File size: 2,515 Bytes
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"camera_protocol": "linear_v1",
"code_commit": "9b307a6ed79af17a54105a457171bd1675e38529",
"data_profile": "iid",
"dataset_metadata": {
"config": {
"camera_generator_version": "strict_camera_v1",
"camera_protocol": "linear_v1",
"frames": 24,
"groups": 8192,
"groups_per_base_family": 8,
"height": 128,
"mujoco_gl": "egl",
"profile": "iid",
"seed": 2026090801,
"split_groups": {
"test": 1536,
"train": 5120,
"val": 1536
},
"state_protocol": "coverage_v1",
"substeps": 8,
"width": 128
},
"generator": "tools/intervenceact/build_strict_anchor.py",
"manifest_sha256": "6592ec0067420036c40f521085c1f5d390c7abac1f12a5aee302fa88d6e5378a",
"next_stage": "Run frozen ALAM RGB extraction and convert to intervenceact.counterfactual_manifest.v1; raw RGB records are not accepted directly by StrictQuartetDataset.",
"oracle_report_sha256": "78167acfc9927b53fd149ea7b1c3816e99066a01173a4ee78623aa85ca89d782",
"oracle_schema_version": "interveneact.raw_strict_anchor_oracle.v1",
"output_dir": "/mnt/workspace/tangzuojin.tzj/interveneact_eval_artifacts/b12_scale8192_20260908_v1/data",
"raw_manifest_schema_version": "interveneact.raw_strict_anchor.v1",
"schema_version": "interveneact.raw_strict_anchor_dataset.v1",
"status": "passed"
},
"egl_runtime": {
"driver_dirs": [
"/usr/lib/x86_64-linux-gnu"
],
"nvidia_egl_libraries": [
"/usr/lib/x86_64-linux-gnu/libEGL_nvidia.so.0",
"/usr/lib/x86_64-linux-gnu/libEGL_nvidia.so.580.105.08"
],
"selected_library": "/usr/lib/x86_64-linux-gnu/libEGL_nvidia.so.580.105.08",
"vendor_file": "/tmp/b12-scale-egl-3ppk6aq_/egl_vendor.d/10_nvidia.json"
},
"labels_used_as_model_input": false,
"oracle_report_sha256": "78167acfc9927b53fd149ea7b1c3816e99066a01173a4ee78623aa85ca89d782",
"raw_manifest_sha256": "6592ec0067420036c40f521085c1f5d390c7abac1f12a5aee302fa88d6e5378a",
"runtime": {
"execution_backend": "local_training_data_generation",
"gpu_ids": [
0,
1,
2,
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],
"mujoco_version": "3.3.7",
"render_reproducibility": "Cross-context uint8 RGB rounding may differ by one level; physics and labels unchanged in 64-group regression.",
"reuse_family_renderer": true,
"workers_per_gpu": 16
},
"schema_version": "interveneact.strict_anchor_aihub_entry.v1",
"status": "complete",
"strict_camera_counterfactual": true
}
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