecting and placing cans on shelf", + "Inspecting and placing cardboard strips", + "Inspecting and stocking shelf items", + "Inspecting bottle", + "Inspecting cardboard", + "Inspecting pieces and switching to scissors", + "Inspecting shelf contents", + "Inspecting supplement bottle", + "Inspecting the cleaned plastic jar", + "Install display hooks", + "Interacting with coworker", + "Interacting with phone", + "Interlocking the craft strips", + "Interruption: handling charging case", + "Labeling and organizing cardboard squares", + "Labeling and placing cardboard square", + "Labeling and placing cardboard squares", + "Labeling and retrieving cardboard pieces", + "Labeling and switching markers", + "Labeling cardboard pieces", + "Labeling cardboard square", + "Labeling cardboard squares", + "Leaving the room and retrieving object", + "Managing shopping container", + "Manipulate adhesive strip", + "Manipulate and inspect colorful pieces", + "Manipulate and release paper strips", + "Manipulate colorful pieces", + "Manipulate craft pieces", + "Manipulate light blue strip", + "Manipulate paper decoration", + "Manipulate paper edge", + "Manipulate paper piece", + "Manipulate paper strip", + "Manipulate paper strips", + "Manipulate puzzle piece", + "Manipulate puzzle pieces", + "Manipulate quilled paper strip", + "Manipulate small paper segment", + "Manipulate star and prepare next strip", + "Manipulating and placing paper shapes", + "Manipulating and placing strip components", + "Manipulating and releasing paper strips", + "Manipulating and releasing quilling strips", + "Manipulating beads", + "Manipulating cardboard and picking up scissors", + "Manipulating cardboard piece", + "Manipulating cardboard shapes", + "Manipulating components on a strip", + "Manipulating paper quilling piece", + "Manipulating paper star", + "Manipulating paper stars", + "Manipulating paper strip", + "Manipulating paper strips", + "Manipulating plastic strip", + "Manipulating puzzle pieces", + "Manipulating quilled paper", + "Manipulating ribbon piece", + "Manipulating small object", + "Manipulating tools and quilling materials", + "Manipulating yellow strips", + "Mark cardboard for cutting", + "Mark cardboard with marker", + "Mark fabric", + "Mark fabric and reposition ruler", + "Mark fabric with pen and remove ruler", + "Mark fabric with pen and ruler", + "Mark lines on cardboard", + "Marking and cutting cardboard", + "Marking and positioning cardboard", + "Marking cardboard", + "Marking cardboard and preparing to cut", + "Marking cardboard measurements", + "Marking cardboard piece", + "Marking cardboard piece and preparing workspace", + "Marking cardboard pieces", + "Marking cardboard squares", + "Marking cardboard with pen", + "Marking dimensions on cardboard", + "Marking grid lines", + "Marking guidelines on cardboard", + "Marking lines and repositioning ruler", + "Marking lines on cardboard", + "Marking lines with pen", + "Marking list and moving blue beads", + "Marking list and sorting beads", + "Marking paper and adjusting piles", + "Measure and mark cardboard with ruler", + "Measuring and adjusting workspace", + "Measuring and marking cardboard", + "Measuring and marking cardboard for crafting", + "Measuring and marking cardboard for cutting", + "Measuring and marking cardboard with ruler", + "Monitoring task progress via smartwatch", + "Move product towards shelf", + "Move to stocking area", + "Move towards shelf and position tray", + "Moving along the aisle", + "Moving along the aisle to assess stock", + "Moving along the shelves", + "Moving and adjusting the vacuum cleaner", + "Moving around the kitchen", + "Moving away from and returning to the table", + "Moving away from workstation", + "Moving cardboard cutouts", + "Moving cardboard pieces across the workspace", + "Moving container and stocking items", + "Moving hand over pile and sorting orange buttons", + "Moving orange buttons", + "Moving orange buttons and interacting with smartphone", + "Moving origami stars", + "Moving plastic storage bin", + "Moving the vacuum cleaner", + "Moving through the room", + "Moving through workspace", + "Moving to workspace", + "Moving towards aisle", + "Moving utility knife along ruler", + "Moving, placing, and adjusting puzzle pieces", + "Navigating store and browsing shelves", + "Observe puzzle progress", + "Observe workspace", + "Observe workspace and reach for beads", + "Observing and pausing", + "Observing restocking needs", + "Observing shelf and relocating to next aisle", + "Observing workspace", + "Opening cardboard box", + "Operate and release smartphone", + "Organize and count beads", + "Organize inventory and reach for products", + "Organizing buttons into patterns", + "Organizing canned goods in container", + "Organizing cans into a storage box", + "Organizing cardboard pieces", + "Organizing container contents", + "Organizing paper pieces into piles", + "Organizing paper strips", + "Organizing pickle jars and maintaining cleaning tools", + "Organizing products into box", + "Organizing products on shelf", + "Organizing shelf and placing plush toy into bag", + "Organizing shelf display", + "Organizing shelf products", + "Organizing shelf workspace", + "Organizing snack packages in box", + "Organizing snack pouches into containers", + "Organizing snacks in box", + "Organizing stars into a row", + "Organizing tools and materials", + "Pack beads into box", + "Paper quilling craft", + "Peeling and disposing of shelf labels", + "Performing precision cuts on cardboard", + "Pick up and begin folding paper strip", + "Pick up and deposit beads into box", + "Pick up and inspect light blue strip", + "Pick up and place accessory on shelf", + "Pick up and place buttons", + "Pick up and place canned goods on shelf", + "Pick up and place product on shelf", + "Pick up and place puzzle piece", + "Pick up and place star-shaped beads", + "Pick up and place tiles on stack", + "Pick up cereal boxes", + "Pick up electronic accessory from box", + "Pick up grocery item", + "Pick up product from box", + "Pick, place, and count beads", + "Picking and moving items to shelf", + "Picking and placing items from bin onto shelves", + "Picking and stocking items from container", + "Picking up and bagging a charging cable", + "Picking up and bagging an electronic item", + "Picking up and packing products", + "Picking up and placing canned goods", + "Picking up and placing tiles", + "Picking up canned goods", + "Picking up knife and cutting cardboard", + "Place accessory on shelf", + "Place and adjust items on shelf", + "Place and retrieve items for stocking", + "Place canned food on shelf", + "Place down paper segment and reach for supplies", + "Place down paper strip", + "Place grocery item on shelf", + "Place product on shelf", + "Place puzzle piece", + "Place white box, adjust smartphone, and resume sorting", + "Placing and adjusting plush toys", + "Placing and arranging cans on the shelf", + "Placing and retrieving canned goods", + "Placing and scanning for puzzle pieces", + "Placing and searching for puzzle pieces", + "Placing canned food onto shelf", + "Placing canned goods on the shelf", + "Placing canned goods onto the shelf", + "Placing canned goods onto the shelf and retrieving container", + "Placing cans onto the shelf", + "Placing cardboard piece", + "Placing container on floor", + "Placing containers on the shelf", + "Placing down scissors", + "Placing held items on shelf", + "Placing items and checking phone", + "Placing items and returning to box", + "Placing items and transitioning", + "Placing items into and organizing shopping bag", + "Placing items into the bin", + "Placing items on shelf", + "Placing items on shelf and moving box", + "Placing items on shelf and retrieving new items", + "Placing items on the shelf", + "Placing jar on shelf", + "Placing product bags on shelf", + "Placing products on shelf", + "Placing ribbon onto project", + "Placing snack packages in box", + "Placing snack packages on shelf", + "Placing, rearranging, and cleaning shelf items", + "Position ruler and draw initial lines", + "Position tray and reach for beads", + "Position utility knife and begin cutting", + "Positioning and cutting cardboard", + "Positioning and cutting cardboard piece", + "Positioning cardboard piece", + "Positioning cardboard pieces", + "Positioning container near the shelf", + "Positioning newspaper and scissors", + "Positioning paper strip", + "Positioning puzzle piece", + "Positioning ribbon piece", + "Positioning ruler and drawing lines", + "Positioning ruler for cutting", + "Positioning ruler for measurement", + "Positioning scissors to cut cardboard", + "Positioning shelving dividers", + "Positioning the container on the floor", + "Positioning utility knife", + "Preparation and initial cutting with utility knife", + "Prepare for further marking", + "Prepare shelf for stocking", + "Prepare to cut cardboard", + "Prepare tools for marking", + "Prepare workspace and tools", + "Preparing and folding cardboard", + "Preparing container on shelf", + "Preparing craft area", + "Preparing for further