Seal Phase 4AN exact continuation engineering evidence
This commit is contained in:
Digital Drosophila Archive
+45
@@ -0,0 +1,45 @@
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{
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"array_sha256": {
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"apl_globals.npy": "979ef88dff30d41168ce9b377a006ccb3cd034b2dce86d54923ca0f4b87cb6a6",
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"input_matrix.npy": "528a5f6f5ffe424f323c5a44695db4a7cf32570709832eff2f37f49e85c92c3e",
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"kc_globals.npy": "9e990d10a63b0f74cd7bbbdc5369082f24d5246487af944ba289bc6bf48d4b75",
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"output_matrix.npy": "0dcf02cdb7836ab72da32ac47f5682ca33e25f63a8a662a8452d4ea9d46babb9"
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},
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"decay_f32_bits": "3f7eb923",
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"dt_ms": 0.1,
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"environment": {
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"CUBLAS_WORKSPACE_CONFIG": null,
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"cuda": "13.0",
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"cuda_matmul_allow_tf32": false,
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"cudnn": 92400,
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"cudnn_allow_tf32": true,
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"cudnn_benchmark": false,
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"cudnn_deterministic": false,
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"deterministic_algorithms": false,
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"device_capability": [
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8,
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9
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],
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"device_index": 0,
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"device_name": "NVIDIA GeForce RTX 4090",
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"float32_matmul_precision": "highest",
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"numpy": "2.2.6",
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"precision_configuration_changed_by_component": false,
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"torch": "2.14.0+cu130"
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},
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"files_sha256": {
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"apl_globals.npy": "8388c8795d49cfe5b14fda54f76ef3a35030c62ba87bd8ca6334a2dcdf186f19",
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"input_matrix.npy": "c4d3df703ea5f1d7402b8255cfa19d9744139ad1048827c23b151d8ba766fec6",
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"kc_globals.npy": "97a570aafa089f93e642b2bb07e3a3322dabb14c3c7dd431f0c8d2b3b7951fdd",
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"output_matrix.npy": "e2d0a1ccd740e6777245ebf2efcd88bf5e1da9e47308c63ec8e83d451e134a73"
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},
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"gain_f32_bits": "3c23d70a",
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"h_units": "legacy mV",
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"initial_state": "float32 zeros",
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"n_apl": 2,
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"n_kc": 4064,
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"n_neurons": 166700,
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"ok": true,
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"operator_sequence": "state.mul_(decay32); drive=mv(I32,spikes32); state.add_(drive); h=matmul(state,O32)*gain32",
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"protocol": "phase4ag-apl-v1"
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}
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+37
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{
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"apl_delay_steps": 18,
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"applied_generated_rows": 0,
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"applied_trace": null,
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"biological_delay_measurement_claimed": false,
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"brain_tail_advanced": false,
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"closed_loop_branch_integrals_claimed_equal": false,
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"final_apl_state_float32": [
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0.0,
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0.0
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],
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"final_apl_state_nonzero": false,
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"final_apl_state_u32_bits": [
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0,
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0
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],
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"finite_generated_sequence_only": true,
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"full_sequence_bitwise_audit_performed": false,
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"future_apl_decay_or_feedback_generated": false,
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"generated_rows": 5,
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"generated_trace": null,
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"pending_application_tick_start": 5,
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"pending_application_tick_stop_exclusive": 23,
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"pending_generated_count": 5,
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"pending_generated_tick_start": 0,
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"pending_generated_tick_stop_exclusive": 5,
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"pending_initial_zero_prefix": 13,
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"pending_queue_drained": false,
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"pending_raw_sha256": "81cc5530fab22979a78429b863d208e62d9249ddff3a0a06de0edbda0c688aaf",
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"pending_shape": [
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18,
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4064
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],
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"pending_trace": "apl-pending-tail.float32.npy",
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"scope": "Original D18 ring AST retained; generated/applied histories not recorded",
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"steps": 5
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}
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+26
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{
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"complete": true,
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"counts_scope": "segment_only",
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"files_sha256": {
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"apl-component.json": "7a49a1a8fbe42b3965913b8e483ef729ba1f13c211f8da7f10b4b2cd142e6882",
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"apl-pending-tail.float32.npy": "f4c6097555e9bca1551d23df2751afd3d8ae6914559233707de894b51c9dd200",
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"apl-timing-audit.json": "e683ba6046e405c6787e6861cfff6b2d5df8b38be7684351810dc2bb8fb65b76",
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"finite-audit.json": "4d5ecd025cf500818de9c269269596c604b385c795a80442384ae688cb907066",
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"overlay-audit.json": "03fa596094d386840f2a8e00e59d76eb4dea10b5835a8270e32dce50e7640c38",
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"overlay-input.npz": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
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"overlay-manifest.json": "b0ee003192fbdfd869f8b23c9bbab0ff99079b7bd2bf1dc33b7afef40785a143",
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"requests.csv": "d2250de77a7723e0237f53b54038377b5502ccf3a549cc08f3344a1e924b99ac",
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"runtime-provenance.json": "ec67e5a4d47948e7152b0c532fc74fd8e0571fd8697cba760352bbfbd4763d48",
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"sealed-gpu-source.diff": "0584f865885b18e6a36870a7ecfbbc98d7a94274fa5e9e073e7cf97597d78a03",
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"source-audit.json": "d644f0265632f117bba0e045d26fb266765b1d005a89426b6242f3de034be935",
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"state.npz": "67943c878314d88e6c34ee89a08ec61dfb9c66c43279766f54946556962b67a3",
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"summary.json": "dfcae9b785dcaa579d813185df194ce69a18e672738deaa63766a61585e59acc",
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"terminal-queues.npz": "749a93983ffcf0b89e2b0f67f51bc11134c575d7e8d0230d6ebe333fa20c28ab"
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},
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"global_next_tick": 5,
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"global_tick_offset": 0,
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"pre_seal_state_integrity_independently_proven": false,
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"schema": "phase4an-checkpoint-v1",
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"segment_steps": 5,
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"state_binding_origin": "checkpoint seal; fresh runtime receipt did not hash state.npz"
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}
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+9
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{
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"accepted_arriving_edges": 0,
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"all_finite": true,
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"arriving_edges": 0,
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"finite_observed_ticks": 5,
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"first_failure_tick": -1,
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"mode": "light",
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"scope": "every completed tick; no neuronal or APL tensor mutated by observer"
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}
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+40
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{
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"am_helper_sha256": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4",
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"apl_fast_edges_zeroed": 5845,
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"base_candidate_sha256": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
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"base_weights_raw_sha256": "a8c19cde743bd456bcb2e988d504f805b6943d6ceb97cd241d6e1e472ab5a591",
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"bridge": "baseSI64 + (delta32 widened to float64) * float64(0.001); nonzero rows only",
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"candidate_count": 14232,
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"complete": true,
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"delta_dtype": "float32",
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"delta_raw_sha256": "ea03a0ab6b537ea6bcac86191dc79f4eed997ef890885cb695440a0cfc224a67",
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"delta_units": "mV",
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"effective_weights_raw_sha256": "a60a2846dd952916097cecd1d3daf74cf5e785818749e0ffd818b3ced1c58fd2",
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"eligibility_v2_source_sha256": null,
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"inherited_AJ_provenance_only": {
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"candidate_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
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"diagnostic_additions": [
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"generated/applied/pending trace split",
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"fixed-sequence bitwise audit",
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"source provenance and final APL state disclosure"
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],
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"module_globals_patched": false,
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"only_dynamics_change": "fixed zero-initialized 0/18-step h32 delay before unchanged end g write",
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"sealed_source_sha256": {
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"ae_backend": "03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278",
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"af_queue": "d72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961",
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"ag_gpu": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
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"ag_worker": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291"
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},
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"source_diff_sha256": "0584f865885b18e6a36870a7ecfbbc98d7a94274fa5e9e073e7cf97597d78a03"
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},
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"mask_sha256": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
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"nonzero_delta_count": 14232,
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"overlay_name": "static25",
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"parent_chain_verified_by_runtime": false,
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"parent_snapshot_sha256": null,
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"schema": "phase4an-overlay-install-v1",
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"state_dtype": "float64",
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"weights_updated_during_run": false,
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"zero_rows_untouched": true
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}
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+12
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{
