Datasets:
File size: 1,372 Bytes
84a242a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"scope": "deterministic integrity comparison of existing data; no AL, docking, model training, or cache replacement",
"cache_sha256": "10b4a50f5cfc3de000ab06d0b8112146486e63571ad9db252455dd5af3976a91",
"raw_id_index_sha256": "7e265af1318119a7c8e2086fbf4bc2786143d825b68479e6bd83ede46e4bf294",
"ligand_sha256": "ad74c18a2560f0c4577a045c22582ce37a1d1827ec05bce48bd1cd1111c54b0c",
"producer_reference": "dal_toolbox_design2/run_dal_toolbox_design2.py functions normalize_features, random_project, load_ligand_features, pooled_graph_feature, build_complex_features",
"shape": [
3179,
256
],
"numpy_version": "2.3.5",
"projection_seed": 0,
"absolute_tolerance": 2e-05,
"relative_tolerance": 2e-05,
"maximum_absolute_difference": 2.193450927734375e-05,
"root_mean_square_difference": 2.3208026557708418e-06,
"matching_values": 813824,
"total_values": 813824,
"matching_rows": 3179,
"total_rows": 3179,
"bitwise_numeric_equal": false,
"passed": true,
"note": "NumPy float32 node pooling can differ in rounding from original PyTorch pooling; all comparisons are explicitly quantified.",
"elapsed_seconds": 8.6,
"packaged_producer_excerpt": "provenance/historical_acquisition_source/feature_builder_excerpt.py.txt",
"packaged_producer_provenance": "provenance/historical_acquisition_source/feature_builder_provenance.json"
}
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