sorting", + "Preparing materials", + "Preparing materials and positioning hands for quilling", + "Preparing shopping bag", + "Preparing to organize container bin", + "Preparing tools and materials", + "Preparing workspace", + "Preparing workspace for craft activity", + "Preparing workstation", + "Pushing the vacuum cleaner", + "Reach for and adjust Mahjong tiles", + "Reach for items in box", + "Reach for, pick up, and attempt to fit puzzle piece", + "Reaching for and adjusting shelf containers", + "Reaching for and picking up stars", + "Reaching for products", + "Reaching for products and preparing the shelf", + "Reaching for utility knife", + "Reaching into the box for more stock", + "Rearrange Mahjong tile", + "Rearrange Mahjong tiles", + "Rearranging containers on the shelf", + "Rearranging items from shelf back to box", + "Recording star count", + "Refining bead arrangement with marker", + "Refining button layout", + "Refining cardboard cuts", + "Release and adjust puzzle piece", + "Release and prepare new strip", + "Release paper strip", + "Release scissors and operate smartphone", + "Releasing paper and reaching for phone", + "Releasing scissors", + "Relocating storage bins along the aisle", + "Remove packaging and prepare component", + "Remove tools after marking", + "Removing and discarding damaged items", + "Removing items from bag and stocking them", + "Removing labels and moving along the shelf", + "Removing old shelf labels", + "Reorganize items in box", + "Reorganizing stock on shelf", + "Replenishing shelf stock", + "Reposition and cut cardboard", + "Reposition and cut newspaper", + "Reposition ruler and draw lines", + "Reposition sign and organize beads", + "Repositioning and cutting cardboard pieces", + "Repositioning stool for the next section", + "Restocking pineapple chips", + "Resuming cardboard cutting", + "Resuming cutting", + "Resuming cutting cardboard", + "Resuming recording star count", + "Resuming sorting paper stars", + "Retrieve and move cardboard tray", + "Retrieve and transport cereal", + "Retrieve food items from boxes", + "Retrieve product from box", + "Retrieve snack packs", + "Retrieving additional supplies", + "Retrieving and carrying containers", + "Retrieving and examining items from bag", + "Retrieving and placing canned goods", + "Retrieving and shelving container", + "Retrieving cleaning supplies", + "Retrieving items for bag placement", + "Retrieving items from bag", + "Retrieving items from boxes", + "Retrieving items from shelf", + "Retrieving materials", + "Retrieving next product", + "Retrieving plastic container and moving to aisle", + "Retrieving smartphone", + "Retrieving tools from bag", + "Returning Dior gift box to shelf", + "Returning canned goods to shelf", + "Returning to desk", + "Returning to desk and setting up smartphone", + "Returning to table and placing controller", + "Returning to the workspace", + "Returning to work table", + "Returning to workspace", + "Returning to workstation", + "Reviewing and organizing records", + "Reviewing craft instructions", + "Reviewing new product labels", + "Roll quilling paper", + "Rolling paper strips into coils", + "Scanning workspace", + "Scoring and cutting cardboard", + "Scrolling and placing smartphone down", + "Scrolling and setting down smartphone", + "Scrolling and tapping on smartphone", + "Scrolling and viewing content on phone", + "Scrolling on smartphone", + "Scrolling smartphone screen", + "Search for and pick up puzzle piece", + "Secure lantern with adhesive", + "Secure paper edges with adhesive", + "Securing ribbon with needle", + "Select and handle paper strips", + "Selecting a bottle", + "Selecting and bagging electronic accessories", + "Selecting and collecting bottled goods", + "Selecting and collecting oil bottles", + "Selecting and evaluating items", + "Selecting and manipulating paper strips", + "Selecting and packing spice jars", + "Selecting and picking up canned goods", + "Setting down water and picking up phone", + "Setting up smartphone", + "Sliding utility knife along ruler", + "Sort Mahjong tiles", + "Sort and adjust button line", + "Sort and arrange buttons", + "Sort and combine bead piles", + "Sort and group beads", + "Sort and place buttons", + "Sort and record bead counts", + "Sort beads", + "Sort beads and adjust phone", + "Sort beads and adjust tray position", + "Sort beads and record count", + "Sort beads by color", + "Sort beads by hand", + "Sort beads on table", + "Sort beads on the table", + "Sort buttons", + "Sort buttons by color", + "Sort canned goods in tray", + "Sort colorful paper pieces", + "Sort colorful pieces", + "Sort craft materials into piles", + "Sort purple beads", + "Sort puzzle pieces", + "Sort small colorful pieces", + "Sort small craft pieces", + "Sort star-shaped beads", + "Sorting and collecting cardboard squares", + "Sorting and counting beads", + "Sorting and grouping buttons", + "Sorting and processing cardboard strips", + "Sorting and reaching for pieces", + "Sorting and reaching for plastic pieces", + "Sorting and stacking cardboard pieces", + "Sorting beads by color", + "Sorting blue beads and marking list", + "Sorting blue beads and writing on paper", + "Sorting buttons", + "Sorting buttons by color", + "Sorting cardboard pieces", + "Sorting cardboard shapes and holding marker", + "Sorting colorful paper stars", + "Sorting gift boxes into a bin", + "Sorting light blue origami stars", + "Sorting orange button", + "Sorting orange buttons", + "Sorting origami stars", + "Sorting origami stars by color", + "Sorting pieces and retrieving smartphone", + "Sorting pieces and writing on paper", + "Sorting purple star-shaped objects", + "Sorting quilled paper pieces", + "Sorting small colored tiles", + "Sorting small star-shaped plastic pieces", + "Sorting squares and preparing for next cut", + "Sorting star-shaped objects", + "Sorting star-shaped objects by color", + "Sorting tiles by color", + "Sorting yellow star-shaped objects", + "Stabilizing cardboard for cutting", + "Stacking and organizing cardboard", + "Stacking cardboard pieces", + "Stacking cardboard squares", + "Steadying the ruler and pen", + "Stock multiple products on shelf", + "Stocking and repositioning box", + "Stocking canned goods", + "Stocking canned goods onto the shelf", + "Stocking containers on the shelf", + "Stocking gift boxes on the shelf", + "Stocking items and carrying container", + "Stocking items and reaching for container", + "Stocking jars on shelf", + "Stocking miscellaneous products on shelf", + "Stocking multiple cans on the shelf", + "Stocking product boxes", + "Stocking products and reorganizing bin", + "Stocking products from bin onto shelf", + "Stocking products on shelf", + "Stocking sauce bottles on shelf", + "Stocking snack packets on the shelf", + "Stocking snack pouches on the shelf", + "Stop measuring and transition to smartphone usage", + "Stopping sorting activity", + "Sweeping floor debris", + "Taking a break to drink water and check phone", + "Tapping and putting away smartphone", + "Tear newspaper", + "Tearing and preparing blue foam pieces", + "Tidying workspace", + "Touch pieces in box and interact with colleagues", + "Touching canned goods", + "Trace and remove pattern", + "Trace and remove pattern piece", + "Transferring items from shelf to shopping bag", + "Transferring products from box to shelf", + "Transition to new product selection", + "Transitioning and observing workspace", + "Transitioning from jar to tin can", + "Transitioning from utility knife to scissors", + "Transitioning to cutting", + "Transitioning to new workstation", + "Transitioning to smartphone usage", + "Transport cereal to shelf", + "Transport pasta to shelf", + "Transporting cardboard to collection area", + "Transporting snack packages to shelf", + "Trimming and placing cardboard pieces", + "Trimming and stacking cardboard pieces", + "Trimming cardboard piece", + "Typing and navigating on phone", + "Typing message on smartphone", + "Typing on smartphone", + "Typing on smartphone while working with paper", + "Unfold paper lantern", + "Unpack additional lantern component", + "Unpack and place items on shelf", + "Use smartphone", + "Using a smartphone", + "Using and placing phone", + "Using phone", + "Using phone and drinking water", + "Using phone and resuming work", + "Using smartphone", + "Using smartphone as a guide on cardboard", + "Vacuuming along the wall edge", + "Vacuuming the carpet", + "Vacuuming the carpet corner", + "Vacuuming the carpet edge", + "Walk to and approach packing area", + "Walk to shelf location", + "Walking along the aisle", + "Walking in workspace", + "Walking through office", + "Walking through the room", + "Walking through workspace", + "Walking to and approaching workspace", + "Walking to storage area", + "Walking to the crafting area", + "Walking to workspace", + "Walking to workstation", + "Walking towards the desk", + "Walking towards workstation", + "Washing hands", 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Try lowering --min-label-fraction." + } + ], + "notes": [ + "Shard media and