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"aj_model_dir": "/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1",
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"am_overlay_path": "/data/digital-drosophila/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py",
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"am_overlay_sha256": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4",
|
||||
"base_candidate_path": "/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/protocol/base-candidate.float32-mV.npy",
|
||||
"base_candidate_sha256": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
|
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"mask_path": "/data/digital-drosophila/experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-ids.int64.npy",
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"mask_sha256": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
|
||||
"overlay_name": "static25",
|
||||
"overlay_sha256": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
|
||||
"schema": "phase4an-overlay-v1"
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||||
}
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+1
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tick,neuron_idx,attempted,accepted,rejected
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|
+85
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{
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"admission_bound_changed_explicitly": true,
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"ast": {
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"added_runtime_callbacks": [
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"_runtime.install(weights, graph, apl_out_mask, upload, out_dir, source_provenance, device)",
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"_runtime.finish(ring, apl_ring, apl, steps, out_dir)",
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"_runtime.timing(steps, pending)",
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"_runtime.after_tick(tick, v, g, ref, drive, apl_state, h, applied_h)",
|
||||
"_runtime.arrivals(expanded, destination, ref)"
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],
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"admission_edit": "0 < steps <= 1000 -> 0 < steps <= spec.max_steps",
|
||||
"aj_source_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"derived_math_ast_sha256": "e46b7d037862b54c0000381ea50df3ba416c7c2c134e3cea78fa90ddf549f710",
|
||||
"derived_module_ast_sha256": "4572043a15a53b3874766b40b4521422567761dbc75db57535ab44b817210429",
|
||||
"derived_namespace_file": "/data/digital-drosophila/models/male-cns-lif/olfactory-conditioning-lab-v1/runtime_light.py",
|
||||
"math_ast_sha256": "e46b7d037862b54c0000381ea50df3ba416c7c2c134e3cea78fa90ddf549f710",
|
||||
"mathematical_ast_identical": true,
|
||||
"mode": "light",
|
||||
"old_globals_patched": false,
|
||||
"original_module_file": "/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/gpu_timing.py",
|
||||
"output_metadata_binding": "new write_json only labels recording/within-trial scope; no old global mutated",
|
||||
"post_loop_terminal_recording": "_runtime.finish(ring, apl_ring, apl, steps, out_dir)",
|
||||
"pre_loop_installation": "_runtime.install(weights, graph, apl_out_mask, upload, out_dir, source_provenance, device)",
|
||||
"reference_entire_tick_loop_identical": false,
|
||||
"removed_diagnostic_statements": [
|
||||
"Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_applied'), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='apl-applied.float32.npy')), Attribute(value=Name(id='np', ctx=Load()), attr='float32', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Constant(value=4064)], ctx=Load())], keywords=[]))",
|
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"For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='width', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='drive'), Constant(value=2)], ctx=Load()), Tuple(elts=[Constant(value='state'), Constant(value=2)], ctx=Load()), Tuple(elts=[Constant(value='inhibition'), Constant(value=4064)], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=Constant(value='apl-'), op=Add(), right=Name(id='name', ctx=Load())), op=Add(), right=Constant(value='.float32.npy'))), Attribute(value=Name(id='np', ctx=Load()), attr='float32', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='width', ctx=Load())], ctx=Load())], keywords=[]))], orelse=[])",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='dtype', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='v'), Attribute(value=Name(id='np', ctx=Load()), attr='float64', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='g'), Attribute(value=Name(id='np', ctx=Load()), attr='float64', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='ref'), Attribute(value=Name(id='np', ctx=Load()), attr='int32', ctx=Load())], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=Name(id='name', ctx=Load()), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=BinOp(left=Name(id='name', ctx=Load()), op=Add(), right=Constant(value='-history.')), op=Add(), right=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='dtype', ctx=Load()), args=[Name(id='dtype', ctx=Load())], keywords=[]), attr='name', ctx=Load())), op=Add(), right=Constant(value='.npy'))), Name(id='dtype', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='n', ctx=Load())], ctx=Load())], keywords=[])), Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='pre_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=BinOp(left=BinOp(left=Constant(value='preAPL-'), op=Add(), right=Name(id='name', ctx=Load())), op=Add(), right=Constant(value='.')), op=Add(), right=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='dtype', ctx=Load()), args=[Name(id='dtype', ctx=Load())], keywords=[]), attr='name', ctx=Load())), op=Add(), right=Constant(value='.npy'))), Name(id='dtype', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='n', ctx=Load())], ctx=Load())], keywords=[]))], orelse=[])], orelse=[])",
|
||||
"Assign(targets=[Name(id='expanded_global', ctx=Store())], value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='empty', ctx=Load()), args=[Constant(value=0)], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='int64', ctx=Load()))]))",
|
||||
"Assign(targets=[Name(id='accepted_cpu', ctx=Store())], value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='empty', ctx=Load()), args=[Constant(value=0)], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='uint8', ctx=Load()))]))",
|
||||
"Assign(targets=[Name(id='expanded_global', ctx=Store())], value=Call(func=Attribute(value=Subscript(value=Subscript(value=Name(id='graph', ctx=Load()), slice=Constant(value='edge_id'), ctx=Load()), slice=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='expanded', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), ctx=Load()), attr='copy', ctx=Load()), args=[], keywords=[]))",
|
||||
"Assign(targets=[Name(id='accepted_cpu', ctx=Store())], value=Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Compare(left=Subscript(value=Name(id='ref', ctx=Load()), slice=Call(func=Attribute(value=Name(id='destination', ctx=Load()), attr='long', ctx=Load()), args=[], keywords=[]), ctx=Load()), ops=[Eq()], comparators=[Constant(value=0)]), attr='to', ctx=Load()), args=[Attribute(value=Name(id='torch', ctx=Load()), attr='uint8', ctx=Load())], keywords=[]), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]))",
|
||||
"Assign(targets=[Name(id='queue', ctx=Store())], value=Call(func=Name(id='queue_summary', ctx=Load()), args=[Name(id='tick', ctx=Load()), Name(id='expanded_global', ctx=Load()), Name(id='accepted_cpu', ctx=Load())], keywords=[]))",
|
||||
"Expr(value=Call(func=Attribute(value=Name(id='queue_output', ctx=Load()), attr='write', ctx=Load()), args=[BinOp(left=Call(func=Attribute(value=Name(id='json', ctx=Load()), attr='dumps', ctx=Load()), args=[Name(id='queue', ctx=Load())], keywords=[keyword(arg='allow_nan', value=Constant(value=False))]), op=Add(), right=Constant(value='\\n'))], keywords=[]))",
|
||||
"AugAssign(target=Name(id='due_total', ctx=Store()), op=Add(), value=Subscript(value=Name(id='queue', ctx=Load()), slice=Constant(value='count'), ctx=Load()))",
|
||||
"AugAssign(target=Name(id='accepted_due_total', ctx=Store()), op=Add(), value=Subscript(value=Name(id='queue', ctx=Load()), slice=Constant(value='accepted_count'), ctx=Load()))",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='v'), Name(id='v', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='g'), Name(id='g', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='ref'), Name(id='ref', ctx=Load())], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='pre_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='value', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]))], orelse=[])], orelse=[])",
|
||||
"Assign(targets=[Name(id='apl_cpu', ctx=Store())], value=Dict(keys=[Constant(value='drive'), Constant(value='state'), Constant(value='inhibition'), Constant(value='applied')], values=[Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='drive', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='apl_state', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='h', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='applied_h', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[])]))",
|
||||
"For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Name(id='value', ctx=Load()))], orelse=[])",
|
||||
"Assign(targets=[Name(id='actual', ctx=Store())], value=Dict(keys=[Constant(value='v'), Constant(value='g'), Constant(value='ref')], values=[Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='v', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='g', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='ref', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[])]))",
|
||||
"Assign(targets=[Name(id='finite', ctx=Store())], value=Call(func=Name(id='all', ctx=Load()), args=[GeneratorExp(elt=Call(func=Name(id='bool', ctx=Load()), args=[Call(func=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='isfinite', ctx=Load()), args=[Name(id='value', ctx=Load())], keywords=[]), attr='all', ctx=Load()), args=[], keywords=[])], keywords=[]), generators=[comprehension(target=Name(id='value', ctx=Store()), iter=BinOp(left=Call(func=Name(id='list', ctx=Load()), args=[Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='values', ctx=Load()), args=[], keywords=[])], keywords=[]), op=Add(), right=Call(func=Name(id='list', ctx=Load()), args=[Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='values', ctx=Load()), args=[], keywords=[])], keywords=[])), ifs=[], is_async=0)])], keywords=[]))",
|
||||
"Assign(targets=[Name(id='row', ctx=Store())], value=Dict(keys=[Constant(value='tick'), None], values=[Name(id='tick', ctx=Load()), DictComp(key=BinOp(left=Name(id='name', ctx=Load()), op=Add(), right=Constant(value='_sha256')), value=Call(func=Name(id='raw_hash', ctx=Load()), args=[Name(id='value', ctx=Load()), IfExp(test=Compare(left=Name(id='name', ctx=Load()), ops=[Eq()], comparators=[Constant(value='ref')]), body=Constant(value='<i4'), orelse=Constant(value='<f8'))], keywords=[]), generators=[comprehension(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), ifs=[], is_async=0)])]))",
|
||||
"Expr(value=Call(func=Attribute(value=Name(id='hash_output', ctx=Load()), attr='write', ctx=Load()), args=[BinOp(left=Call(func=Attribute(value=Name(id='json', ctx=Load()), attr='dumps', ctx=Load()), args=[Name(id='row', ctx=Load())], keywords=[keyword(arg='allow_nan', value=Constant(value=False))]), op=Add(), right=Constant(value='\\n'))], keywords=[]))",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=Name(id='name', ctx=Load()), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Name(id='value', ctx=Load()))], orelse=[])], orelse=[])",
|
||||
"If(test=UnaryOp(op=Not(), operand=Name(id='finite', ctx=Load())), body=[With(items=[withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='first-failure-state.npz')), attr='open', ctx=Load()), args=[Constant(value='xb')], keywords=[]), optional_vars=Name(id='target', ctx=Store()))], body=[Expr(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='savez_compressed', ctx=Load()), args=[Name(id='target', ctx=Load())], keywords=[keyword(arg='tick', value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='array', ctx=Load()), args=[Name(id='tick', ctx=Load())], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='int32', ctx=Load()))])), keyword(value=Name(id='actual', ctx=Load())), keyword(value=DictComp(key=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), value=Name(id='value', ctx=Load()), generators=[comprehension(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), ifs=[], is_async=0)]))]))]), Expr(value=Call(func=Name(id='require', ctx=Load()), args=[Constant(value=False), Constant(value='Nonfinite state; first failure saved')], keywords=[]))], orelse=[])"
|
||||
],
|
||||
"replaced_diagnostic_nodes": [
|
||||
"withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='queue.jsonl')), attr='open', ctx=Load()), args=[Constant(value='x')], keywords=[keyword(arg='encoding', value=Constant(value='utf-8')), keyword(arg='buffering', value=Constant(value=1))]), optional_vars=Name(id='queue_output', ctx=Store()))",
|
||||
"withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='tick-state-hashes.jsonl')), attr='open', ctx=Load()), args=[Constant(value='x')], keywords=[keyword(arg='encoding', value=Constant(value='utf-8')), keyword(arg='buffering', value=Constant(value=1))]), optional_vars=Name(id='hash_output', ctx=Store()))",
|
||||
"Assign(targets=[Name(id='timing', ctx=Store())], value=Call(func=Name(id='audit_sequence', ctx=Load()), args=[Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_inhibition'), ctx=Load()), Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_applied'), ctx=Load()), Name(id='pending', ctx=Load()), Name(id='apl_delay', ctx=Load())], keywords=[]))"
|
||||
]
|
||||
},
|
||||
"complete": true,
|
||||
"finite_audit_sha256": "4d5ecd025cf500818de9c269269596c604b385c795a80442384ae688cb907066",
|
||||
"input_sha256": {
|
||||
"/data/digital-drosophila/experiments/phase4ag-author-apl-r2/graphs/full/weights.npy": "462839ffc3feb8f6c278044488082b1c8e410e7f23229d6b5e29d1b7042416a1",
|
||||
"/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/overlays/static25.npz": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
|
||||
"/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/protocol/base-candidate.float32-mV.npy": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/cases/static25--chain--light-s00/requests.npz": "517b500f350b0825f7cc9c639beb62d06764de286b13e0835cb26c5f83ff106a",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/cases/static25--chain--light-s00/spec.json": "ddb53c3d067aa3c85c81f2525db59dc6ab8eda1bfeb910fd7a3828222499e5ff",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/overlays/static25.json": "b0ee003192fbdfd869f8b23c9bbab0ff99079b7bd2bf1dc33b7afef40785a143",