sensor-feature paths remain in shard output directories.", + "Assistant answers are strict JSON for episode understanding, not robot-control policies.", + "Merged label options are recomputed globally across all shards.", + "Episodes with no labeled windows under the configured label rule are skipped and reported." + ] +} \ No newline at end of file diff --git a/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/dataset/episode_manifest.json b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/dataset/episode_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..7943da1935ad5a8673550c0d1c0a3a9705339938 --- /dev/null +++ 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b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/dataset/target_manifest.json @@ -0,0 +1,22 @@ +{ + "status": "pass", + "input_dataset_jsonl": "results/omni_finetune/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_dataset/dataset.jsonl", + "output_jsonl": "results/omni_finetune/xperience10m_cosmos3_camera_pose_targets_20260608/dataset_with_cosmos_actions.jsonl", + "domain_name": "camera_pose", + "raw_action_dim": 9, + "chunk_size": 8, + "resolution_tier": 480, + "view_point": "ego_view", + "target_kind": "slam_camera_pose_delta_proxy_v1", + "counts": { + "rows_seen": 3808, + "rows_augmented": 3808 + }, + "episode_annotation_files_read": 119, + "issues": [], + "limitations": [ + "This is an egocentric camera-motion proxy, not a robot gripper or human hand-control action.", + "Use it for Cosmos3 action-packer and one-episode overfit smoke tests before claiming model-quality improvement.", + "Fit any normalization on train episodes only before a full publishable Cosmos adapter run." + ] +} diff --git a/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/eval/RUN_REPORT.md b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/eval/RUN_REPORT.md new file mode 100644 index 0000000000000000000000000000000000000000..bf7416d3025de929f1f396515a43b346c331bdf4 --- /dev/null +++ b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/eval/RUN_REPORT.md @@ -0,0 +1,10 @@ +# Cosmos3-Super Forward-Dynamics LoRA Evaluation + +- Run id: `xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp` +- Status: `complete` +- Split: `test` +- Eval samples: `448` +- Mean loss: `3.6853174321087345` +- Adapter dir: `/home/cy/Ropedia/ropedia-episode-task-suite/results/omni_finetune/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608/adapter_lora` + +The metric is rectified-flow vision velocity MSE under camera-pose action conditioning. It does not evaluate semantic JSON action labels. diff --git a/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/eval/loss_records.jsonl b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/eval/loss_records.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a46dfd085a5fa0711d9ef60617c3d17e204900bc --- /dev/null +++ b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/eval/loss_records.jsonl @@ -0,0 +1,448 @@ +{"index": 0, "loss": 5.744529724121094, "loss_scale": 10.0, "loss_surface": "vision_velocity_conditioned_on_camera_pose", "num_train_timesteps": 1000, "run_id": 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b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/validation/eval.json new file mode 100644 index 0000000000000000000000000000000000000000..ef786a1045f106e583632e8f8d53010f6949088a --- /dev/null +++ b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/validation/eval.json @@ -0,0 +1,18 @@ +{ + "checks": { + "adapter_parameter_numel": 26214400, + "adapter_tensors_repaired": true, + "public_package_excludes_weights": true, + "test_eval_complete": true, + "training_complete": true, + "val_eval_complete": true + }, + "status": "pass", + "summary": { + "held_out_episode_count": 14, + "test_eval_samples": 448, + "test_forward_dynamics_mse": 3.6853174321087345, + "train_final_loss": 1.0785235166549683, + "val_forward_dynamics_mse": 4.008244896889664 + } +} diff --git a/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/verified_result_summary.json b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/verified_result_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..4b710b1240602939cf1b057ca82f44e34572da36 --- /dev/null +++ b/results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/verified_result_summary.json @@ -0,0 +1,124 @@ +{ + "backbone": "cosmos3_super_forward_dynamics", + "backbone_display_name": "Cosmos3-Super Forward-Dynamics LoRA", + "dataset": { + "action_target": { + "chunk_size": 8, + "domain_name": "camera_pose", + "raw_action_dim": 9, + "rows_augmented": 3808, + "target_kind": "slam_camera_pose_delta_proxy_v1" + }, + "num_episodes": 119, + "num_samples": 3808, + "skipped_episodes": 9, + "split_counts": { + "test": 448, + "train": 2848, + "val": 512 + } + }, + "dataset_contract": "xperience10m_camera_pose_forward_dynamics_v1", + "dataset_run_id": "xperience10m_cosmos3_camera_pose_targets_20260608", + "eval": { + "eval_split": "test", + "held_out_episode_count": 14, + "num_eval_episodes": 14, + "num_samples": 448, + "prediction_file": "loss_records.jsonl", + "prediction_rows": 448, + "primary_metrics": { + "adapter_parameter_numel": 26214400, + "held_out_episode_count": 14, + "test_forward_dynamics_mse": 3.6853174321087345, + "train_final_loss": 1.0785235166549683, + "val_forward_dynamics_mse": 4.008244896889664 + } + }, + "eval_run_id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp", + "excluded_policy": "Raw Xperience-10M media/annotations, base-model weights, LoRA adapter weights, checkpoints, and large archives are not included.", + "included_files": [ + "dataset/dataset_manifest.json", + "dataset/episode_manifest.json", + "dataset/target_manifest.json", + "eval/RUN_REPORT.md", + "eval/loss_records.jsonl", + "eval/metrics.json", + "eval/progress/progress_rank0.jsonl", + "eval/progress/progress_rank1.jsonl", + "eval/progress/progress_rank2.jsonl", + "eval/progress/progress_rank3.jsonl", + "eval/progress/progress_rank4.jsonl", + "eval/progress/progress_rank5.jsonl", + "eval/progress/progress_rank6.jsonl", + "eval/progress/progress_rank7.jsonl", + "eval/rank_metrics/rank_0_metrics.json", + "eval/rank_metrics/rank_1_metrics.json", + "eval/rank_metrics/rank_2_metrics.json", + "eval/rank_metrics/rank_3_metrics.json", + "eval/rank_metrics/rank_4_metrics.json", + "eval/rank_metrics/rank_5_metrics.json", + "eval/rank_metrics/rank_6_metrics.json", + "eval/rank_metrics/rank_7_metrics.json", + "eval/val_metrics.json", + "training/adapter_repair_audit.json", + "training/adapter_shape_check_raw_fsdp.json", + "training/progress.jsonl", + "training/training_metadata.json", + "validation/eval.json" + ], + "public_package_allowed": [ + "loss metrics", + "rank-level eval metrics", + "progress logs", + "run reports", + "episode and dataset manifests", + "adapter repair audit", + "validation summaries" + ], + "public_package_forbidden": [ + ".bin", + ".ckpt", + ".gz", + ".hdf5", + ".mov", + ".mp4", + ".pt", + ".pth", + ".rrd", + ".safetensors", + ".tar", + ".zip" + ], + "required_eval_files": [ + "metrics.json", + "RUN_REPORT.md", + "loss_records.jsonl" + ], + "status": "verified", + "train_run_id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608", + "training": { + "final_loss": 1.0785235166549683, + "history": [ + { + "epoch": 1, + "note": "FSDP 8-GPU LoRA over camera-pose-conditioned future vision velocity loss; adapter weights are excluded from this public package.", + "train_loss": 1.0785235166549683, + "val_loss": 4.008244896889664 + } + ], + "max_steps": 356, + "num_processes": 8, + "num_train_samples": 2848, + "num_val_samples": 512, + "trainable_params": 26214400 + }, + "training_objective": "camera_pose_conditioned_future_vision_velocity_lora", + "validation_summary": { + "held_out_episode_count": 14, + "test_eval_samples": 448, + "test_forward_dynamics_mse": 3.6853174321087345, + "train_final_loss": 1.0785235166549683, + "val_forward_dynamics_mse": 4.008244896889664 + } +} diff --git a/scripts/omni/build_omni_model_comparison.py b/scripts/omni/build_omni_model_comparison.py index bc83df5647f9250f19783af7f60a28ca265a12e9..5399b3d68308968f6c216b0d5c5f472456a5659c 100644 --- a/scripts/omni/build_omni_model_comparison.py +++ b/scripts/omni/build_omni_model_comparison.py @@ -221,7 +221,11 @@ def model_branch_summary() -> dict[str, Any]: branches = [model_branch_entry(payload) for payload in verified_summaries()] qwen = [item for item in branches if item.get("backbone") == "qwen3_omni_lora"] cosmos_nano = [item for item in branches if item.get("backbone") == "cosmos_world_model"] - cosmos_super = [item for item in branches if item.get("backbone") == "cosmos3_super_reasoner"] + cosmos_super = [ + item + for item in branches + if item.get("backbone") in {"cosmos3_super_reasoner", "cosmos3_super_forward_dynamics"} + ] return { "id": "v3_multi_episode_foundation_model_branches", "title": "128-Episode Foundation-Model Branches", @@ -240,14 +244,16 @@ def model_branch_summary() -> dict[str, Any]: "Qwen3-Omni LoRA", "Cosmos3-Nano future-window compatibility branch", "Cosmos3-Super Reasoner base-weight evaluation", + "Cosmos3-Super forward-dynamics LoRA", ], "branches": branches, "interpretation": ( "This layer contains the held-out foundation-model packages. Qwen3-Omni " "packages evaluate structured JSON task prediction; Cosmos3-Nano evaluates " "a future-window world-model compatibility adapter; Cosmos3-Super Reasoner " - "evaluates staged base weights through vLLM on the JSON task. Neither Cosmos " - "branch is a new fine-tuned weight release yet." + "evaluates staged base weights through vLLM on the JSON task; Cosmos3-Super " + "Forward-Dynamics LoRA is the first Super adapter branch and evaluates " + "camera-pose-conditioned future vision velocity loss." ), } @@ -448,6 +454,7 @@ def model_grouped_view(versions: list[dict[str, Any]]) -> list[dict[str, Any]]: qwen_branches = [branch for branch in branches if branch.get("backbone") == "qwen3_omni_lora"] cosmos_nano_branches = [branch for branch in branches if branch.get("backbone") == "cosmos_world_model"] cosmos_super_branches = [branch for branch in branches if branch.get("backbone") == "cosmos3_super_reasoner"] + cosmos_super_fd_branches = [branch for branch in branches if branch.get("backbone") == "cosmos3_super_forward_dynamics"] cosmos_super_readiness = cosmos3_super_readiness_entry() cosmos_super_action_contract = cosmos3_super_action_contract_entry() cosmos_super_packer = cosmos3_super_packer_entry() @@ -473,6 +480,9 @@ def model_grouped_view(versions: list[dict[str, Any]]) -> list[dict[str, Any]]: "evaluated through vLLM; create a separate repo only after new adapter or " "fine-tuned weights exist" ) + for branch in cosmos_super_fd_branches: + branch["is_current"] = True + branch["weights_repository"] = "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep" return [ { "id": "task_head_baselines", @@ -567,8 +577,33 @@ def model_grouped_view(versions: list[dict[str, Any]]) -> list[dict[str, Any]]: "Reasoner evaluation on the same JSON task as Qwen3. It uses staged base " "weights through vLLM, so it is a model-branch diagnostic, not a weight release. " "A camera-pose proxy forward-dynamics target export now passes the contract audit " - "and schema-only packer smoke; true Cosmos3-Super fine-tuning is still blocked " - "until a trainable multi-GPU/offload path produces adapter or fine-tuned weights." + "and schema-only packer smoke; the separate Forward-Dynamics LoRA group records " + "the trainable adapter run and loss-based held-out evaluation." + ), + }, + { + "id": "cosmos3_super_forward_dynamics", + "model_family": "Cosmos3-Super Forward-Dynamics LoRA", + "model_type": "PEFT LoRA over nv-community/Cosmos3-Super for camera-pose-conditioned future vision velocity", + "weight_repository": "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep", + "one_episode_runs": [ + { + "id": "cosmos3_super_forward_dynamics_overfit_smoke", + "title": "Cosmos3-Super Forward-Dynamics Overfit Smoke", + "scope": "small overfit smoke before 128-episode scale-up", + "status": "verified_smoke", + "source": "results/omni_finetune/xperience10m_cosmos3_super_forward_dynamics_lora_overfit_after_qwen_v4_20260608_fsdp8_attn256_gradfix_savefix2/", + "weights": "local repaired LoRA smoke adapter, not public packaged as final", + "interpretation": ( + "Validated the trainable adapter path, FSDP save repair, and Diffusers load before the full 128-episode run." + ), + } + ], + "multi_episode_128_runs": cosmos_super_fd_branches, + "comparison_note": ( + "This is the first verified Cosmos3-Super fine-tuned adapter branch. " + "Its metric is forward-dynamics MSE, so compare it to world-model loss " + "or future-prediction targets, not to Qwen JSON classification accuracy." ), }, ] @@ -592,7 +627,7 @@ def build_report() -> dict[str, Any]: "version_reading_notes": [ "Version 1 is the public-sample 12-task harness with minimal and neural heads.", "Version 2 is the selected 128-episode same-split simple/NN baseline alignment.", - "Version 3 is the verified model-branch layer: the current final Qwen3-Omni LoRA package is the JSON-task diagnostic result, Cosmos3-Nano is a future-window compatibility result, and Cosmos3-Super Reasoner is a base-weight JSON-task evaluation; Cosmos3-Super has a camera-pose forward-dynamics contract audit and schema-only packer smoke, but no new fine-tuned weight release.", + "Version 3 is the verified model-branch layer: the current final Qwen3-Omni LoRA package is the JSON-task diagnostic result, Cosmos3-Nano is a future-window compatibility result, Cosmos3-Super Reasoner is a base-weight JSON-task evaluation, and Cosmos3-Super Forward-Dynamics LoRA is the first Super fine-tuned adapter branch.", ], "versions": versions, "model_groups": model_groups, @@ -601,11 +636,11 @@ def build_report() -> dict[str, Any]: "Task-head baselines have both a one-episode public-sample run and a 128-episode same-split metadata/text run.", "Qwen3-Omni has a one-episode sensor-adapter smoke test and separate 128-episode LoRA diagnostic packages; the newest verified full-eval 128-episode adapter belongs in the Qwen LoRA model repo.", "Cosmos3-Nano has a 128-episode future-window compatibility package.", - "Cosmos3-Super has a 128-episode base-weight Reasoner evaluation on the JSON task plus a camera-pose forward-dynamics contract audit; create a separate Cosmos model repo only after a trainable multi-GPU/offload run produces real Cosmos adapter or fine-tuned weights.", + "Cosmos3-Super now has both a 128-episode base-weight Reasoner evaluation on the JSON task and a fine-tuned forward-dynamics LoRA branch over camera-pose proxy targets.", ], "pending": [ "Use the verified Qwen3 v4 4-epoch full-eval package as the current Qwen row; older Qwen package rows remain historical diagnostics for comparison.", - "Promote Cosmos3 from Nano compatibility, Super base-weight evaluation, and the camera-pose forward-dynamics contract to true fine-tuning only after a trainable Cosmos3-Super run produces new weights.", + "Verify the live Cosmos3-Super forward-dynamics adapter model repo after upload; the public-safe verified_public package still excludes safetensors by design.", ], } @@ -640,6 +675,10 @@ def entry_metric_text(entry: dict[str, Any]) -> str: "json_validity_rate", "action_macro_f1", "future_retrieval_mrr", + "test_forward_dynamics_mse", + "val_forward_dynamics_mse", + "train_final_loss", + "adapter_parameter_numel", "temporal_consistency", "transition_accuracy", "contact_accuracy", @@ -736,7 +775,19 @@ def markdown(report: dict[str, Any]) -> str: key_metrics = ", ".join( f"{key}={fmt_score(value)}" for key, value in metrics.items() - if key in {"json_validity_rate", "action_macro_f1", "future_retrieval_mrr", "temporal_consistency", "transition_accuracy", "contact_accuracy"} + if key + in { + "json_validity_rate", + "action_macro_f1", + "future_retrieval_mrr", + "test_forward_dynamics_mse", + "val_forward_dynamics_mse", + "train_final_loss", + "adapter_parameter_numel", + "temporal_consistency", + "transition_accuracy", + "contact_accuracy", + } ) counts = branch.get("counts", {}) lines.append( diff --git a/scripts/omni/prepare_cosmos3_super_lora_hf_package.py b/scripts/omni/prepare_cosmos3_super_lora_hf_package.py new file mode 100644 index 0000000000000000000000000000000000000000..c87440d811024eaf5cf34d5231966094574572de --- /dev/null +++ b/scripts/omni/prepare_cosmos3_super_lora_hf_package.py @@ -0,0 +1,234 @@ +#!/usr/bin/env python3 +"""Prepare a Hugging Face upload folder for the Cosmos3-Super LoRA adapter.""" + +from __future__ import annotations + +import argparse +import hashlib +import json +import shutil +from datetime import datetime, timezone +from pathlib import Path +from typing import Any + + +ROOT = Path(__file__).resolve().parents[2] +DEFAULT_TRAIN_RUN_ID = "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608" +DEFAULT_VAL_RUN_ID = f"{DEFAULT_TRAIN_RUN_ID}_eval_val_full_fsdp" +DEFAULT_EVAL_RUN_ID = f"{DEFAULT_TRAIN_RUN_ID}_eval_test_full_fsdp" +DEFAULT_VERIFIED_DIR = ROOT / "results/omni_finetune/verified_public" / DEFAULT_EVAL_RUN_ID +DEFAULT_ADAPTER_DIR = ROOT / "results/omni_finetune" / DEFAULT_TRAIN_RUN_ID / "adapter_lora" +DEFAULT_OUTPUT_DIR = ROOT.parent / "hf_publish/cosmos3_super_forward_dynamics_lora_128ep" + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--adapter-dir", type=Path, default=DEFAULT_ADAPTER_DIR) + parser.add_argument("--verified-dir", type=Path, default=DEFAULT_VERIFIED_DIR) + parser.add_argument("--output-dir", type=Path, default=DEFAULT_OUTPUT_DIR) + parser.add_argument("--base-model", default="nv-community/Cosmos3-Super") + parser.add_argument("--repo-id", default="cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep") + return parser.parse_args() + + +def load_json(path: Path) -> dict[str, Any]: + return json.loads(path.read_text(encoding="utf-8")) + + +def sha256(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as handle: + for chunk in iter(lambda: handle.