|
||||
"/data/digital-drosophila/experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-ids.int64.npy": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
|
||||
"/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/gpu_timing.py": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/timing_queue.py": "54df6d4818e2a0c26e96fb0aaf5d9b71cd964981706da937562d48af79aca14e",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-apl-lab-v2/gpu_apl.py": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-apl-lab-v2/legacy_apl_worker.py": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-fullgraph-lab-v1/oracle_full.py": "d72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/author_ext.cpp": "208a937d17bbb041b9bf6b25b89264ee566830b60609e58491b44583d8541f15",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/author_ext.cu": "669f166e18ce9a3f63fc723db8b0a8b74f7fa4757194b1bd65b4cf6008a7787e",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/gpu_backend.py": "03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278",
|
||||
"/data/digital-drosophila/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4"
|
||||
},
|
||||
"learning_pass_claimed": false,
|
||||
"math_changed": false,
|
||||
"mode": "light",
|
||||
"old_globals_patched": false,
|
||||
"overlay_audit_sha256": "03fa596094d386840f2a8e00e59d76eb4dea10b5835a8270e32dce50e7640c38",
|
||||
"parent_chain_verification_owned_by_coordinator": true,
|
||||
"schema": "phase4an-reporting-adapter-v1",
|
||||
"source_file": "/data/digital-drosophila/models/male-cns-lif/olfactory-conditioning-lab-v1/runtime_light.py",
|
||||
"source_sha256": "522b8c31ea938890fe15364fccd25ccc5bded54101754909f255532e7ad01aae",
|
||||
"summary_sha256": "dfcae9b785dcaa579d813185df194ce69a18e672738deaa63766a61585e59acc",
|
||||
"terminal_queues_sha256": "749a93983ffcf0b89e2b0f67f51bc11134c575d7e8d0230d6ebe333fa20c28ab",
|
||||
"weights_updated_during_run": false
|
||||
}
|
||||
+17
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"sealed_source_sha256": {
|
||||
"ag_gpu": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
|
||||
"ag_worker": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291",
|
||||
"ae_backend": "03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278",
|
||||
"af_queue": "d72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961"
|
||||
},
|
||||
"candidate_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"source_diff_sha256": "0584f865885b18e6a36870a7ecfbbc98d7a94274fa5e9e073e7cf97597d78a03",
|
||||
"module_globals_patched": false,
|
||||
"only_dynamics_change": "fixed zero-initialized 0/18-step h32 delay before unchanged end g write",
|
||||
"diagnostic_additions": [
|
||||
"generated/applied/pending trace split",
|
||||
"fixed-sequence bitwise audit",
|
||||
"source provenance and final APL state disclosure"
|
||||
]
|
||||
}
|
||||
+181
@@ -0,0 +1,181 @@
|
||||
{
|
||||
"accepted_arriving_edges": 0,
|
||||
"accepted_requests": 0,
|
||||
"all_finite": true,
|
||||
"apl_component": {
|
||||
"array_sha256": {
|
||||
"apl_globals.npy": "979ef88dff30d41168ce9b377a006ccb3cd034b2dce86d54923ca0f4b87cb6a6",
|
||||
"input_matrix.npy": "528a5f6f5ffe424f323c5a44695db4a7cf32570709832eff2f37f49e85c92c3e",
|
||||
"kc_globals.npy": "9e990d10a63b0f74cd7bbbdc5369082f24d5246487af944ba289bc6bf48d4b75",
|
||||
"output_matrix.npy": "0dcf02cdb7836ab72da32ac47f5682ca33e25f63a8a662a8452d4ea9d46babb9"
|
||||
},
|
||||
"decay_f32_bits": "3f7eb923",
|
||||
"dt_ms": 0.1,
|
||||
"environment": {
|
||||
"CUBLAS_WORKSPACE_CONFIG": null,
|
||||
"cuda": "13.0",
|
||||
"cuda_matmul_allow_tf32": false,
|
||||
"cudnn": 92400,
|
||||
"cudnn_allow_tf32": true,
|
||||
"cudnn_benchmark": false,
|
||||
"cudnn_deterministic": false,
|
||||
"deterministic_algorithms": false,
|
||||
"device_capability": [
|
||||
8,
|
||||
9
|
||||
],
|
||||
"device_index": 0,
|
||||
"device_name": "NVIDIA GeForce RTX 4090",
|
||||
"float32_matmul_precision": "highest",
|
||||
"numpy": "2.2.6",
|
||||
"precision_configuration_changed_by_component": false,
|
||||
"torch": "2.14.0+cu130"
|
||||
},
|
||||
"files_sha256": {
|
||||
"apl_globals.npy": "8388c8795d49cfe5b14fda54f76ef3a35030c62ba87bd8ca6334a2dcdf186f19",
|
||||
"input_matrix.npy": "c4d3df703ea5f1d7402b8255cfa19d9744139ad1048827c23b151d8ba766fec6",
|
||||
"kc_globals.npy": "97a570aafa089f93e642b2bb07e3a3322dabb14c3c7dd431f0c8d2b3b7951fdd",
|
||||
"output_matrix.npy": "e2d0a1ccd740e6777245ebf2efcd88bf5e1da9e47308c63ec8e83d451e134a73"
|
||||
},
|
||||
"gain_f32_bits": "3c23d70a",
|
||||
"h_units": "legacy mV",
|
||||
"initial_state": "float32 zeros",
|
||||
"n_apl": 2,
|
||||
"n_kc": 4064,
|
||||
"n_neurons": 166700,
|
||||
"ok": true,
|
||||
"operator_sequence": "state.mul_(decay32); drive=mv(I32,spikes32); state.add_(drive); h=matmul(state,O32)*gain32",
|
||||
"protocol": "phase4ag-apl-v1"
|
||||
},
|
||||
"apl_delay_steps": 18,
|
||||
"apl_fast_edges_zeroed": 5845,
|
||||
"apl_precision": "float32",
|
||||
"apl_schedule": "end, after threshold/reset and guarded arrivals, unconditional all KC",
|
||||
"apl_si_conversion": "applied h32 -> float64 -> multiply float64 0.001 -> separate float64 subtraction",
|
||||
"apl_timing": {
|
||||
"apl_delay_steps": 18,
|
||||
"applied_generated_rows": 0,
|
||||
"applied_trace": null,
|
||||
"biological_delay_measurement_claimed": false,
|
||||
"brain_tail_advanced": false,
|
||||
"closed_loop_branch_integrals_claimed_equal": false,
|
||||
"final_apl_state_float32": [
|
||||
0.0,
|
||||
0.0
|
||||
],
|
||||
"final_apl_state_nonzero": false,
|
||||
"final_apl_state_u32_bits": [
|
||||
0,
|
||||
0
|
||||
],
|
||||
"finite_generated_sequence_only": true,
|
||||
"full_sequence_bitwise_audit_performed": false,
|
||||
"future_apl_decay_or_feedback_generated": false,
|
||||
"generated_rows": 5,
|
||||
"generated_trace": null,
|
||||
"pending_application_tick_start": 5,
|
||||
"pending_application_tick_stop_exclusive": 23,
|
||||
"pending_generated_count": 5,
|
||||
"pending_generated_tick_start": 0,
|
||||
"pending_generated_tick_stop_exclusive": 5,
|
||||
"pending_initial_zero_prefix": 13,
|
||||
"pending_queue_drained": false,
|
||||
"pending_raw_sha256": "81cc5530fab22979a78429b863d208e62d9249ddff3a0a06de0edbda0c688aaf",
|
||||
"pending_shape": [
|
||||
18,
|
||||
4064
|
||||
],
|
||||
"pending_trace": "apl-pending-tail.float32.npy",
|
||||
"scope": "Original D18 ring AST retained; generated/applied histories not recorded",
|
||||
"steps": 5
|
||||
},
|
||||
"arriving_edges": 0,
|
||||
"build": {
|
||||
"arch_list": "8.9",
|
||||
"cuda_flags": [
|
||||
"-O2",
|
||||
"--fmad=false",
|
||||
"--ftz=false",
|
||||
"--prec-div=true",
|
||||
"--prec-sqrt=true"
|
||||
],
|
||||
"sources": {
|
||||
"author_ext.cpp": "208a937d17bbb041b9bf6b25b89264ee566830b60609e58491b44583d8541f15",
|
||||
"author_ext.cu": "669f166e18ce9a3f63fc723db8b0a8b74f7fa4757194b1bd65b4cf6008a7787e"
|
||||
},
|
||||
"torch": "2.14.0+cu130",
|
||||
"torch_cuda": "13.0"
|
||||
},
|
||||
"build_or_cache_seconds": 0.468830017001892,
|
||||
"case": "seed_validation-physiological-00-s1073741825",
|
||||
"checkpoint_continuation_used": false,
|
||||
"complete": true,
|
||||
"completed_ticks": 5,
|
||||
"counts_match_sparse_events": true,
|
||||
"cpu_sync_each_tick": true,
|
||||
"diagnostic_mode": "light",
|
||||
"diagnostic_simulation_seconds": 0.20982420800282853,
|
||||
"edges": 25582938,
|
||||
"effective_weights_raw_sha256": "a60a2846dd952916097cecd1d3daf74cf5e785818749e0ffd818b3ced1c58fd2",
|
||||
"entire_neural_trial_executed": true,
|
||||
"explicit_steps_executed": 5,
|
||||
"first_failure_tick": -1,
|
||||
"full_APL_history_recorded": false,
|
||||
"full_queue_hashes_recorded": false,
|
||||
"full_sequence_bitwise_audit_performed": false,
|
||||
"full_tick_state_hashes_recorded": false,
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||||
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@@ -0,0 +1,40 @@
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+12
@@ -0,0 +1,12 @@
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+5
@@ -0,0 +1,5 @@
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tick,neuron_idx,attempted,accepted,rejected
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@@ -0,0 +1,96 @@
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{
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||||
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|
||||
"aj_source_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"derived_math_ast_sha256": "e46b7d037862b54c0000381ea50df3ba416c7c2c134e3cea78fa90ddf549f710",
|
||||
"derived_module_ast_sha256": "4572043a15a53b3874766b40b4521422567761dbc75db57535ab44b817210429",
|
||||
"math_ast_sha256": "e46b7d037862b54c0000381ea50df3ba416c7c2c134e3cea78fa90ddf549f710",
|
||||
"mathematical_ast_identical": true,
|
||||
"mode": "light",
|
||||
"old_globals_patched": false,
|
||||
"post_loop_terminal_recording": "_runtime.finish(ring, apl_ring, apl, steps, out_dir)",
|
||||
"pre_loop_installation": "_runtime.install(weights, graph, apl_out_mask, upload, out_dir, source_provenance, device)",
|
||||
"reference_entire_tick_loop_identical": false,
|
||||
"removed_diagnostic_statements": [
|
||||
"Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_applied'), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='apl-applied.float32.npy')), Attribute(value=Name(id='np', ctx=Load()), attr='float32', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Constant(value=4064)], ctx=Load())], keywords=[]))",
|
||||
"For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='width', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='drive'), Constant(value=2)], ctx=Load()), Tuple(elts=[Constant(value='state'), Constant(value=2)], ctx=Load()), Tuple(elts=[Constant(value='inhibition'), Constant(value=4064)], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=Constant(value='apl-'), op=Add(), right=Name(id='name', ctx=Load())), op=Add(), right=Constant(value='.float32.npy'))), Attribute(value=Name(id='np', ctx=Load()), attr='float32', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='width', ctx=Load())], ctx=Load())], keywords=[]))], orelse=[])",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='dtype', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='v'), Attribute(value=Name(id='np', ctx=Load()), attr='float64', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='g'), Attribute(value=Name(id='np', ctx=Load()), attr='float64', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='ref'), Attribute(value=Name(id='np', ctx=Load()), attr='int32', ctx=Load())], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=Name(id='name', ctx=Load()), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=BinOp(left=Name(id='name', ctx=Load()), op=Add(), right=Constant(value='-history.')), op=Add(), right=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='dtype', ctx=Load()), args=[Name(id='dtype', ctx=Load())], keywords=[]), attr='name', ctx=Load())), op=Add(), right=Constant(value='.npy'))), Name(id='dtype', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='n', ctx=Load())], ctx=Load())], keywords=[])), Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='pre_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=BinOp(left=BinOp(left=Constant(value='preAPL-'), op=Add(), right=Name(id='name', ctx=Load())), op=Add(), right=Constant(value='.')), op=Add(), right=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='dtype', ctx=Load()), args=[Name(id='dtype', ctx=Load())], keywords=[]), attr='name', ctx=Load())), op=Add(), right=Constant(value='.npy'))), Name(id='dtype', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='n', ctx=Load())], ctx=Load())], keywords=[]))], orelse=[])], orelse=[])",
|
||||
"Assign(targets=[Name(id='expanded_global', ctx=Store())], value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='empty', ctx=Load()), args=[Constant(value=0)], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='int64', ctx=Load()))]))",
|
||||
"Assign(targets=[Name(id='accepted_cpu', ctx=Store())], value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='empty', ctx=Load()), args=[Constant(value=0)], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='uint8', ctx=Load()))]))",
|
||||
"Assign(targets=[Name(id='expanded_global', ctx=Store())], value=Call(func=Attribute(value=Subscript(value=Subscript(value=Name(id='graph', ctx=Load()), slice=Constant(value='edge_id'), ctx=Load()), slice=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='expanded', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), ctx=Load()), attr='copy', ctx=Load()), args=[], keywords=[]))",
|
||||
"Assign(targets=[Name(id='accepted_cpu', ctx=Store())], value=Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Compare(left=Subscript(value=Name(id='ref', ctx=Load()), slice=Call(func=Attribute(value=Name(id='destination', ctx=Load()), attr='long', ctx=Load()), args=[], keywords=[]), ctx=Load()), ops=[Eq()], comparators=[Constant(value=0)]), attr='to', ctx=Load()), args=[Attribute(value=Name(id='torch', ctx=Load()), attr='uint8', ctx=Load())], keywords=[]), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]))",
|
||||
"Assign(targets=[Name(id='queue', ctx=Store())], value=Call(func=Name(id='queue_summary', ctx=Load()), args=[Name(id='tick', ctx=Load()), Name(id='expanded_global', ctx=Load()), Name(id='accepted_cpu', ctx=Load())], keywords=[]))",
|
||||
"Expr(value=Call(func=Attribute(value=Name(id='queue_output', ctx=Load()), attr='write', ctx=Load()), args=[BinOp(left=Call(func=Attribute(value=Name(id='json', ctx=Load()), attr='dumps', ctx=Load()), args=[Name(id='queue', ctx=Load())], keywords=[keyword(arg='allow_nan', value=Constant(value=False))]), op=Add(), right=Constant(value='\\n'))], keywords=[]))",
|
||||
"AugAssign(target=Name(id='due_total', ctx=Store()), op=Add(), value=Subscript(value=Name(id='queue', ctx=Load()), slice=Constant(value='count'), ctx=Load()))",
|
||||
"AugAssign(target=Name(id='accepted_due_total', ctx=Store()), op=Add(), value=Subscript(value=Name(id='queue', ctx=Load()), slice=Constant(value='accepted_count'), ctx=Load()))",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='v'), Name(id='v', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='g'), Name(id='g', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='ref'), Name(id='ref', ctx=Load())], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='pre_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='value', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]))], orelse=[])], orelse=[])",
|
||||
"Assign(targets=[Name(id='apl_cpu', ctx=Store())], value=Dict(keys=[Constant(value='drive'), Constant(value='state'), Constant(value='inhibition'), Constant(value='applied')], values=[Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='drive', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='apl_state', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='h', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='applied_h', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[])]))",