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def copy_file(src: Path, dst: Path, package_root: Path) -> dict[str, Any]: + if not src.is_file(): + raise FileNotFoundError(src) + dst.parent.mkdir(parents=True, exist_ok=True) + shutil.copy2(src, dst) + return {"path": dst.relative_to(package_root).as_posix(), "bytes": dst.stat().st_size, "sha256": sha256(dst)} + + +def metric_table(metrics: dict[str, Any]) -> list[str]: + rows = [ + ("Test forward-dynamics MSE", metrics.get("test_forward_dynamics_mse")), + ("Validation forward-dynamics MSE", metrics.get("val_forward_dynamics_mse")), + ("Train final loss", metrics.get("train_final_loss")), + ("Adapter parameters", metrics.get("adapter_parameter_numel")), + ("Held-out test episodes", metrics.get("held_out_episode_count")), + ] + lines = ["| Metric | Value |", "|---|---:|"] + for name, value in rows: + if value is None: + continue + if isinstance(value, float): + rendered = f"{value:.4f}" + else: + rendered = str(value) + lines.append(f"| {name} | {rendered} |") + return lines + + +def render_readme(summary: dict[str, Any], base_model: str, repo_id: str) -> str: + dataset = summary.get("dataset", {}) + training = summary.get("training", {}) + eval_payload = summary.get("eval", {}) + metrics = eval_payload.get("primary_metrics", {}) + action_target = dataset.get("action_target", {}) + return "\n".join( + [ + "---", + f"base_model: {base_model}", + "library_name: safetensors", + "license: other", + "tags:", + "- cosmos3-super", + "- lora", + "- robotics", + "- embodied-ai", + "- world-model", + "- xperience-10m", + "datasets:", + "- ropedia-ai/xperience-10m", + "metrics:", + "- mean_squared_error", + "---", + "", + "# Ropedia Xperience-10M Cosmos3-Super Forward-Dynamics LoRA", + "", + "This repository contains the weight-bearing LoRA adapter tensor file for", + "the verified Cosmos3-Super forward-dynamics branch of the Ropedia", + "Xperience-10M 128-episode diagnostic work.", + "", + "This is a research adapter over a camera-pose proxy forward-dynamics", + "objective. It is not a JSON action classifier, not a robot policy, and", + "not a standalone Cosmos3-Super base model.", + "", + "## Run Identity", + "", + f"- Target repo: `{repo_id}`", + f"- Base model: `{base_model}`", + f"- Dataset run: `{summary.get('dataset_run_id')}`", + f"- Train run: `{summary.get('train_run_id')}`", + f"- Eval run: `{summary.get('eval_run_id')}`", + f"- Dataset contract: `{summary.get('dataset_contract')}`", + f"- Objective: `{summary.get('training_objective')}`", + "", + "## Data Scope", + "", + f"- Train rows: `{training.get('num_train_samples')}`", + f"- Validation rows: `{training.get('num_val_samples')}`", + f"- Held-out test rows: `{eval_payload.get('num_samples')}`", + f"- Held-out test episodes: `{eval_payload.get('held_out_episode_count')}`", + f"- Action target domain: `{action_target.get('domain_name')}`", + f"- Raw action dimension: `{action_target.get('raw_action_dim')}`", + f"- Action chunk size: `{action_target.get('chunk_size')}`", + f"- Target kind: `{action_target.get('target_kind')}`", + "", + "Raw Xperience-10M MP4/HDF5/RRD files and Cosmos3-Super base weights are", + "not included.", + "", + "## Metrics", + "", + *metric_table(metrics), + "", + "The metric is future-vision-velocity loss under camera-pose conditioning.", + "Compare it to world-model or forward-prediction branches, not to Qwen3", + "structured JSON accuracy.", + "", + "## Files", + "", + "- `pytorch_lora_weights.safetensors`: LoRA adapter tensor state dict.", + "- `training_metadata.json`: training run metadata.", + "- `adapter_repair_audit.json`: shape repair audit for the FSDP-saved LoRA tensors.", + "- `eval_metrics.json` and `val_metrics.json`: full held-out loss summaries.", + "- `verified_result_summary.json`: public-safe result summary without raw data.", + "- `package_audit.json`: verified public package audit.", + "- `target_manifest.json`: camera-pose target manifest.", + "", + "## Loading Note", + "", + "Use the repository scripts that produced the adapter, especially", + "`scripts/omni/train_cosmos3_super_forward_dynamics_lora.py` and", + "`scripts/omni/eval_cosmos3_super_forward_dynamics_lora.py`, to map these", + "LoRA tensors onto the staged `nv-community/Cosmos3-Super` runtime. The", + "tensor file is not a plug-and-play Diffusers pipeline by itself.", + "", + "## Related Project Links", + "", + "- Project website: https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/", + "- GitHub repository: https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite", + "- Artifact dataset: https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts", + "- Qwen3-Omni LoRA model repo: https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep", + "- Baseline model repo: https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines", + "- Official gated dataset: https://huggingface.co/datasets/ropedia-ai/xperience-10m", + "", + ] + ) + + +def main() -> int: + args = parse_args() + adapter_dir = args.adapter_dir.expanduser().resolve() + verified_dir = args.verified_dir.expanduser().resolve() + output_dir = args.output_dir.expanduser().resolve() + + summary_path = verified_dir / "verified_result_summary.json" + package_audit_path = verified_dir / "package_audit.json" + if not summary_path.is_file(): + raise SystemExit(f"Verified summary does not exist: {summary_path}") + summary = load_json(summary_path) + if summary.get("backbone") != "cosmos3_super_forward_dynamics": + raise SystemExit(f"Verified summary is not a Cosmos3-Super forward-dynamics package: {summary_path}") + + if output_dir.exists(): + shutil.rmtree(output_dir) + output_dir.mkdir(parents=True) + + copied = [] + copy_pairs = [ + (adapter_dir / "pytorch_lora_weights.safetensors", output_dir / "pytorch_lora_weights.safetensors"), + (adapter_dir / "adapter_repair_audit.json", output_dir / "adapter_repair_audit.json"), + (verified_dir / "training/training_metadata.json", output_dir / "training_metadata.json"), + (verified_dir / "eval/metrics.json", output_dir / "eval_metrics.json"), + (verified_dir / "eval/val_metrics.json", output_dir / "val_metrics.json"), + (verified_dir / "dataset/target_manifest.json", output_dir / "target_manifest.json"), + (summary_path, output_dir / "verified_result_summary.json"), + (package_audit_path, output_dir / "package_audit.json"), + ] + for src, dst in copy_pairs: + copied.append(copy_file(src, dst, output_dir)) + + readme_path = output_dir / "README.md" + readme_path.write_text(render_readme(summary, args.base_model, args.repo_id), encoding="utf-8") + copied.append({"path": "README.md", "bytes": readme_path.stat().st_size, "sha256": sha256(readme_path)}) + + manifest = { + "status": "ready", + "generated_at_utc": datetime.now(timezone.utc).isoformat(timespec="seconds"), + "repo_id": args.repo_id, + "base_model": args.base_model, + "adapter_source": "local verified Cosmos3-Super forward-dynamics LoRA training run", + "verified_package_source": "local verified_public Cosmos3-Super forward-dynamics package", + "dataset_run_id": summary.get("dataset_run_id"), + "train_run_id": summary.get("train_run_id"), + "eval_run_id": summary.get("eval_run_id"), + "files": copied, + "forbidden_files_excluded": [ + "raw Xperience-10M MP4/HDF5/RRD files", + "Cosmos3-Super base-model weights", + "full FSDP checkpoints", + "optimizer state", + ], + } + manifest_path = output_dir / "upload_manifest.json" + manifest_path.write_text(json.dumps(manifest, indent=2) + "\n", encoding="utf-8") + print(f"PASS: prepared {output_dir}") + print(f"Repo target: {args.repo_id}") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/omni/run_cosmos3_super_forward_dynamics_lora.sh b/scripts/omni/run_cosmos3_super_forward_dynamics_lora.sh index 47ae6eddc73c1423ffe3cce15b6126fb1ab41aa0..bebdf485bca5c72393089699c8ec91778e527e8e 100644 --- a/scripts/omni/run_cosmos3_super_forward_dynamics_lora.sh +++ b/scripts/omni/run_cosmos3_super_forward_dynamics_lora.sh @@ -13,6 +13,7 @@ SPLIT="${SPLIT:-train}" MAX_TRAIN_SAMPLES="${MAX_TRAIN_SAMPLES:-1}" MAX_STEPS="${MAX_STEPS:-10}" LEARNING_RATE="${LEARNING_RATE:-0.0001}" +NUM_PROCESSES="${NUM_PROCESSES:-1}" DEVICE_MAP="${DEVICE_MAP:-balanced}" DTYPE="${DTYPE:-bfloat16}" SEED="${SEED:-123}" @@ -20,9 +21,15 @@ TARGET_MODULES="${TARGET_MODULES:-}" TIMESTEP_SAMPLING="${TIMESTEP_SAMPLING:-uniform}" OVERRIDE_RESOLUTION_TIER="${OVERRIDE_RESOLUTION_TIER:-}" GRADIENT_CHECKPOINTING="${GRADIENT_CHECKPOINTING:-1}" +FSDP_TRANSFORMER_LAYER="${FSDP_TRANSFORMER_LAYER:-Cosmos3VLTextMoTDecoderLayer}" +FSDP_ACTIVATION_CHECKPOINTING="${FSDP_ACTIVATION_CHECKPOINTING:-true}" DRY_RUN="${DRY_RUN:-0}" -args=( +if [[ "$NUM_PROCESSES" != "1" && "$DEVICE_MAP" != "none" ]]; then + DEVICE_MAP="none" +fi + +train_args=( "$PROJECT_ROOT/scripts/omni/train_cosmos3_super_forward_dynamics_lora.py" --workspace "$PROJECT_ROOT" --dataset-jsonl "$DATASET_JSONL" @@ -40,20 +47,39 @@ args=( ) if [[ -n "$OVERRIDE_RESOLUTION_TIER" ]]; then - args+=(--override-resolution-tier "$OVERRIDE_RESOLUTION_TIER") + train_args+=(--override-resolution-tier "$OVERRIDE_RESOLUTION_TIER") fi if [[ -n "$TARGET_MODULES" ]]; then - args+=(--target-modules "$TARGET_MODULES") + train_args+=(--target-modules "$TARGET_MODULES") fi if [[ "$GRADIENT_CHECKPOINTING" == "0" ]]; then - args+=(--no-gradient-checkpointing) + train_args+=(--no-gradient-checkpointing) fi if [[ "$DRY_RUN" == "1" ]]; then - args+=(--dry-run) + train_args+=(--dry-run) +fi + +if [[ "$NUM_PROCESSES" == "1" ]]; then + cmd=("$VENV_PY" "${train_args[@]}") +else + cmd=( + "$VENV_PY" -m accelerate.commands.launch + --num_processes "$NUM_PROCESSES" + --mixed_precision bf16 + --use_fsdp + --fsdp_sharding_strategy FULL_SHARD + --fsdp_auto_wrap_policy TRANSFORMER_BASED_WRAP + --fsdp_transformer_layer_cls_to_wrap "$FSDP_TRANSFORMER_LAYER" + --fsdp_use_orig_params true + --fsdp_cpu_ram_efficient_loading true + --fsdp_sync_module_states true + --fsdp_activation_checkpointing "$FSDP_ACTIVATION_CHECKPOINTING" + "${train_args[@]}" + ) fi cd "$PROJECT_ROOT" -exec "$VENV_PY" "${args[@]}" +exec "${cmd[@]}" diff --git a/scripts/omni/train_cosmos3_super_forward_dynamics_lora.py b/scripts/omni/train_cosmos3_super_forward_dynamics_lora.py index eb5383a98af64be58025e910c618df16b0a80858..8a272426bd47b44e2633f0f1be455b04fac8acd4 100644 --- a/scripts/omni/train_cosmos3_super_forward_dynamics_lora.py +++ b/scripts/omni/train_cosmos3_super_forward_dynamics_lora.py @@ -14,6 +14,7 @@ import argparse import json import math import random +import shutil import time from pathlib import Path from typing import Any @@ -133,6 +134,20 @@ def select_rows(rows: list[dict[str, Any]], args: argparse.Namespace) -> list[di return candidates +def distributed_slice(samples: list[dict[str, Any]], process_index: int, num_processes: int) -> list[dict[str, Any]]: + if num_processes <= 1: + return list(samples) + shard = list(samples[process_index::num_processes]) + max_len = math.ceil(len(samples) / num_processes) + if not samples: + return [] + if not shard: + shard = [samples[process_index % len(samples)]] + while len(shard) < max_len: + shard.append(random.choice(shard)) + return shard + + def checkpoint_module_suffixes(model_dir: Path) -> set[str]: suffixes: set[str] = set() for index_path in ( @@ -163,6 +178,188 @@ def lora_targets(args: argparse.Namespace, inner: dict[str, Any], model_dir: Pat return fallback or modules or DEFAULT_COSMOS3_SUPER_LORA_TARGETS +def parameter_dtype_counts(module: Any) -> dict[str, int]: + counts: dict[str, int] = {} + for param in module.parameters(): + key = str(param.dtype).replace("torch.", "") + counts[key] = counts.get(key, 0) + param.numel() + return counts + + +def adapter_tensor_numel(adapter_dir: Path) -> int: + weight_path = adapter_dir / "pytorch_lora_weights.safetensors" + if not weight_path.exists(): + return -1 + from safetensors.torch import load_file + + state = load_file(str(weight_path), device="cpu") + return sum(tensor.numel() for tensor in state.values()) + + +def expected_lora_shape(transformer: Any, key: str, lora_rank: int) -> tuple[int, ...] | None: + marker = ".lora_" + if marker not in key: + return None + module_name, suffix = key.split(marker, 1) + candidates = [module_name] + parts = module_name.split(".") + if len(parts) >= 2 and parts[0] == "layers": + candidates.append(".".join([parts[0], parts[1], "_fsdp_wrapped_module", *parts[2:]])) + module = None + last_error: Exception | None = None + for candidate in candidates: + try: + module = transformer.get_submodule(candidate) + break + except AttributeError as exc: + last_error = exc + continue + try: + if module is None: + raise last_error or AttributeError(module_name) + except AttributeError: + try: + module = transformer + for part in module_name.split("."): + module = getattr(module, part) + except AttributeError: + return None + base = getattr(module, "base_layer", module) + in_features = getattr(base, "in_features", None) + out_features = getattr(base, "out_features", None) + if in_features is None or out_features is None: + return None + if suffix.startswith("lora_A."): + return (int(lora_rank), int(in_features)) + if suffix.startswith("lora_B."): + return (int(out_features), int(lora_rank)) + return None + + +def fallback_flat_lora_shape(key: str, tensor_numel: int, lora_rank: int) -> tuple[int, ...] | None: + if lora_rank <= 0 or tensor_numel % lora_rank: + return None + if ".lora_A." in key: + return (int(lora_rank), int(tensor_numel // lora_rank)) + if ".lora_B." in key: + return (int(tensor_numel // lora_rank), int(lora_rank)) + return None + + +def repair_lora_adapter_shapes(adapter_dir: Path, transformer: Any, lora_rank: int) -> dict[str, Any]: + weight_path = adapter_dir / "pytorch_lora_weights.safetensors" + from safetensors import safe_open + from safetensors.torch import load_file, save_file + + with safe_open(str(weight_path), framework="pt", device="cpu") as handle: + metadata = handle.metadata() + state = load_file(str(weight_path), device="cpu") + repaired: dict[str, Any] = {} + for key, tensor in list(state.items()): + expected_shape = expected_lora_shape(transformer, key, lora_rank) + if expected_shape is None and tensor.ndim == 1: + expected_shape = fallback_flat_lora_shape(key, tensor.numel(), lora_rank) + if expected_shape is None or tuple(tensor.shape) == expected_shape: + continue + if tensor.ndim == 1 and tensor.numel() == math.prod(expected_shape): + state[key] = tensor.reshape(expected_shape).contiguous() + repaired[key] = {"from": list(tensor.shape), "to": list(expected_shape)} + if repaired: + save_file(state, str(weight_path), metadata=metadata) + return {"adapter_file": str(weight_path), "tensor_numel": sum(t.numel() for t in state.values()), "repaired": repaired} + + +def json_safe(value: Any) -> Any: + if isinstance(value, set): + return sorted(value) + if isinstance(value, dict): + return {key: json_safe(item) for key, item in value.items()} + if isinstance(value, (list, tuple)): + return [json_safe(item) for item in value] + return value + + +def canonical_lora_key(name: str, adapter_name: str) -> str | None: + for marker in (".lora_A.", ".lora_B."): + if marker not in name: + continue + prefix, suffix = name.split(marker, 1) + prefix = prefix.replace("._fsdp_wrapped_module", "") + adapter_prefix = f"{adapter_name}." + if suffix.startswith(adapter_prefix): + suffix = suffix[len(adapter_prefix) :] + return f"{prefix}{marker}{suffix}" + return None + + +def distributed_save_lora_adapter(transformer: Any, adapter_dir: Path, adapter_name: str, lora_config: Any, lora_rank: int) -> dict[str, Any]: + import torch.distributed as dist + from safetensors.torch import save_file + + adapter_dir.mkdir(parents=True, exist_ok=True) + local_state: dict[str, Any] = {} + expected_shapes: dict[str, tuple[int, ...]] = {} + for name, param in transformer.named_parameters(): + key = canonical_lora_key(name, adapter_name) + if key is None or not param.requires_grad: + continue + expected_shape = expected_lora_shape(transformer, key, lora_rank) + if expected_shape is not None: + expected_shapes[key] = expected_shape + if param.numel() == 0: + continue + tensor = param.detach().cpu() + if expected_shape is not None and tensor.ndim == 1 and tensor.numel() == math.prod(expected_shape): + tensor = tensor.reshape(expected_shape) + local_state[key] = tensor.contiguous() + + if dist.is_available() and dist.is_initialized(): + gathered: list[dict[str, Any] | None] = [None for _ in range(dist.get_world_size())] + dist.all_gather_object(gathered, local_state) + rank = dist.get_rank() + else: + gathered = [local_state] + rank = 0 + + merged: dict[str, Any] = {} + duplicate_keys: list[str] = [] + for shard in gathered: + if not shard: + continue + for key, tensor in shard.items(): + if key in merged: + duplicate_keys.append(key) + expected_shape = expected_shapes.get(key) + if expected_shape is None and tensor.ndim == 1: + expected_shape = fallback_flat_lora_shape(key, tensor.numel(), lora_rank) + if expected_shape is not None: + expected_shapes[key] = expected_shape + if expected_shape is not None and tensor.ndim == 1 and tensor.numel() == math.prod(expected_shape): + tensor = tensor.reshape(expected_shape).contiguous() + merged[key] = tensor + + missing_keys = sorted(set(expected_shapes) - set(merged)) + adapter_file = adapter_dir / "pytorch_lora_weights.safetensors" + metadata = { + "format": "pt", + "lora_adapter_metadata": json.dumps(json_safe(lora_config.to_dict()), indent=2, sort_keys=True), + } + if rank == 0: + if missing_keys: + raise RuntimeError(f"missing gathered LoRA tensors: {missing_keys[:8]} ({len(missing_keys)} total)") + save_file(merged, str(adapter_file), metadata=metadata) + return { + "adapter_dir": str(adapter_dir), + "adapter_file": str(adapter_file), + "local_keys": sorted(local_state), + "merged_keys": sorted(merged), + "missing_keys": missing_keys, + "duplicate_keys": sorted(duplicate_keys), + "tensor_numel": sum(tensor.numel() for tensor in merged.values()), + "tensor_shapes": {key: list(tensor.shape) for key, tensor in merged.items()}, + } + + def instantiate_action(row: dict[str, Any], resolution_tier: int | None): import torch from diffusers.pipelines.cosmos.pipeline_cosmos3_omni import CosmosActionCondition @@ -264,7 +461,13 @@ def action_latents(action: Any, pipe: Any, device: str, dtype: Any): raw = torch.cat([raw, raw[-1:].expand(action_chunk_size - raw.shape[0], -1)], dim=0) raw = raw[:action_chunk_size] raw_action_dim = int(raw.shape[-1]) - action_dim = int(pipe.transformer.action_dim) + transformer = pipe.transformer + action_dim = getattr(transformer, "action_dim", None) + if action_dim is None and hasattr(transformer, "module"): + action_dim = getattr(transformer.module, "action_dim", None) + if action_dim is None: + raise ValueError("Cosmos3 transformer does not expose action_dim") + action_dim = int(action_dim) if raw_action_dim > action_dim: raise ValueError(f"raw action dim {raw_action_dim} exceeds model action_dim {action_dim}") if raw_action_dim < action_dim: @@ -334,7 +537,16 @@ def pack_static(pipe: Any, input_ids: list[int], latents: Any, action_tokens: An } -def training_step(pipe: Any, row: dict[str, Any], args: argparse.Namespace, device: str, dtype: Any, num_train_timesteps: int, sigma_shift: float): +def training_step( + pipe: Any, + row: dict[str, Any], + args: argparse.Namespace, + device: str, + dtype: Any, + num_train_timesteps: int, + sigma_shift: float, + grad_enabled: bool = True, +): import torch contract = row_contract(row, require_media_exists=args.require_media_exists) @@ -366,40 +578,42 @@ def training_step(pipe: Any, row: dict[str, Any], args: argparse.Namespace, devi vision_timesteps = torch.full((packed["num_noisy_vision_tokens"],), timestep, device=device) action_timesteps = torch.full((packed["num_noisy_action_tokens"],), timestep, device=device) - preds_vision, preds_sound, preds_action = pipe.transformer( - input_ids=packed["input_ids"], - text_indexes=packed["text_indexes"], - position_ids=packed["position_ids"], - und_len=packed["und_len"], - sequence_length=packed["sequence_length"], - vision_tokens=[latents.to(device=device, dtype=dtype)], - vision_token_shapes=packed["vision_token_shapes"], - vision_sequence_indexes=packed["vision_sequence_indexes"], - vision_mse_loss_indexes=packed["vision_mse_loss_indexes"], - vision_timesteps=vision_timesteps, - vision_noisy_frame_indexes=packed["vision_noisy_frame_indexes"], - action_tokens=[act_tokens.to(device=device, dtype=dtype)], - action_token_shapes=packed["action_token_shapes"], - action_sequence_indexes=packed["action_sequence_indexes"], - action_mse_loss_indexes=packed["action_mse_loss_indexes"], - action_timesteps=action_timesteps, - action_noisy_frame_indexes=packed["action_noisy_frame_indexes"], - action_domain_ids=[action_domain_id(action.domain_name, device)], - ) - pred_velocity, _pred_sound, _pred_action = pipe._mask_velocity_predictions( - preds_vision, - preds_sound, - vision_condition_mask=[vision_condition_mask.to(dtype=preds_vision[0].dtype)], - preds_action=preds_action, - action_condition_mask=[act_mask], - raw_action_dim=raw_action_dim, - ) - target = velocity_target.to(device=pred_velocity.device, dtype=pred_velocity.dtype) - mask = loss_mask.to(device=pred_velocity.device, dtype=pred_velocity.dtype) - denom = mask.expand_as(pred_velocity).sum() - loss = ((pred_velocity - target) ** 2 * mask).sum() / denom.clamp_min(1.0) - if args.loss_scale: - loss = loss * args.loss_scale + grad_context = torch.enable_grad() if grad_enabled else torch.no_grad() + with grad_context: + preds_vision, preds_sound, preds_action = pipe.transformer( + input_ids=packed["input_ids"], + text_indexes=packed["text_indexes"], + position_ids=packed["position_ids"], + und_len=packed["und_len"], + sequence_length=packed["sequence_length"], + vision_tokens=[latents.to(device=device, dtype=dtype)], + vision_token_shapes=packed["vision_token_shapes"], + vision_sequence_indexes=packed["vision_sequence_indexes"], + vision_mse_loss_indexes=packed["vision_mse_loss_indexes"], + vision_timesteps=vision_timesteps, + vision_noisy_frame_indexes=packed["vision_noisy_frame_indexes"], + action_tokens=[act_tokens.to(device=device, dtype=dtype)], + action_token_shapes=packed["action_token_shapes"], + action_sequence_indexes=packed["action_sequence_indexes"], + action_mse_loss_indexes=packed["action_mse_loss_indexes"], + action_timesteps=action_timesteps, + action_noisy_frame_indexes=packed["action_noisy_frame_indexes"], + action_domain_ids=[action_domain_id(action.domain_name, device)], + ) + pred_velocity, _pred_sound, _pred_action = pipe._mask_velocity_predictions( + preds_vision, + preds_sound, + vision_condition_mask=[vision_condition_mask.to(dtype=preds_vision[0].dtype)], + preds_action=preds_action, + action_condition_mask=[act_mask], + raw_action_dim=raw_action_dim, + ) + target = velocity_target.to(device=pred_velocity.device, dtype=pred_velocity.dtype) + mask = loss_mask.to(device=pred_velocity.device, dtype=pred_velocity.dtype) + denom = mask.expand_as(pred_velocity).sum() + loss = ((pred_velocity - target) ** 2 * mask).sum() / denom.clamp_min(1.0) + if args.loss_scale: + loss = loss * args.loss_scale return loss, { "row_id": contract["row_id"], "episode_id": contract["episode_id"], @@ -443,21 +657,27 @@ def write_report(output_dir: Path, payload: dict[str, Any]) -> None: def main() -> int: args = parse_args() + from accelerate import Accelerator + + accelerator = Accelerator() args.workspace = args.workspace.expanduser().resolve() args.dataset_jsonl = args.dataset_jsonl.expanduser().resolve() args.model_dir = args.model_dir.expanduser().resolve() output_dir = args.output_dir or args.workspace / "results" / "omni_finetune" / args.run_id output_dir = output_dir.expanduser().resolve() progress_path = output_dir / "progress.jsonl" - if progress_path.exists(): + if accelerator.is_main_process and progress_path.exists(): progress_path.unlink() + accelerator.wait_for_everyone() - random.seed(args.seed) + random.seed(args.seed + accelerator.process_index) started = time.time() - append_jsonl(progress_path, {"event": "start", "run_id": args.run_id, "timestamp": started}) + if accelerator.is_main_process: + append_jsonl(progress_path, {"event": "start", "run_id": args.run_id, "timestamp": started}) inner = model_inner_config(args.model_dir) - train_rows = select_rows(load_jsonl(args.dataset_jsonl), args) + all_train_rows = select_rows(load_jsonl(args.dataset_jsonl), args) + train_rows = distributed_slice(all_train_rows, accelerator.process_index, accelerator.num_processes) target_modules = lora_targets(args, inner, args.model_dir) lora_rank = int(args.lora_rank or inner.get("lora_rank") or 16) lora_alpha = int(args.lora_alpha or inner.get("lora_alpha") or 32) @@ -469,34 +689,46 @@ def main() -> int: loss_scale = args.loss_scale if args.loss_scale is not None else train_cfg.get("loss_scale") args.loss_scale = float(loss_scale) if loss_scale is not None else None - append_jsonl( - progress_path, - { - "event": "dataset_ready", - "timestamp": time.time(), - "train_samples": len(train_rows), - "target_modules": target_modules, - "lora_rank": lora_rank, - "lora_alpha": lora_alpha, - "sigma_shift": sigma_shift, - "loss_scale": args.loss_scale, - }, - ) + if accelerator.is_main_process: + append_jsonl( + progress_path, + { + "event": "dataset_ready", + "timestamp": time.time(), + "num_processes": accelerator.num_processes, + "train_samples": len(all_train_rows), + "rank0_samples": len(train_rows), + "target_modules": target_modules, + "lora_rank": lora_rank, + "lora_alpha": lora_alpha, + "sigma_shift": sigma_shift, + "loss_scale": args.loss_scale, + }, + ) import torch from diffusers import Cosmos3OmniPipeline from peft import LoraConfig + torch.set_grad_enabled(True) dtype = dtype_from_name(args.dtype) load_kwargs: dict[str, Any] = { "torch_dtype": dtype, "local_files_only": args.local_files_only, "enable_safety_checker": False, } + if accelerator.num_processes > 1 and args.device_map != "none": + args.device_map = "none" if args.device_map != "none": load_kwargs["device_map"] = args.device_map pipe = Cosmos3OmniPipeline.from_pretrained(str(args.model_dir), **load_kwargs) - if args.device_map == "none": + if accelerator.num_processes > 1: + device = accelerator.device + for component_name in ("vae", "sound_tokenizer"): + component = getattr(pipe, component_name, None) + if component is not None: + component.to(device) + elif args.device_map == "none": pipe.to(args.device) device = args.device else: @@ -516,7 +748,12 @@ def main() -> int: ) pipe.transformer.add_adapter(lora_config, adapter_name=args.adapter_name) pipe.transformer.set_adapter(args.adapter_name) + if args.device_map == "none": + pipe.transformer.to(dtype=dtype) pipe.transformer.train() + for param in pipe.transformer.parameters(): + if param.requires_grad and param.dtype != dtype: + param.data = param.data.to(dtype=dtype) for component_name in ("vae", "sound_tokenizer"): component = getattr(pipe, component_name, None) if component is not None: @@ -525,11 +762,28 @@ def main() -> int: trainable = [param for param in pipe.transformer.parameters() if param.requires_grad] trainable_params = sum(param.numel() for param in trainable) - append_jsonl(progress_path, {"event": "model_ready", "timestamp": time.time(), "device": device, "trainable_params": trainable_params}) + if accelerator.is_main_process: + append_jsonl( + progress_path, + { + "event": "model_ready", + "timestamp": time.time(), + "device": str(device), + "device_map": args.device_map, + "trainable_params": trainable_params, + "parameter_dtype_counts": parameter_dtype_counts(pipe.transformer), + }, + ) if