|
||||
"For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Name(id='value', ctx=Load()))], orelse=[])",
|
||||
"Assign(targets=[Name(id='actual', ctx=Store())], value=Dict(keys=[Constant(value='v'), Constant(value='g'), Constant(value='ref')], values=[Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='v', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='g', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='ref', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[])]))",
|
||||
"Assign(targets=[Name(id='finite', ctx=Store())], value=Call(func=Name(id='all', ctx=Load()), args=[GeneratorExp(elt=Call(func=Name(id='bool', ctx=Load()), args=[Call(func=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='isfinite', ctx=Load()), args=[Name(id='value', ctx=Load())], keywords=[]), attr='all', ctx=Load()), args=[], keywords=[])], keywords=[]), generators=[comprehension(target=Name(id='value', ctx=Store()), iter=BinOp(left=Call(func=Name(id='list', ctx=Load()), args=[Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='values', ctx=Load()), args=[], keywords=[])], keywords=[]), op=Add(), right=Call(func=Name(id='list', ctx=Load()), args=[Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='values', ctx=Load()), args=[], keywords=[])], keywords=[])), ifs=[], is_async=0)])], keywords=[]))",
|
||||
"Assign(targets=[Name(id='row', ctx=Store())], value=Dict(keys=[Constant(value='tick'), None], values=[Name(id='tick', ctx=Load()), DictComp(key=BinOp(left=Name(id='name', ctx=Load()), op=Add(), right=Constant(value='_sha256')), value=Call(func=Name(id='raw_hash', ctx=Load()), args=[Name(id='value', ctx=Load()), IfExp(test=Compare(left=Name(id='name', ctx=Load()), ops=[Eq()], comparators=[Constant(value='ref')]), body=Constant(value='<i4'), orelse=Constant(value='<f8'))], keywords=[]), generators=[comprehension(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), ifs=[], is_async=0)])]))",
|
||||
"Expr(value=Call(func=Attribute(value=Name(id='hash_output', ctx=Load()), attr='write', ctx=Load()), args=[BinOp(left=Call(func=Attribute(value=Name(id='json', ctx=Load()), attr='dumps', ctx=Load()), args=[Name(id='row', ctx=Load())], keywords=[keyword(arg='allow_nan', value=Constant(value=False))]), op=Add(), right=Constant(value='\\n'))], keywords=[]))",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=Name(id='name', ctx=Load()), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Name(id='value', ctx=Load()))], orelse=[])], orelse=[])",
|
||||
"If(test=UnaryOp(op=Not(), operand=Name(id='finite', ctx=Load())), body=[With(items=[withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='first-failure-state.npz')), attr='open', ctx=Load()), args=[Constant(value='xb')], keywords=[]), optional_vars=Name(id='target', ctx=Store()))], body=[Expr(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='savez_compressed', ctx=Load()), args=[Name(id='target', ctx=Load())], keywords=[keyword(arg='tick', value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='array', ctx=Load()), args=[Name(id='tick', ctx=Load())], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='int32', ctx=Load()))])), keyword(value=Name(id='actual', ctx=Load())), keyword(value=DictComp(key=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), value=Name(id='value', ctx=Load()), generators=[comprehension(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), ifs=[], is_async=0)]))]))]), Expr(value=Call(func=Name(id='require', ctx=Load()), args=[Constant(value=False), Constant(value='Nonfinite state; first failure saved')], keywords=[]))], orelse=[])"
|
||||
],
|
||||
"replaced_diagnostic_nodes": [
|
||||
"withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='queue.jsonl')), attr='open', ctx=Load()), args=[Constant(value='x')], keywords=[keyword(arg='encoding', value=Constant(value='utf-8')), keyword(arg='buffering', value=Constant(value=1))]), optional_vars=Name(id='queue_output', ctx=Store()))",
|
||||
"withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='tick-state-hashes.jsonl')), attr='open', ctx=Load()), args=[Constant(value='x')], keywords=[keyword(arg='encoding', value=Constant(value='utf-8')), keyword(arg='buffering', value=Constant(value=1))]), optional_vars=Name(id='hash_output', ctx=Store()))",
|
||||
"Assign(targets=[Name(id='timing', ctx=Store())], value=Call(func=Name(id='audit_sequence', ctx=Load()), args=[Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_inhibition'), ctx=Load()), Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_applied'), ctx=Load()), Name(id='pending', ctx=Load()), Name(id='apl_delay', ctx=Load())], keywords=[]))"
|
||||
]
|
||||
},
|
||||
"clock_admission_new": "tick + _continuation.global_offset >= 18",
|
||||
"clock_admission_old": "tick >= 18",
|
||||
"derived_module_ast_sha256": "f6a9a518081089a4be9692178688663cfb39f9d44c92c4abb119620149f54007",
|
||||
"diagnostic_namespace_binding": "audit_sequence checks parent_pending + generated, not an assumed zero-initial queue",
|
||||
"full_AST_rollback_identical": true,
|
||||
"kernels_sorting_and_local_ring_math_unchanged": true,
|
||||
"restore_hook": "_continuation.restore(v, g, ref, counts, ring, apl_ring, apl, upload)"
|
||||
},
|
||||
"complete": true,
|
||||
"finite_audit_sha256": "ff22fb288988dea3ac624bcec27359837bdfa4dab244768b252e65e2e1acfa46",
|
||||
"fresh_runtime_sha256": "522b8c31ea938890fe15364fccd25ccc5bded54101754909f255532e7ad01aae",
|
||||
"global_next_tick": 18,
|
||||
"global_tick_offset": 5,
|
||||
"input_sha256": {
|
||||
"/data/digital-drosophila/experiments/phase4af-author-fullgraph/oracle/no_input/coefficients.json": "bde79d95ef0097b827d5faf4d5658eafc009d8e9fcef1fddd645c953823e3f64",
|
||||
"/data/digital-drosophila/experiments/phase4ag-author-apl-r2/graphs/full/weights.npy": "462839ffc3feb8f6c278044488082b1c8e410e7f23229d6b5e29d1b7042416a1",
|
||||
"/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/overlays/static25.npz": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
|
||||
"/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/protocol/base-candidate.float32-mV.npy": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/cases/static25--chain--light-s01/requests.npz": "929f5b8a23043c0a10790d7cc0683ff81a6049b4e714db86b1fb54cb7f3ca8f2",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/cases/static25--chain--light-s01/spec.json": "c29fcf0d124c07d169e9357ff07b5cd9dcb6d6676562d9ba4db85c6c8f24e613",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/overlays/static25.json": "b0ee003192fbdfd869f8b23c9bbab0ff99079b7bd2bf1dc33b7afef40785a143",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/runs/static25--chain--light-s00/checkpoint-manifest.json": "e1eb04c098b366870cb05869af9a4277d85fb7722f87202ac9e3b97e768d30cb",
|
||||
"/data/digital-drosophila/experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-ids.int64.npy": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
|
||||
"/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/gpu_timing.py": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/timing_queue.py": "54df6d4818e2a0c26e96fb0aaf5d9b71cd964981706da937562d48af79aca14e",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-apl-lab-v2/gpu_apl.py": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-apl-lab-v2/legacy_apl_worker.py": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-fullgraph-lab-v1/oracle_full.py": "d72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/author_ext.cpp": "208a937d17bbb041b9bf6b25b89264ee566830b60609e58491b44583d8541f15",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/author_ext.cu": "669f166e18ce9a3f63fc723db8b0a8b74f7fa4757194b1bd65b4cf6008a7787e",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/gpu_backend.py": "03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278",
|
||||
"/data/digital-drosophila/models/male-cns-lif/olfactory-conditioning-lab-v1/runtime_light.py": "522b8c31ea938890fe15364fccd25ccc5bded54101754909f255532e7ad01aae",
|
||||
"/data/digital-drosophila/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4"
|
||||
},
|
||||
"learning_pass_claimed": false,
|
||||
"mode": "light",
|
||||
"old_globals_patched": false,
|
||||
"overlay_audit_sha256": "03fa596094d386840f2a8e00e59d76eb4dea10b5835a8270e32dce50e7640c38",
|
||||
"parent_checkpoint_manifest_sha256": "e1eb04c098b366870cb05869af9a4277d85fb7722f87202ac9e3b97e768d30cb",
|
||||
"schema": "phase4an-continuation-runtime-v1",
|
||||
"source_file": "/data/digital-drosophila/models/male-cns-lif/olfactory-conditioning-lab-v1/runtime_continuation.py",
|
||||
"source_sha256": "0b8e8e0a6a23a079dc62a88355ce355d53b3ae22f6665519a8f6aef2dcfc5aba",
|
||||
"state_sha256": "93ef29574754b862a88c665589190732acc69f9fecdbf57295f71d9a3ccc99c7",
|
||||
"summary_sha256": "0b4f6774478e8e79b551527838bf230a2c1fae1547920979c002149fff924bc9",
|
||||
"terminal_queues_sha256": "cf00897e9128b83a01d32c1c7208449911f34a776fb9a88f78273a91aabf0986",
|
||||
"weights_updated_during_run": false
|
||||
}
|
||||
+17
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"sealed_source_sha256": {
|
||||
"ag_gpu": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
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"summary.json": "82e68ff0074b239038c267a13fcfab9ca0ae034a6d731a9777a5b1d5c126c5bb",
|
||||
"terminal-queues.npz": "c62e42ea853eba86b021529340bb106425043080632d41a935d107ec32f467b1"
|
||||
},
|
||||
"global_next_tick": 19,
|
||||
"global_tick_offset": 18,
|
||||
"pre_seal_state_integrity_independently_proven": false,
|
||||
"schema": "phase4an-checkpoint-v1",
|
||||
"segment_steps": 1,
|
||||
"state_binding_origin": "checkpoint seal; fresh runtime receipt did not hash state.npz"
|
||||
}
|
||||
+29
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"checkpoint_continuation_verified_by_GPU_comparison": false,
|
||||
"clock_admission_edit": "tick + _continuation.global_offset >= 18",
|
||||
"complete": true,
|
||||
"counts_scope": "segment_only_not_lifetime",
|
||||
"global_next_tick": 19,
|
||||
"global_tick_offset": 18,
|
||||
"parent_checkpoint_dir": "/data/digital-drosophila/experiments/phase4an-engineering-validation/runs/static25--chain--light-s01",
|
||||
"parent_checkpoint_manifest_sha256": "e3885149662d9abf9666a76953784b508398a08be963b8165cbbb3548b4e2b13",
|
||||
"payload_sha256": {
|
||||
"apl-component.json": "7a49a1a8fbe42b3965913b8e483ef729ba1f13c211f8da7f10b4b2cd142e6882",
|
||||
"apl-pending-tail.float32.npy": "1f730d8d9b512d19d1cb4af20c85dcb56d60dde2a6fcdea5000f9078415850d3",
|
||||
"apl-timing-audit.json": "bf13d66b8834c17b1c68a0d107b1b48258cb2179b548ece5e2c2142fe2ca3df5",
|
||||
"finite-audit.json": "f11b37717ad3c092a481adcf78f7caffd688650bf4cb56ab644175721e63a9e8",
|
||||
"overlay-audit.json": "03fa596094d386840f2a8e00e59d76eb4dea10b5835a8270e32dce50e7640c38",
|
||||
"overlay-input.npz": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
|
||||
"overlay-manifest.json": "b0ee003192fbdfd869f8b23c9bbab0ff99079b7bd2bf1dc33b7afef40785a143",
|
||||
"requests.csv": "d2250de77a7723e0237f53b54038377b5502ccf3a549cc08f3344a1e924b99ac",
|
||||
"runtime-provenance.json": "b9547378fa968408fcaed0a2997e98d1f065d2864d4e531703739b6e9d281312",
|
||||
"sealed-gpu-source.diff": "0584f865885b18e6a36870a7ecfbbc98d7a94274fa5e9e073e7cf97597d78a03",
|
||||
"source-audit.json": "d644f0265632f117bba0e045d26fb266765b1d005a89426b6242f3de034be935",
|
||||
"state.npz": "e73da12668986893b8fe7d412e2efaa8ebf53478b12bd6081c92f3ab7d0d1960",
|
||||
"summary.json": "82e68ff0074b239038c267a13fcfab9ca0ae034a6d731a9777a5b1d5c126c5bb",
|
||||
"terminal-queues.npz": "c62e42ea853eba86b021529340bb106425043080632d41a935d107ec32f467b1"
|
||||
},
|
||||
"schema": "phase4an-continuation-receipt-v1",
|
||||
"segment_steps": 1,
|
||||
"weights_updated_during_run": false
|
||||
}
|
||||
+9
@@ -0,0 +1,9 @@
|
||||
{
|
||||
"accepted_arriving_edges": 0,
|
||||
"all_finite": true,
|
||||
"arriving_edges": 0,
|
||||
"finite_observed_ticks": 1,
|
||||
"first_failure_tick": -1,
|
||||
"mode": "light",
|
||||
"scope": "every completed tick; no neuronal or APL tensor mutated by observer"
|
||||
}
|
||||
+40
@@ -0,0 +1,40 @@
|
||||
{
|
||||
"am_helper_sha256": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4",
|
||||
"apl_fast_edges_zeroed": 5845,
|
||||
"base_candidate_sha256": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
|
||||
"base_weights_raw_sha256": "a8c19cde743bd456bcb2e988d504f805b6943d6ceb97cd241d6e1e472ab5a591",
|
||||
"bridge": "baseSI64 + (delta32 widened to float64) * float64(0.001); nonzero rows only",
|
||||
"candidate_count": 14232,
|
||||
"complete": true,
|
||||
"delta_dtype": "float32",
|
||||
"delta_raw_sha256": "ea03a0ab6b537ea6bcac86191dc79f4eed997ef890885cb695440a0cfc224a67",
|
||||
"delta_units": "mV",
|
||||
"effective_weights_raw_sha256": "a60a2846dd952916097cecd1d3daf74cf5e785818749e0ffd818b3ced1c58fd2",
|
||||
"eligibility_v2_source_sha256": null,
|
||||
"inherited_AJ_provenance_only": {
|
||||
"candidate_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"diagnostic_additions": [
|
||||
"generated/applied/pending trace split",
|
||||
"fixed-sequence bitwise audit",
|
||||
"source provenance and final APL state disclosure"
|
||||
],
|
||||
"module_globals_patched": false,
|
||||
"only_dynamics_change": "fixed zero-initialized 0/18-step h32 delay before unchanged end g write",
|
||||
"sealed_source_sha256": {
|
||||
"ae_backend": "03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278",
|
||||
"af_queue": "d72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961",
|
||||
"ag_gpu": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
|
||||
"ag_worker": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291"
|
||||
},
|
||||
"source_diff_sha256": "0584f865885b18e6a36870a7ecfbbc98d7a94274fa5e9e073e7cf97597d78a03"
|
||||
},
|
||||
"mask_sha256": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
|
||||
"nonzero_delta_count": 14232,
|
||||
"overlay_name": "static25",
|
||||
"parent_chain_verified_by_runtime": false,
|
||||
"parent_snapshot_sha256": null,
|
||||
"schema": "phase4an-overlay-install-v1",
|
||||
"state_dtype": "float64",
|
||||
"weights_updated_during_run": false,
|
||||
"zero_rows_untouched": true
|
||||
}
|
||||
+12
@@ -0,0 +1,12 @@
|
||||
{
|
||||
"aj_model_dir": "/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1",
|
||||
"am_overlay_path": "/data/digital-drosophila/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py",
|
||||
"am_overlay_sha256": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4",
|
||||
"base_candidate_path": "/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/protocol/base-candidate.float32-mV.npy",
|
||||
"base_candidate_sha256": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
|
||||
"mask_path": "/data/digital-drosophila/experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-ids.int64.npy",
|
||||
"mask_sha256": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