not trainable: raise RuntimeError("no trainable LoRA parameters found") optimizer = torch.optim.AdamW(trainable, lr=args.learning_rate, weight_decay=args.weight_decay) + if accelerator.num_processes > 1: + if accelerator.is_main_process: + append_jsonl(progress_path, {"event": "accelerator_prepare_start", "timestamp": time.time()}) + pipe.transformer, optimizer = accelerator.prepare(pipe.transformer, optimizer) + if accelerator.is_main_process: + append_jsonl(progress_path, {"event": "accelerator_prepare_done", "timestamp": time.time()}) losses: list[float] = [] status = "dry_run_complete" if args.dry_run else "complete" adapter_dir: Path | None = None @@ -541,25 +795,58 @@ def main() -> int: loss_value = float(loss.detach().float().cpu()) losses.append(loss_value) if not args.dry_run: - loss.backward() + if accelerator.num_processes > 1: + accelerator.backward(loss) + else: + loss.backward() optimizer.step() if step == 1 or step % args.progress_every == 0 or step == args.max_steps: - append_jsonl( - progress_path, - { - "event": "train_step", - "timestamp": time.time(), - "step": step, - "loss": loss_value, - **info, - }, - ) + if accelerator.is_main_process: + append_jsonl( + progress_path, + { + "event": "train_step", + "timestamp": time.time(), + "step": step, + "rank0_loss": loss_value, + **info, + }, + ) if not args.dry_run: - adapter_dir = save_adapter(pipe, output_dir, args.adapter_name) - append_jsonl(progress_path, {"event": "adapter_saved", "timestamp": time.time(), "adapter_dir": str(adapter_dir)}) + if accelerator.is_main_process: + append_jsonl(progress_path, {"event": "save_start", "timestamp": time.time()}) + accelerator.wait_for_everyone() + if accelerator.num_processes > 1: + pipe.transformer = accelerator.unwrap_model(pipe.transformer) + adapter_dir = output_dir / "adapter_lora" + adapter_audit = distributed_save_lora_adapter( + pipe.transformer, + adapter_dir, + args.adapter_name, + lora_config, + lora_rank, + ) + accelerator.wait_for_everyone() + if accelerator.is_main_process: + append_jsonl( + progress_path, + { + "event": "adapter_saved", + "timestamp": time.time(), + "adapter_dir": str(adapter_dir), + "adapter_audit": adapter_audit, + }, + ) + write_json(output_dir / "adapter_shape_check.json", adapter_audit) + else: + adapter_dir = save_adapter(pipe, output_dir, args.adapter_name) + if accelerator.is_main_process: + append_jsonl(progress_path, {"event": "adapter_saved", "timestamp": time.time(), "adapter_dir": str(adapter_dir)}) + accelerator.wait_for_everyone() except Exception as exc: status = "failed" - append_jsonl(progress_path, {"event": "failed", "timestamp": time.time(), "error": repr(exc)}) + if accelerator.is_main_process: + append_jsonl(progress_path, {"event": "failed", "timestamp": time.time(), "error": repr(exc)}) raise finally: finished = time.time() @@ -575,7 +862,9 @@ def main() -> int: "model_dir": str(args.model_dir), "split": args.split, "episode_id": args.episode_id, - "train_samples": len(train_rows), + "num_processes": accelerator.num_processes, + "train_samples": len(all_train_rows), + "rank_samples": len(train_rows), "max_steps": args.max_steps, "learning_rate": args.learning_rate, "target_modules": target_modules, @@ -592,11 +881,13 @@ def main() -> int: "loss_surface": "vision_velocity_conditioned_on_camera_pose", "action_loss_expected": False, } - write_json(output_dir / "training_metadata.json", payload) - write_report(output_dir, payload) - append_jsonl(progress_path, {"event": "complete", "timestamp": time.time(), "status": status}) + if accelerator.is_main_process: + write_json(output_dir / "training_metadata.json", payload) + write_report(output_dir, payload) + append_jsonl(progress_path, {"event": "complete", "timestamp": time.time(), "status": status}) - print(json.dumps({"status": status, "output_dir": str(output_dir), "adapter_dir": str(adapter_dir) if adapter_dir else None}, indent=2)) + if accelerator.is_main_process: + print(json.dumps({"status": status, "output_dir": str(output_dir), "adapter_dir": str(adapter_dir) if adapter_dir else None}, indent=2)) return 0 diff --git a/scripts/validate_mirror_parity.py b/scripts/validate_mirror_parity.py index 7a668cb13306589982dec6793250b551a3508cb9..4a3096c65c5ccf68412c98e696e48189f60bad24 100644 --- a/scripts/validate_mirror_parity.py +++ b/scripts/validate_mirror_parity.py @@ -85,6 +85,7 @@ SCRIPT_FILES = [ "omni/defer_cosmos3_super_after_qwen_v4.sh", "omni/export_cosmos3_camera_pose_targets.py", "omni/pack_cosmos3_super_action_batch.py", + "omni/prepare_cosmos3_super_lora_hf_package.py", "omni/prepare_qwen3_lora_hf_package.py", "omni/probe_cosmos3_super_training_readiness.py", "omni/run_128_task_baselines.py", diff --git a/scripts/verify_live_publication.py b/scripts/verify_live_publication.py index 909b50299d2b8b1c40ec58d61e97e1aebdf27ee3..b44aebc8785907320607f071e27c7acc371bc5dc 100644 --- a/scripts/verify_live_publication.py +++ b/scripts/verify_live_publication.py @@ -30,6 +30,10 @@ QWEN3_LORA_UPLOAD_DIR_CANDIDATES = [ ROOT.parent / "hf_publish/qwen3_lora_128ep", ROOT / "results/omni_finetune/hf_upload_qwen3_128ep_full", ] +COSMOS3_SUPER_LORA_REPO_ID = "cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep" +COSMOS3_SUPER_LORA_UPLOAD_DIR_CANDIDATES = [ + ROOT.parent / "hf_publish/cosmos3_super_forward_dynamics_lora_128ep", +] HASH_GROUPS = [ @@ -311,7 +315,8 @@ MARKER_CHECKS = [ "100.00%", "omni_model_comparison.json", "ropedia-qwen3-omni-lora-128ep", - "Cosmos3-Super has a verified base-weight JSON-task evaluation plus a camera-pose forward-dynamics contract audit", + "ropedia-cosmos3-super-forward-dynamics-lora-128ep", + "Cosmos3-Super has a verified base-weight JSON-task evaluation plus a fine-tuned forward-dynamics LoRA branch", ], "forbidden": [ "xperience10m-" + "taskfirst-v10", @@ -340,7 +345,8 @@ MARKER_CHECKS = [ "100.00%", "omni_model_comparison.json", "ropedia-qwen3-omni-lora-128ep", - "Cosmos3-Super has a verified base-weight JSON-task evaluation plus a camera-pose forward-dynamics contract audit", + "ropedia-cosmos3-super-forward-dynamics-lora-128ep", + "Cosmos3-Super has a verified base-weight JSON-task evaluation plus a fine-tuned forward-dynamics LoRA branch", ], "forbidden": [ "xperience10m-" + "taskfirst-v10", @@ -358,6 +364,7 @@ MARKER_CHECKS = [ "100.00% JSON validity", "Cosmos3-Super", "ropedia-qwen3-omni-lora-128ep", + "ropedia-cosmos3-super-forward-dynamics-lora-128ep", ], "forbidden": ["xperience10m-" + "taskfirst-v10"], }, @@ -405,6 +412,7 @@ MARKER_CHECKS = [ "100.00%", "Cosmos3-Super", "ropedia-qwen3-omni-lora-128ep", + "ropedia-cosmos3-super-forward-dynamics-lora-128ep", ], "forbidden": ["xperience10m-" + "taskfirst-v10"], }, @@ -471,6 +479,13 @@ def qwen3_lora_upload_dir() -> Path | None: return None +def cosmos3_super_lora_upload_dir() -> Path | None: + for path in COSMOS3_SUPER_LORA_UPLOAD_DIR_CANDIDATES: + if path.exists(): + return path + return None + + def display_local_path(path: Path) -> str: resolved = path.resolve() for base, prefix in ((ROOT, ""), (ROOT.parent, "../")): @@ -512,6 +527,39 @@ def qwen3_lora_hash_groups() -> list[dict]: return groups +def cosmos3_super_lora_hash_groups() -> list[dict]: + upload_dir = cosmos3_super_lora_upload_dir() + if upload_dir is None: + return [] + groups = [] + required_files = [ + "README.md", + "upload_manifest.json", + "pytorch_lora_weights.safetensors", + "verified_result_summary.json", + "package_audit.json", + "eval_metrics.json", + "val_metrics.json", + ] + for filename in required_files: + path = upload_dir / filename + if not path.exists(): + continue + groups.append( + { + "id": f"cosmos3_super_lora_{filename.replace('.', '_').replace('-', '_')}", + "title": f"Cosmos3-Super LoRA repo file: {filename}", + "local_path": display_local_path(path), + "urls": { + "hf_cosmos3_super_lora_model": ( + f"https://huggingface.co/{COSMOS3_SUPER_LORA_REPO_ID}/resolve/main/{filename}" + ), + }, + } + ) + return groups + + def sha256_bytes(data: bytes) -> str: return hashlib.sha256(data).hexdigest() @@ -695,7 +743,10 @@ def marker_record(check: dict) -> dict: def build_report() -> dict: - hash_records = [hash_group_record(group) for group in [*HASH_GROUPS, *qwen3_lora_hash_groups()]] + hash_records = [ + hash_group_record(group) + for group in [*HASH_GROUPS, *qwen3_lora_hash_groups(), *cosmos3_super_lora_hash_groups()] + ] marker_records = [marker_record(check) for check in [*MARKER_CHECKS, *local_path_checks()]] failures = [ {"check": record["id"], **failure} @@ -708,8 +759,8 @@ def build_report() -> dict: "checked_at_utc": datetime.now(timezone.utc).isoformat(timespec="seconds"), "scope": ( "Live GitHub Pages, GitHub raw, Hugging Face Space, artifact dataset, " - "baseline model mirrors, and the Qwen3 LoRA adapter repo when the final " - "upload package exists locally." + "baseline model mirrors, and the Qwen3/Cosmos3 LoRA adapter repos when " + "their upload packages exist locally." ), "hash_groups": hash_records, "marker_checks": marker_records,