|
||||
"overlay_name": "static25",
|
||||
"overlay_sha256": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
|
||||
"schema": "phase4an-overlay-v1"
|
||||
}
|
||||
+1
@@ -0,0 +1 @@
|
||||
tick,neuron_idx,attempted,accepted,rejected
|
||||
|
+96
@@ -0,0 +1,96 @@
|
||||
{
|
||||
"ast": {
|
||||
"base": {
|
||||
"added_runtime_callbacks": [
|
||||
"_runtime.install(weights, graph, apl_out_mask, upload, out_dir, source_provenance, device)",
|
||||
"_runtime.finish(ring, apl_ring, apl, steps, out_dir)",
|
||||
"_runtime.timing(steps, pending)",
|
||||
"_runtime.after_tick(tick, v, g, ref, drive, apl_state, h, applied_h)",
|
||||
"_runtime.arrivals(expanded, destination, ref)"
|
||||
],
|
||||
"admission_edit": "0 < steps <= 1000 -> 0 < steps <= spec.max_steps",
|
||||
"aj_source_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"derived_math_ast_sha256": "e46b7d037862b54c0000381ea50df3ba416c7c2c134e3cea78fa90ddf549f710",
|
||||
"derived_module_ast_sha256": "4572043a15a53b3874766b40b4521422567761dbc75db57535ab44b817210429",
|
||||
"math_ast_sha256": "e46b7d037862b54c0000381ea50df3ba416c7c2c134e3cea78fa90ddf549f710",
|
||||
"mathematical_ast_identical": true,
|
||||
"mode": "light",
|
||||
"old_globals_patched": false,
|
||||
"post_loop_terminal_recording": "_runtime.finish(ring, apl_ring, apl, steps, out_dir)",
|
||||
"pre_loop_installation": "_runtime.install(weights, graph, apl_out_mask, upload, out_dir, source_provenance, device)",
|
||||
"reference_entire_tick_loop_identical": false,
|
||||
"removed_diagnostic_statements": [
|
||||
"Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_applied'), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='apl-applied.float32.npy')), Attribute(value=Name(id='np', ctx=Load()), attr='float32', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Constant(value=4064)], ctx=Load())], keywords=[]))",
|
||||
"For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='width', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='drive'), Constant(value=2)], ctx=Load()), Tuple(elts=[Constant(value='state'), Constant(value=2)], ctx=Load()), Tuple(elts=[Constant(value='inhibition'), Constant(value=4064)], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=Constant(value='apl-'), op=Add(), right=Name(id='name', ctx=Load())), op=Add(), right=Constant(value='.float32.npy'))), Attribute(value=Name(id='np', ctx=Load()), attr='float32', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='width', ctx=Load())], ctx=Load())], keywords=[]))], orelse=[])",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='dtype', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='v'), Attribute(value=Name(id='np', ctx=Load()), attr='float64', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='g'), Attribute(value=Name(id='np', ctx=Load()), attr='float64', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='ref'), Attribute(value=Name(id='np', ctx=Load()), attr='int32', ctx=Load())], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=Name(id='name', ctx=Load()), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=BinOp(left=Name(id='name', ctx=Load()), op=Add(), right=Constant(value='-history.')), op=Add(), right=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='dtype', ctx=Load()), args=[Name(id='dtype', ctx=Load())], keywords=[]), attr='name', ctx=Load())), op=Add(), right=Constant(value='.npy'))), Name(id='dtype', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='n', ctx=Load())], ctx=Load())], keywords=[])), Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='pre_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=BinOp(left=BinOp(left=Constant(value='preAPL-'), op=Add(), right=Name(id='name', ctx=Load())), op=Add(), right=Constant(value='.')), op=Add(), right=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='dtype', ctx=Load()), args=[Name(id='dtype', ctx=Load())], keywords=[]), attr='name', ctx=Load())), op=Add(), right=Constant(value='.npy'))), Name(id='dtype', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='n', ctx=Load())], ctx=Load())], keywords=[]))], orelse=[])], orelse=[])",
|
||||
"Assign(targets=[Name(id='expanded_global', ctx=Store())], value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='empty', ctx=Load()), args=[Constant(value=0)], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='int64', ctx=Load()))]))",
|
||||
"Assign(targets=[Name(id='accepted_cpu', ctx=Store())], value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='empty', ctx=Load()), args=[Constant(value=0)], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='uint8', ctx=Load()))]))",
|
||||
"Assign(targets=[Name(id='expanded_global', ctx=Store())], value=Call(func=Attribute(value=Subscript(value=Subscript(value=Name(id='graph', ctx=Load()), slice=Constant(value='edge_id'), ctx=Load()), slice=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='expanded', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), ctx=Load()), attr='copy', ctx=Load()), args=[], keywords=[]))",
|
||||
"Assign(targets=[Name(id='accepted_cpu', ctx=Store())], value=Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Compare(left=Subscript(value=Name(id='ref', ctx=Load()), slice=Call(func=Attribute(value=Name(id='destination', ctx=Load()), attr='long', ctx=Load()), args=[], keywords=[]), ctx=Load()), ops=[Eq()], comparators=[Constant(value=0)]), attr='to', ctx=Load()), args=[Attribute(value=Name(id='torch', ctx=Load()), attr='uint8', ctx=Load())], keywords=[]), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]))",
|
||||
"Assign(targets=[Name(id='queue', ctx=Store())], value=Call(func=Name(id='queue_summary', ctx=Load()), args=[Name(id='tick', ctx=Load()), Name(id='expanded_global', ctx=Load()), Name(id='accepted_cpu', ctx=Load())], keywords=[]))",
|
||||
"Expr(value=Call(func=Attribute(value=Name(id='queue_output', ctx=Load()), attr='write', ctx=Load()), args=[BinOp(left=Call(func=Attribute(value=Name(id='json', ctx=Load()), attr='dumps', ctx=Load()), args=[Name(id='queue', ctx=Load())], keywords=[keyword(arg='allow_nan', value=Constant(value=False))]), op=Add(), right=Constant(value='\\n'))], keywords=[]))",
|
||||
"AugAssign(target=Name(id='due_total', ctx=Store()), op=Add(), value=Subscript(value=Name(id='queue', ctx=Load()), slice=Constant(value='count'), ctx=Load()))",
|
||||
"AugAssign(target=Name(id='accepted_due_total', ctx=Store()), op=Add(), value=Subscript(value=Name(id='queue', ctx=Load()), slice=Constant(value='accepted_count'), ctx=Load()))",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='v'), Name(id='v', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='g'), Name(id='g', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='ref'), Name(id='ref', ctx=Load())], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='pre_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='value', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]))], orelse=[])], orelse=[])",
|
||||
"Assign(targets=[Name(id='apl_cpu', ctx=Store())], value=Dict(keys=[Constant(value='drive'), Constant(value='state'), Constant(value='inhibition'), Constant(value='applied')], values=[Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='drive', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='apl_state', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='h', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='applied_h', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[])]))",
|
||||
"For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Name(id='value', ctx=Load()))], orelse=[])",
|
||||
"Assign(targets=[Name(id='actual', ctx=Store())], value=Dict(keys=[Constant(value='v'), Constant(value='g'), Constant(value='ref')], values=[Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='v', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='g', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='ref', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[])]))",
|
||||
"Assign(targets=[Name(id='finite', ctx=Store())], value=Call(func=Name(id='all', ctx=Load()), args=[GeneratorExp(elt=Call(func=Name(id='bool', ctx=Load()), args=[Call(func=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='isfinite', ctx=Load()), args=[Name(id='value', ctx=Load())], keywords=[]), attr='all', ctx=Load()), args=[], keywords=[])], keywords=[]), generators=[comprehension(target=Name(id='value', ctx=Store()), iter=BinOp(left=Call(func=Name(id='list', ctx=Load()), args=[Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='values', ctx=Load()), args=[], keywords=[])], keywords=[]), op=Add(), right=Call(func=Name(id='list', ctx=Load()), args=[Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='values', ctx=Load()), args=[], keywords=[])], keywords=[])), ifs=[], is_async=0)])], keywords=[]))",
|
||||
"Assign(targets=[Name(id='row', ctx=Store())], value=Dict(keys=[Constant(value='tick'), None], values=[Name(id='tick', ctx=Load()), DictComp(key=BinOp(left=Name(id='name', ctx=Load()), op=Add(), right=Constant(value='_sha256')), value=Call(func=Name(id='raw_hash', ctx=Load()), args=[Name(id='value', ctx=Load()), IfExp(test=Compare(left=Name(id='name', ctx=Load()), ops=[Eq()], comparators=[Constant(value='ref')]), body=Constant(value='<i4'), orelse=Constant(value='<f8'))], keywords=[]), generators=[comprehension(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), ifs=[], is_async=0)])]))",
|
||||
"Expr(value=Call(func=Attribute(value=Name(id='hash_output', ctx=Load()), attr='write', ctx=Load()), args=[BinOp(left=Call(func=Attribute(value=Name(id='json', ctx=Load()), attr='dumps', ctx=Load()), args=[Name(id='row', ctx=Load())], keywords=[keyword(arg='allow_nan', value=Constant(value=False))]), op=Add(), right=Constant(value='\\n'))], keywords=[]))",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=Name(id='name', ctx=Load()), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Name(id='value', ctx=Load()))], orelse=[])], orelse=[])",
|
||||
"If(test=UnaryOp(op=Not(), operand=Name(id='finite', ctx=Load())), body=[With(items=[withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='first-failure-state.npz')), attr='open', ctx=Load()), args=[Constant(value='xb')], keywords=[]), optional_vars=Name(id='target', ctx=Store()))], body=[Expr(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='savez_compressed', ctx=Load()), args=[Name(id='target', ctx=Load())], keywords=[keyword(arg='tick', value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='array', ctx=Load()), args=[Name(id='tick', ctx=Load())], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='int32', ctx=Load()))])), keyword(value=Name(id='actual', ctx=Load())), keyword(value=DictComp(key=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), value=Name(id='value', ctx=Load()), generators=[comprehension(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), ifs=[], is_async=0)]))]))]), Expr(value=Call(func=Name(id='require', ctx=Load()), args=[Constant(value=False), Constant(value='Nonfinite state; first failure saved')], keywords=[]))], orelse=[])"
|
||||
],
|
||||
"replaced_diagnostic_nodes": [
|
||||
"withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='queue.jsonl')), attr='open', ctx=Load()), args=[Constant(value='x')], keywords=[keyword(arg='encoding', value=Constant(value='utf-8')), keyword(arg='buffering', value=Constant(value=1))]), optional_vars=Name(id='queue_output', ctx=Store()))",
|
||||
"withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='tick-state-hashes.jsonl')), attr='open', ctx=Load()), args=[Constant(value='x')], keywords=[keyword(arg='encoding', value=Constant(value='utf-8')), keyword(arg='buffering', value=Constant(value=1))]), optional_vars=Name(id='hash_output', ctx=Store()))",
|
||||
"Assign(targets=[Name(id='timing', ctx=Store())], value=Call(func=Name(id='audit_sequence', ctx=Load()), args=[Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_inhibition'), ctx=Load()), Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_applied'), ctx=Load()), Name(id='pending', ctx=Load()), Name(id='apl_delay', ctx=Load())], keywords=[]))"
|
||||
]
|
||||
},
|
||||
"clock_admission_new": "tick + _continuation.global_offset >= 18",
|
||||
"clock_admission_old": "tick >= 18",
|
||||
"derived_module_ast_sha256": "f6a9a518081089a4be9692178688663cfb39f9d44c92c4abb119620149f54007",
|
||||
"diagnostic_namespace_binding": "audit_sequence checks parent_pending + generated, not an assumed zero-initial queue",
|
||||
"full_AST_rollback_identical": true,
|
||||
"kernels_sorting_and_local_ring_math_unchanged": true,
|
||||
"restore_hook": "_continuation.restore(v, g, ref, counts, ring, apl_ring, apl, upload)"
|
||||
},
|
||||
"complete": true,
|
||||
"finite_audit_sha256": "f11b37717ad3c092a481adcf78f7caffd688650bf4cb56ab644175721e63a9e8",
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||||
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||||
"global_next_tick": 19,
|
||||
"global_tick_offset": 18,
|
||||
"input_sha256": {
|
||||
"/data/digital-drosophila/experiments/phase4af-author-fullgraph/oracle/no_input/coefficients.json": "bde79d95ef0097b827d5faf4d5658eafc009d8e9fcef1fddd645c953823e3f64",
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||||
"/data/digital-drosophila/experiments/phase4ag-author-apl-r2/graphs/full/weights.npy": "462839ffc3feb8f6c278044488082b1c8e410e7f23229d6b5e29d1b7042416a1",
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||||
"/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/overlays/static25.npz": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
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||||
"/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/protocol/base-candidate.float32-mV.npy": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
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||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/runs/static25--chain--light-s01/checkpoint-manifest.json": "e3885149662d9abf9666a76953784b508398a08be963b8165cbbb3548b4e2b13",
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|
||||
"/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/gpu_timing.py": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
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"/data/digital-drosophila/models/male-cns-lif/author-apl-lab-v2/gpu_apl.py": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
|
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|
||||
"/data/digital-drosophila/models/male-cns-lif/author-fullgraph-lab-v1/oracle_full.py": "d72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/author_ext.cpp": "208a937d17bbb041b9bf6b25b89264ee566830b60609e58491b44583d8541f15",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/author_ext.cu": "669f166e18ce9a3f63fc723db8b0a8b74f7fa4757194b1bd65b4cf6008a7787e",
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"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/gpu_backend.py": "03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278",
|
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"/data/digital-drosophila/models/male-cns-lif/olfactory-conditioning-lab-v1/runtime_light.py": "522b8c31ea938890fe15364fccd25ccc5bded54101754909f255532e7ad01aae",
|
||||
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|
||||
},
|
||||
"learning_pass_claimed": false,
|
||||
"mode": "light",
|
||||
"old_globals_patched": false,
|
||||
"overlay_audit_sha256": "03fa596094d386840f2a8e00e59d76eb4dea10b5835a8270e32dce50e7640c38",
|
||||
"parent_checkpoint_manifest_sha256": "e3885149662d9abf9666a76953784b508398a08be963b8165cbbb3548b4e2b13",
|
||||
"schema": "phase4an-continuation-runtime-v1",
|
||||
"source_file": "/data/digital-drosophila/models/male-cns-lif/olfactory-conditioning-lab-v1/runtime_continuation.py",
|
||||
"source_sha256": "0b8e8e0a6a23a079dc62a88355ce355d53b3ae22f6665519a8f6aef2dcfc5aba",
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|
||||
"weights_updated_during_run": false
|
||||
}
|
||||
+17
@@ -0,0 +1,17 @@
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||||
{
|
||||
"sealed_source_sha256": {
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},
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"module_globals_patched": false,
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"only_dynamics_change": "fixed zero-initialized 0/18-step h32 delay before unchanged end g write",
|
||||
"diagnostic_additions": [
|
||||
"generated/applied/pending trace split",
|
||||
"fixed-sequence bitwise audit",
|
||||
"source provenance and final APL state disclosure"
|
||||
]
|
||||
}
|
||||
+199
@@ -0,0 +1,199 @@
|
||||
{
|
||||
"accepted_arriving_edges": 0,
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"accepted_requests": 0,
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"all_finite": true,
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},
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"environment": {
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"CUBLAS_WORKSPACE_CONFIG": null,
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"cuda": "13.0",
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||||
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||||
"cudnn": 92400,
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||||
"cudnn_allow_tf32": true,
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||||
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||||
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|
||||
"deterministic_algorithms": false,
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||||
"device_capability": [
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8,
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9
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],
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|
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"device_name": "NVIDIA GeForce RTX 4090",
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"float32_matmul_precision": "highest",
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"numpy": "2.2.6",
|
||||
"precision_configuration_changed_by_component": false,
|
||||
"torch": "2.14.0+cu130"
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||||
},
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"files_sha256": {
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"n_neurons": 166700,
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"operator_sequence": "state.mul_(decay32); drive=mv(I32,spikes32); state.add_(drive); h=matmul(state,O32)*gain32",
|
||||
"protocol": "phase4ag-apl-v1"
|
||||
},
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|
||||
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||||
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||||
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"final_apl_state_float32": [
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||||
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],
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||||
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1067683394
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||||
],
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||||
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||||
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|
||||
],
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||||
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||||
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||||
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|
||||
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||||
},
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
},
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
"generated/applied/pending trace split",
|
||||
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|
||||
"source provenance and final APL state disclosure"
|
||||
],
|
||||
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|
||||
"only_dynamics_change": "fixed zero-initialized 0/18-step h32 delay before unchanged end g write",
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||||
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||||
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||||
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|
||||
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||||
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||||
}
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||||
+45
@@ -0,0 +1,45 @@
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||||
{
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
},
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||||
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||||
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||||
},
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"ok": true,
|
||||
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|
||||
"protocol": "phase4ag-apl-v1"
|
||||
}
|
||||
+50
@@ -0,0 +1,50 @@
|
||||
{
|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
"brain_tail_advanced": false,
|
||||
"brain_tail_advanced_scope": "no extra brain ticks beyond this explicit segment",
|
||||
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|
||||
"final_apl_state_float32": [
|
||||
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|
||||
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||||
],
|
||||
"final_apl_state_nonzero": true,
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||||
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||||
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||||
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|
||||
],
|
||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
],
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||||
"pending_trace": "apl-pending-tail.float32.npy",
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||||
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||||
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"steps": 481,
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||||
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||||
}
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||||
+27
@@ -0,0 +1,27 @@
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{
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"complete": true,
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||||
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||||
},
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||||
"schema": "phase4an-checkpoint-v1",
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||||
"segment_steps": 481,
|
||||
"state_binding_origin": "checkpoint seal; fresh runtime receipt did not hash state.npz"
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||||
}
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||||
+29
@@ -0,0 +1,29 @@
|
||||
{
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||||
"checkpoint_continuation_verified_by_GPU_comparison": false,
|
||||
"clock_admission_edit": "tick + _continuation.global_offset >= 18",
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||||
"complete": true,
|
||||
"counts_scope": "segment_only_not_lifetime",
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||||
"global_next_tick": 500,
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||||
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||||
"parent_checkpoint_dir": "/data/digital-drosophila/experiments/phase4an-engineering-validation/runs/static25--chain--light-s02",
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||||
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"payload_sha256": {
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||||
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||||
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||||
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||||
+9
@@ -0,0 +1,9 @@
|
||||
{
|
||||
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|
||||
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||||
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||||
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||||
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|
||||
"mode": "light",
|
||||
"scope": "every completed tick; no neuronal or APL tensor mutated by observer"
|
||||
}
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||||
+40
@@ -0,0 +1,40 @@
|
||||
{
|
||||
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||||
"diagnostic_additions": [
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||||
"generated/applied/pending trace split",
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||||
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||||
"source provenance and final APL state disclosure"
|
||||
],
|
||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
+12
@@ -0,0 +1,12 @@
|
||||
{
|
||||
"aj_model_dir": "/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1",
|
||||
"am_overlay_path": "/data/digital-drosophila/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py",
|
||||
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|
||||
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|
||||
"mask_sha256": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
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"overlay_name": "static25",
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|
||||
"schema": "phase4an-overlay-v1"
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}
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||||
+42
@@ -0,0 +1,42 @@
|
||||
tick,neuron_idx,attempted,accepted,rejected
|
||||
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||||
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||||
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|
||||
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||||
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|
||||
|
+96
@@ -0,0 +1,96 @@
|
||||
{
|
||||
"ast": {
|
||||
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|
||||
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|
||||
"_runtime.install(weights, graph, apl_out_mask, upload, out_dir, source_provenance, device)",
|
||||
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|
||||
"_runtime.timing(steps, pending)",
|
||||
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|
||||
"_runtime.arrivals(expanded, destination, ref)"
|
||||
],
|
||||
"admission_edit": "0 < steps <= 1000 -> 0 < steps <= spec.max_steps",
|
||||
"aj_source_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"derived_math_ast_sha256": "e46b7d037862b54c0000381ea50df3ba416c7c2c134e3cea78fa90ddf549f710",
|
||||
"derived_module_ast_sha256": "4572043a15a53b3874766b40b4521422567761dbc75db57535ab44b817210429",
|
||||
"math_ast_sha256": "e46b7d037862b54c0000381ea50df3ba416c7c2c134e3cea78fa90ddf549f710",
|
||||
"mathematical_ast_identical": true,
|
||||
"mode": "light",
|
||||
"old_globals_patched": false,
|
||||
"post_loop_terminal_recording": "_runtime.finish(ring, apl_ring, apl, steps, out_dir)",
|
||||
"pre_loop_installation": "_runtime.install(weights, graph, apl_out_mask, upload, out_dir, source_provenance, device)",
|
||||
"reference_entire_tick_loop_identical": false,
|
||||
"removed_diagnostic_statements": [
|
||||
"Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_applied'), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='apl-applied.float32.npy')), Attribute(value=Name(id='np', ctx=Load()), attr='float32', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Constant(value=4064)], ctx=Load())], keywords=[]))",
|
||||
"For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='width', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='drive'), Constant(value=2)], ctx=Load()), Tuple(elts=[Constant(value='state'), Constant(value=2)], ctx=Load()), Tuple(elts=[Constant(value='inhibition'), Constant(value=4064)], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=Constant(value='apl-'), op=Add(), right=Name(id='name', ctx=Load())), op=Add(), right=Constant(value='.float32.npy'))), Attribute(value=Name(id='np', ctx=Load()), attr='float32', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='width', ctx=Load())], ctx=Load())], keywords=[]))], orelse=[])",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='dtype', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='v'), Attribute(value=Name(id='np', ctx=Load()), attr='float64', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='g'), Attribute(value=Name(id='np', ctx=Load()), attr='float64', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='ref'), Attribute(value=Name(id='np', ctx=Load()), attr='int32', ctx=Load())], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=Name(id='name', ctx=Load()), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=BinOp(left=Name(id='name', ctx=Load()), op=Add(), right=Constant(value='-history.')), op=Add(), right=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='dtype', ctx=Load()), args=[Name(id='dtype', ctx=Load())], keywords=[]), attr='name', ctx=Load())), op=Add(), right=Constant(value='.npy'))), Name(id='dtype', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='n', ctx=Load())], ctx=Load())], keywords=[])), Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='pre_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=BinOp(left=BinOp(left=Constant(value='preAPL-'), op=Add(), right=Name(id='name', ctx=Load())), op=Add(), right=Constant(value='.')), op=Add(), right=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='dtype', ctx=Load()), args=[Name(id='dtype', ctx=Load())], keywords=[]), attr='name', ctx=Load())), op=Add(), right=Constant(value='.npy'))), Name(id='dtype', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='n', ctx=Load())], ctx=Load())], keywords=[]))], orelse=[])], orelse=[])",
|
||||
"Assign(targets=[Name(id='expanded_global', ctx=Store())], value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='empty', ctx=Load()), args=[Constant(value=0)], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='int64', ctx=Load()))]))",
|
||||
"Assign(targets=[Name(id='accepted_cpu', ctx=Store())], value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='empty', ctx=Load()), args=[Constant(value=0)], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='uint8', ctx=Load()))]))",
|
||||
"Assign(targets=[Name(id='expanded_global', ctx=Store())], value=Call(func=Attribute(value=Subscript(value=Subscript(value=Name(id='graph', ctx=Load()), slice=Constant(value='edge_id'), ctx=Load()), slice=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='expanded', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), ctx=Load()), attr='copy', ctx=Load()), args=[], keywords=[]))",
|
||||
"Assign(targets=[Name(id='accepted_cpu', ctx=Store())], value=Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Compare(left=Subscript(value=Name(id='ref', ctx=Load()), slice=Call(func=Attribute(value=Name(id='destination', ctx=Load()), attr='long', ctx=Load()), args=[], keywords=[]), ctx=Load()), ops=[Eq()], comparators=[Constant(value=0)]), attr='to', ctx=Load()), args=[Attribute(value=Name(id='torch', ctx=Load()), attr='uint8', ctx=Load())], keywords=[]), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]))",
|
||||
"Assign(targets=[Name(id='queue', ctx=Store())], value=Call(func=Name(id='queue_summary', ctx=Load()), args=[Name(id='tick', ctx=Load()), Name(id='expanded_global', ctx=Load()), Name(id='accepted_cpu', ctx=Load())], keywords=[]))",
|
||||
"Expr(value=Call(func=Attribute(value=Name(id='queue_output', ctx=Load()), attr='write', ctx=Load()), args=[BinOp(left=Call(func=Attribute(value=Name(id='json', ctx=Load()), attr='dumps', ctx=Load()), args=[Name(id='queue', ctx=Load())], keywords=[keyword(arg='allow_nan', value=Constant(value=False))]), op=Add(), right=Constant(value='\\n'))], keywords=[]))",
|
||||
"AugAssign(target=Name(id='due_total', ctx=Store()), op=Add(), value=Subscript(value=Name(id='queue', ctx=Load()), slice=Constant(value='count'), ctx=Load()))",
|
||||
"AugAssign(target=Name(id='accepted_due_total', ctx=Store()), op=Add(), value=Subscript(value=Name(id='queue', ctx=Load()), slice=Constant(value='accepted_count'), ctx=Load()))",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='v'), Name(id='v', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='g'), Name(id='g', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='ref'), Name(id='ref', ctx=Load())], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='pre_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='value', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]))], orelse=[])], orelse=[])",
|
||||
"Assign(targets=[Name(id='apl_cpu', ctx=Store())], value=Dict(keys=[Constant(value='drive'), Constant(value='state'), Constant(value='inhibition'), Constant(value='applied')], values=[Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='drive', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='apl_state', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='h', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='applied_h', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[])]))",
|
||||
"For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Name(id='value', ctx=Load()))], orelse=[])",
|
||||
"Assign(targets=[Name(id='actual', ctx=Store())], value=Dict(keys=[Constant(value='v'), Constant(value='g'), Constant(value='ref')], values=[Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='v', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='g', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='ref', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[])]))",
|
||||
"Assign(targets=[Name(id='finite', ctx=Store())], value=Call(func=Name(id='all', ctx=Load()), args=[GeneratorExp(elt=Call(func=Name(id='bool', ctx=Load()), args=[Call(func=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='isfinite', ctx=Load()), args=[Name(id='value', ctx=Load())], keywords=[]), attr='all', ctx=Load()), args=[], keywords=[])], keywords=[]), generators=[comprehension(target=Name(id='value', ctx=Store()), iter=BinOp(left=Call(func=Name(id='list', ctx=Load()), args=[Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='values', ctx=Load()), args=[], keywords=[])], keywords=[]), op=Add(), right=Call(func=Name(id='list', ctx=Load()), args=[Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='values', ctx=Load()), args=[], keywords=[])], keywords=[])), ifs=[], is_async=0)])], keywords=[]))",
|
||||
"Assign(targets=[Name(id='row', ctx=Store())], value=Dict(keys=[Constant(value='tick'), None], values=[Name(id='tick', ctx=Load()), DictComp(key=BinOp(left=Name(id='name', ctx=Load()), op=Add(), right=Constant(value='_sha256')), value=Call(func=Name(id='raw_hash', ctx=Load()), args=[Name(id='value', ctx=Load()), IfExp(test=Compare(left=Name(id='name', ctx=Load()), ops=[Eq()], comparators=[Constant(value='ref')]), body=Constant(value='<i4'), orelse=Constant(value='<f8'))], keywords=[]), generators=[comprehension(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), ifs=[], is_async=0)])]))",
|
||||
"Expr(value=Call(func=Attribute(value=Name(id='hash_output', ctx=Load()), attr='write', ctx=Load()), args=[BinOp(left=Call(func=Attribute(value=Name(id='json', ctx=Load()), attr='dumps', ctx=Load()), args=[Name(id='row', ctx=Load())], keywords=[keyword(arg='allow_nan', value=Constant(value=False))]), op=Add(), right=Constant(value='\\n'))], keywords=[]))",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=Name(id='name', ctx=Load()), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Name(id='value', ctx=Load()))], orelse=[])], orelse=[])",
|
||||
"If(test=UnaryOp(op=Not(), operand=Name(id='finite', ctx=Load())), body=[With(items=[withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='first-failure-state.npz')), attr='open', ctx=Load()), args=[Constant(value='xb')], keywords=[]), optional_vars=Name(id='target', ctx=Store()))], body=[Expr(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='savez_compressed', ctx=Load()), args=[Name(id='target', ctx=Load())], keywords=[keyword(arg='tick', value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='array', ctx=Load()), args=[Name(id='tick', ctx=Load())], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='int32', ctx=Load()))])), keyword(value=Name(id='actual', ctx=Load())), keyword(value=DictComp(key=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), value=Name(id='value', ctx=Load()), generators=[comprehension(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), ifs=[], is_async=0)]))]))]), Expr(value=Call(func=Name(id='require', ctx=Load()), args=[Constant(value=False), Constant(value='Nonfinite state; first failure saved')], keywords=[]))], orelse=[])"
|
||||
],
|
||||
"replaced_diagnostic_nodes": [
|
||||
"withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='queue.jsonl')), attr='open', ctx=Load()), args=[Constant(value='x')], keywords=[keyword(arg='encoding', value=Constant(value='utf-8')), keyword(arg='buffering', value=Constant(value=1))]), optional_vars=Name(id='queue_output', ctx=Store()))",
|
||||
"withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='tick-state-hashes.jsonl')), attr='open', ctx=Load()), args=[Constant(value='x')], keywords=[keyword(arg='encoding', value=Constant(value='utf-8')), keyword(arg='buffering', value=Constant(value=1))]), optional_vars=Name(id='hash_output', ctx=Store()))",
|
||||
"Assign(targets=[Name(id='timing', ctx=Store())], value=Call(func=Name(id='audit_sequence', ctx=Load()), args=[Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_inhibition'), ctx=Load()), Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_applied'), ctx=Load()), Name(id='pending', ctx=Load()), Name(id='apl_delay', ctx=Load())], keywords=[]))"
|
||||
]
|
||||
},
|
||||
"clock_admission_new": "tick + _continuation.global_offset >= 18",
|
||||
"clock_admission_old": "tick >= 18",
|
||||
"derived_module_ast_sha256": "f6a9a518081089a4be9692178688663cfb39f9d44c92c4abb119620149f54007",
|
||||
"diagnostic_namespace_binding": "audit_sequence checks parent_pending + generated, not an assumed zero-initial queue",
|
||||
"full_AST_rollback_identical": true,
|
||||
"kernels_sorting_and_local_ring_math_unchanged": true,
|
||||
"restore_hook": "_continuation.restore(v, g, ref, counts, ring, apl_ring, apl, upload)"
|
||||
},
|
||||
"complete": true,
|
||||
"finite_audit_sha256": "78de62547a9d43e37543dedb92ef79687676c58a031269f447d5f1545cf08c9c",
|
||||
"fresh_runtime_sha256": "522b8c31ea938890fe15364fccd25ccc5bded54101754909f255532e7ad01aae",
|
||||
"global_next_tick": 500,
|
||||
"global_tick_offset": 19,
|
||||
"input_sha256": {
|
||||
"/data/digital-drosophila/experiments/phase4af-author-fullgraph/oracle/no_input/coefficients.json": "bde79d95ef0097b827d5faf4d5658eafc009d8e9fcef1fddd645c953823e3f64",
|
||||
"/data/digital-drosophila/experiments/phase4ag-author-apl-r2/graphs/full/weights.npy": "462839ffc3feb8f6c278044488082b1c8e410e7f23229d6b5e29d1b7042416a1",
|
||||
"/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/overlays/static25.npz": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
|
||||
"/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/protocol/base-candidate.float32-mV.npy": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/cases/static25--chain--light-s03/requests.npz": "be049a344735ad19157ea86c6e911ea9042127ace736fe98bcdddf6b3c1425d1",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/cases/static25--chain--light-s03/spec.json": "3256a11c89da8ad99d2504bacf02c7b8ca8dba0679b5697250f3d071e6074d55",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/overlays/static25.json": "b0ee003192fbdfd869f8b23c9bbab0ff99079b7bd2bf1dc33b7afef40785a143",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/runs/static25--chain--light-s02/checkpoint-manifest.json": "ba542fc65ca165c6d1027ce0c056bf8f0b6360b0ad98f4f909240e34419655a8",
|
||||
"/data/digital-drosophila/experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-ids.int64.npy": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
|
||||
"/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/gpu_timing.py": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/timing_queue.py": "54df6d4818e2a0c26e96fb0aaf5d9b71cd964981706da937562d48af79aca14e",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-apl-lab-v2/gpu_apl.py": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-apl-lab-v2/legacy_apl_worker.py": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-fullgraph-lab-v1/oracle_full.py": "d72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/author_ext.cpp": "208a937d17bbb041b9bf6b25b89264ee566830b60609e58491b44583d8541f15",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/author_ext.cu": "669f166e18ce9a3f63fc723db8b0a8b74f7fa4757194b1bd65b4cf6008a7787e",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/gpu_backend.py": "03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278",
|
||||
"/data/digital-drosophila/models/male-cns-lif/olfactory-conditioning-lab-v1/runtime_light.py": "522b8c31ea938890fe15364fccd25ccc5bded54101754909f255532e7ad01aae",
|
||||
"/data/digital-drosophila/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4"
|
||||
},
|
||||
"learning_pass_claimed": false,
|
||||
"mode": "light",
|
||||
"old_globals_patched": false,
|
||||
"overlay_audit_sha256": "03fa596094d386840f2a8e00e59d76eb4dea10b5835a8270e32dce50e7640c38",
|
||||
"parent_checkpoint_manifest_sha256": "ba542fc65ca165c6d1027ce0c056bf8f0b6360b0ad98f4f909240e34419655a8",
|
||||
"schema": "phase4an-continuation-runtime-v1",
|
||||
"source_file": "/data/digital-drosophila/models/male-cns-lif/olfactory-conditioning-lab-v1/runtime_continuation.py",
|
||||
"source_sha256": "0b8e8e0a6a23a079dc62a88355ce355d53b3ae22f6665519a8f6aef2dcfc5aba",
|
||||
"state_sha256": "1ac87260cb29f8358e26f9603dcba748833ae597fb848e28169915b2c2ad75cd",
|
||||
"summary_sha256": "b18796a661d050f5f577750ca9811eb9e34d9dc74cdb7b61d0f45df18cb3e515",
|
||||
"terminal_queues_sha256": "8faf854dcef4d8ff8c66413fd560313dcbbd9df8cdd386fd491521d492f9298b",
|
||||
"weights_updated_during_run": false
|
||||
}
|
||||
+17
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"sealed_source_sha256": {
|
||||
"ag_gpu": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
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||||
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"summary.json": "816ee6c491e3ba9e125b178741aa862679772c1861646f216d4ff3a0d83adda7",
|
||||
"terminal-queues.npz": "279fc5d68f2630b8bb634d01546f529a250a54976ed5f3daef82b8be9d1b683f"
|
||||
},
|
||||
"global_next_tick": 1000,
|
||||
"global_tick_offset": 500,
|
||||
"pre_seal_state_integrity_independently_proven": false,
|
||||
"schema": "phase4an-checkpoint-v1",
|
||||
"segment_steps": 500,
|
||||
"state_binding_origin": "checkpoint seal; fresh runtime receipt did not hash state.npz"
|
||||
}
|
||||
+29
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"checkpoint_continuation_verified_by_GPU_comparison": false,
|
||||
"clock_admission_edit": "tick + _continuation.global_offset >= 18",
|
||||
"complete": true,
|
||||
"counts_scope": "segment_only_not_lifetime",
|
||||
"global_next_tick": 1000,
|
||||
"global_tick_offset": 500,
|
||||
"parent_checkpoint_dir": "/data/digital-drosophila/experiments/phase4an-engineering-validation/runs/static25--chain--light-s03",
|
||||
"parent_checkpoint_manifest_sha256": "7a46fe8914e903760a720caee920070d8dde2e1ecf91190948b3541bbf366505",
|
||||
"payload_sha256": {
|
||||
"apl-component.json": "7a49a1a8fbe42b3965913b8e483ef729ba1f13c211f8da7f10b4b2cd142e6882",
|
||||
"apl-pending-tail.float32.npy": "2dd2e0c79d4ee5299b8c1e8863e6c61b81f3dba08e599011887b1e1621f7c945",
|
||||
"apl-timing-audit.json": "e9988f2d7a7ac7894a576572301bb99a8d1bcc953420c898170dc048a4a66561",
|
||||
"finite-audit.json": "3c654cdf657f9566f5daa467d94e80d225feaf53858cd87a446c4c0893d97662",
|
||||
"overlay-audit.json": "03fa596094d386840f2a8e00e59d76eb4dea10b5835a8270e32dce50e7640c38",
|
||||
"overlay-input.npz": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
|
||||
"overlay-manifest.json": "b0ee003192fbdfd869f8b23c9bbab0ff99079b7bd2bf1dc33b7afef40785a143",
|
||||
"requests.csv": "ea59d983198a1ddb9ca97927561380667ce05d855f8d87dcb4cc89d8b778030f",
|
||||
"runtime-provenance.json": "ce7bddc8556a8d7e2fc60316786290fedf724eab5c149559d2ed95b88dbaba9b",
|
||||
"sealed-gpu-source.diff": "0584f865885b18e6a36870a7ecfbbc98d7a94274fa5e9e073e7cf97597d78a03",
|
||||
"source-audit.json": "d644f0265632f117bba0e045d26fb266765b1d005a89426b6242f3de034be935",
|
||||
"state.npz": "67ecca5b227ec7942c273e2ebecf9d82b4fadd688a4c3fb39e361f6ca1a38c6b",
|
||||
"summary.json": "816ee6c491e3ba9e125b178741aa862679772c1861646f216d4ff3a0d83adda7",
|
||||
"terminal-queues.npz": "279fc5d68f2630b8bb634d01546f529a250a54976ed5f3daef82b8be9d1b683f"
|
||||
},
|
||||
"schema": "phase4an-continuation-receipt-v1",
|
||||
"segment_steps": 500,
|
||||
"weights_updated_during_run": false
|
||||
}
|
||||
+9
@@ -0,0 +1,9 @@
|
||||
{
|
||||
"accepted_arriving_edges": 7959160,
|
||||
"all_finite": true,
|
||||
"arriving_edges": 8654330,
|
||||
"finite_observed_ticks": 500,
|
||||
"first_failure_tick": -1,
|
||||
"mode": "light",
|
||||
"scope": "every completed tick; no neuronal or APL tensor mutated by observer"
|
||||
}
|
||||
+40
@@ -0,0 +1,40 @@
|
||||
{
|
||||
"am_helper_sha256": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4",
|
||||
"apl_fast_edges_zeroed": 5845,
|
||||
"base_candidate_sha256": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
|
||||
"base_weights_raw_sha256": "a8c19cde743bd456bcb2e988d504f805b6943d6ceb97cd241d6e1e472ab5a591",
|
||||
"bridge": "baseSI64 + (delta32 widened to float64) * float64(0.001); nonzero rows only",
|
||||
"candidate_count": 14232,
|
||||
"complete": true,
|
||||
"delta_dtype": "float32",
|
||||
"delta_raw_sha256": "ea03a0ab6b537ea6bcac86191dc79f4eed997ef890885cb695440a0cfc224a67",
|
||||
"delta_units": "mV",
|
||||
"effective_weights_raw_sha256": "a60a2846dd952916097cecd1d3daf74cf5e785818749e0ffd818b3ced1c58fd2",
|
||||
"eligibility_v2_source_sha256": null,
|
||||
"inherited_AJ_provenance_only": {
|
||||
"candidate_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"diagnostic_additions": [
|
||||
"generated/applied/pending trace split",
|
||||
"fixed-sequence bitwise audit",
|
||||
"source provenance and final APL state disclosure"
|
||||
],
|
||||
"module_globals_patched": false,
|
||||
"only_dynamics_change": "fixed zero-initialized 0/18-step h32 delay before unchanged end g write",
|
||||
"sealed_source_sha256": {
|
||||
"ae_backend": "03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278",
|
||||
"af_queue": "d72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961",
|
||||
"ag_gpu": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
|
||||
"ag_worker": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291"
|
||||
},
|
||||
"source_diff_sha256": "0584f865885b18e6a36870a7ecfbbc98d7a94274fa5e9e073e7cf97597d78a03"
|
||||
},
|
||||
"mask_sha256": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
|
||||
"nonzero_delta_count": 14232,
|
||||
"overlay_name": "static25",
|
||||
"parent_chain_verified_by_runtime": false,
|
||||
"parent_snapshot_sha256": null,
|
||||
"schema": "phase4an-overlay-install-v1",
|
||||
"state_dtype": "float64",
|
||||
"weights_updated_during_run": false,
|
||||
"zero_rows_untouched": true
|
||||
}
|
||||
+12
@@ -0,0 +1,12 @@
|
||||
{
|
||||
"aj_model_dir": "/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1",
|
||||
"am_overlay_path": "/data/digital-drosophila/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py",
|
||||
"am_overlay_sha256": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4",
|
||||
"base_candidate_path": "/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/protocol/base-candidate.float32-mV.npy",
|
||||
"base_candidate_sha256": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
|
||||
"mask_path": "/data/digital-drosophila/experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-ids.int64.npy",
|
||||
"mask_sha256": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
|
||||
"overlay_name": "static25",
|
||||
"overlay_sha256": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
|
||||
"schema": "phase4an-overlay-v1"
|
||||
}
|
||||
+66
@@ -0,0 +1,66 @@
|
||||
tick,neuron_idx,attempted,accepted,rejected
|
||||
6,999,1,0,1
|
||||
7,12644,1,1,0
|
||||
13,3161,1,0,1
|
||||
16,522,1,1,0
|
||||
18,12644,1,0,1
|
||||
21,21802,1,1,0
|
||||
28,130472,1,1,0
|
||||
29,360,1,1,0
|
||||
38,7781,1,1,0
|
||||
41,2970,1,1,0
|
||||
47,7781,1,0,1
|
||||
49,131226,1,1,0
|
||||
50,131226,1,0,1
|
||||
51,360,1,1,0
|
||||
96,1514,1,1,0
|
||||
96,9975,1,1,0
|
||||
104,2029,1,1,0
|
||||
105,2347,1,1,0
|
||||
109,1191,1,1,0
|
||||
110,10769,1,0,1
|
||||
113,131226,1,0,1
|
||||
116,522,1,0,1
|
||||
117,522,1,0,1
|
||||
146,2535,1,0,1
|
||||
150,2010,1,1,0
|
||||
154,2231,1,1,0
|
||||
155,522,1,1,0
|
||||
163,360,1,1,0
|
||||
167,10769,1,1,0
|
||||
198,1514,1,1,0
|
||||
204,12644,1,1,0
|
||||
216,1514,1,0,1
|
||||
227,522,1,1,0
|
||||
227,6842,1,1,0
|
||||
245,2010,1,1,0
|
||||
246,360,1,1,0
|
||||
254,3252,1,1,0
|
||||
263,130497,1,1,0
|
||||
264,1890,1,1,0
|
||||
272,3161,1,1,0
|
||||
282,9975,1,1,0
|
||||
294,2029,1,0,1
|
||||
315,130753,1,0,1
|
||||
316,1514,1,0,1
|
||||
316,4505,1,1,0
|
||||
323,14839,1,1,0
|
||||
334,522,1,0,1
|
||||
346,2601,1,1,0
|
||||
355,999,1,0,1
|
||||
359,9370,1,1,0
|
||||
363,522,1,1,0
|
||||
366,360,1,1,0
|
||||
376,6842,1,1,0
|
||||
378,9975,1,1,0
|
||||
398,522,1,1,0
|
||||
406,331,1,1,0
|
||||
406,2010,1,0,1
|
||||
421,5519,1,1,0
|
||||
431,522,1,1,0
|
||||
440,360,1,1,0
|
||||
442,130753,1,1,0
|
||||
471,1890,1,1,0
|
||||
472,2010,1,0,1
|
||||
495,130753,1,1,0
|
||||
496,10769,1,1,0
|
||||
|
+96
@@ -0,0 +1,96 @@
|
||||
{
|
||||
"ast": {
|
||||
"base": {
|
||||
"added_runtime_callbacks": [
|
||||
"_runtime.install(weights, graph, apl_out_mask, upload, out_dir, source_provenance, device)",
|
||||
"_runtime.finish(ring, apl_ring, apl, steps, out_dir)",
|
||||
"_runtime.timing(steps, pending)",
|
||||
"_runtime.after_tick(tick, v, g, ref, drive, apl_state, h, applied_h)",
|
||||
"_runtime.arrivals(expanded, destination, ref)"
|
||||
],
|
||||
"admission_edit": "0 < steps <= 1000 -> 0 < steps <= spec.max_steps",
|
||||
"aj_source_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"derived_math_ast_sha256": "e46b7d037862b54c0000381ea50df3ba416c7c2c134e3cea78fa90ddf549f710",
|
||||
"derived_module_ast_sha256": "4572043a15a53b3874766b40b4521422567761dbc75db57535ab44b817210429",
|
||||
"math_ast_sha256": "e46b7d037862b54c0000381ea50df3ba416c7c2c134e3cea78fa90ddf549f710",
|
||||
"mathematical_ast_identical": true,
|
||||
"mode": "light",
|
||||
"old_globals_patched": false,
|
||||
"post_loop_terminal_recording": "_runtime.finish(ring, apl_ring, apl, steps, out_dir)",
|
||||
"pre_loop_installation": "_runtime.install(weights, graph, apl_out_mask, upload, out_dir, source_provenance, device)",
|
||||
"reference_entire_tick_loop_identical": false,
|
||||
"removed_diagnostic_statements": [
|
||||
"Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_applied'), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='apl-applied.float32.npy')), Attribute(value=Name(id='np', ctx=Load()), attr='float32', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Constant(value=4064)], ctx=Load())], keywords=[]))",
|
||||
"For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='width', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='drive'), Constant(value=2)], ctx=Load()), Tuple(elts=[Constant(value='state'), Constant(value=2)], ctx=Load()), Tuple(elts=[Constant(value='inhibition'), Constant(value=4064)], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=Constant(value='apl-'), op=Add(), right=Name(id='name', ctx=Load())), op=Add(), right=Constant(value='.float32.npy'))), Attribute(value=Name(id='np', ctx=Load()), attr='float32', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='width', ctx=Load())], ctx=Load())], keywords=[]))], orelse=[])",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='dtype', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='v'), Attribute(value=Name(id='np', ctx=Load()), attr='float64', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='g'), Attribute(value=Name(id='np', ctx=Load()), attr='float64', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='ref'), Attribute(value=Name(id='np', ctx=Load()), attr='int32', ctx=Load())], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=Name(id='name', ctx=Load()), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=BinOp(left=Name(id='name', ctx=Load()), op=Add(), right=Constant(value='-history.')), op=Add(), right=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='dtype', ctx=Load()), args=[Name(id='dtype', ctx=Load())], keywords=[]), attr='name', ctx=Load())), op=Add(), right=Constant(value='.npy'))), Name(id='dtype', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='n', ctx=Load())], ctx=Load())], keywords=[])), Assign(targets=[Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='pre_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Store())], value=Call(func=Name(id='new_array', ctx=Load()), args=[BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=BinOp(left=BinOp(left=BinOp(left=BinOp(left=Constant(value='preAPL-'), op=Add(), right=Name(id='name', ctx=Load())), op=Add(), right=Constant(value='.')), op=Add(), right=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='dtype', ctx=Load()), args=[Name(id='dtype', ctx=Load())], keywords=[]), attr='name', ctx=Load())), op=Add(), right=Constant(value='.npy'))), Name(id='dtype', ctx=Load()), Tuple(elts=[Name(id='steps', ctx=Load()), Name(id='n', ctx=Load())], ctx=Load())], keywords=[]))], orelse=[])], orelse=[])",
|
||||
"Assign(targets=[Name(id='expanded_global', ctx=Store())], value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='empty', ctx=Load()), args=[Constant(value=0)], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='int64', ctx=Load()))]))",
|
||||
"Assign(targets=[Name(id='accepted_cpu', ctx=Store())], value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='empty', ctx=Load()), args=[Constant(value=0)], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='uint8', ctx=Load()))]))",
|
||||
"Assign(targets=[Name(id='expanded_global', ctx=Store())], value=Call(func=Attribute(value=Subscript(value=Subscript(value=Name(id='graph', ctx=Load()), slice=Constant(value='edge_id'), ctx=Load()), slice=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='expanded', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), ctx=Load()), attr='copy', ctx=Load()), args=[], keywords=[]))",
|
||||
"Assign(targets=[Name(id='accepted_cpu', ctx=Store())], value=Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Compare(left=Subscript(value=Name(id='ref', ctx=Load()), slice=Call(func=Attribute(value=Name(id='destination', ctx=Load()), attr='long', ctx=Load()), args=[], keywords=[]), ctx=Load()), ops=[Eq()], comparators=[Constant(value=0)]), attr='to', ctx=Load()), args=[Attribute(value=Name(id='torch', ctx=Load()), attr='uint8', ctx=Load())], keywords=[]), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]))",
|
||||
"Assign(targets=[Name(id='queue', ctx=Store())], value=Call(func=Name(id='queue_summary', ctx=Load()), args=[Name(id='tick', ctx=Load()), Name(id='expanded_global', ctx=Load()), Name(id='accepted_cpu', ctx=Load())], keywords=[]))",
|
||||
"Expr(value=Call(func=Attribute(value=Name(id='queue_output', ctx=Load()), attr='write', ctx=Load()), args=[BinOp(left=Call(func=Attribute(value=Name(id='json', ctx=Load()), attr='dumps', ctx=Load()), args=[Name(id='queue', ctx=Load())], keywords=[keyword(arg='allow_nan', value=Constant(value=False))]), op=Add(), right=Constant(value='\\n'))], keywords=[]))",
|
||||
"AugAssign(target=Name(id='due_total', ctx=Store()), op=Add(), value=Subscript(value=Name(id='queue', ctx=Load()), slice=Constant(value='count'), ctx=Load()))",
|
||||
"AugAssign(target=Name(id='accepted_due_total', ctx=Store()), op=Add(), value=Subscript(value=Name(id='queue', ctx=Load()), slice=Constant(value='accepted_count'), ctx=Load()))",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Tuple(elts=[Tuple(elts=[Constant(value='v'), Name(id='v', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='g'), Name(id='g', ctx=Load())], ctx=Load()), Tuple(elts=[Constant(value='ref'), Name(id='ref', ctx=Load())], ctx=Load())], ctx=Load()), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='pre_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='value', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]))], orelse=[])], orelse=[])",
|
||||
"Assign(targets=[Name(id='apl_cpu', ctx=Store())], value=Dict(keys=[Constant(value='drive'), Constant(value='state'), Constant(value='inhibition'), Constant(value='applied')], values=[Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='drive', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='apl_state', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='h', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='applied_h', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[])]))",
|
||||
"For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Name(id='value', ctx=Load()))], orelse=[])",
|
||||
"Assign(targets=[Name(id='actual', ctx=Store())], value=Dict(keys=[Constant(value='v'), Constant(value='g'), Constant(value='ref')], values=[Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='v', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='g', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[]), Call(func=Attribute(value=Call(func=Attribute(value=Call(func=Attribute(value=Name(id='ref', ctx=Load()), attr='cpu', ctx=Load()), args=[], keywords=[]), attr='numpy', ctx=Load()), args=[], keywords=[]), attr='copy', ctx=Load()), args=[], keywords=[])]))",
|
||||
"Assign(targets=[Name(id='finite', ctx=Store())], value=Call(func=Name(id='all', ctx=Load()), args=[GeneratorExp(elt=Call(func=Name(id='bool', ctx=Load()), args=[Call(func=Attribute(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='isfinite', ctx=Load()), args=[Name(id='value', ctx=Load())], keywords=[]), attr='all', ctx=Load()), args=[], keywords=[])], keywords=[]), generators=[comprehension(target=Name(id='value', ctx=Store()), iter=BinOp(left=Call(func=Name(id='list', ctx=Load()), args=[Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='values', ctx=Load()), args=[], keywords=[])], keywords=[]), op=Add(), right=Call(func=Name(id='list', ctx=Load()), args=[Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='values', ctx=Load()), args=[], keywords=[])], keywords=[])), ifs=[], is_async=0)])], keywords=[]))",
|
||||
"Assign(targets=[Name(id='row', ctx=Store())], value=Dict(keys=[Constant(value='tick'), None], values=[Name(id='tick', ctx=Load()), DictComp(key=BinOp(left=Name(id='name', ctx=Load()), op=Add(), right=Constant(value='_sha256')), value=Call(func=Name(id='raw_hash', ctx=Load()), args=[Name(id='value', ctx=Load()), IfExp(test=Compare(left=Name(id='name', ctx=Load()), ops=[Eq()], comparators=[Constant(value='ref')]), body=Constant(value='<i4'), orelse=Constant(value='<f8'))], keywords=[]), generators=[comprehension(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), ifs=[], is_async=0)])]))",
|
||||
"Expr(value=Call(func=Attribute(value=Name(id='hash_output', ctx=Load()), attr='write', ctx=Load()), args=[BinOp(left=Call(func=Attribute(value=Name(id='json', ctx=Load()), attr='dumps', ctx=Load()), args=[Name(id='row', ctx=Load())], keywords=[keyword(arg='allow_nan', value=Constant(value=False))]), op=Add(), right=Constant(value='\\n'))], keywords=[]))",
|
||||
"If(test=Subscript(value=Name(id='spec', ctx=Load()), slice=Constant(value='record_history'), ctx=Load()), body=[For(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='actual', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), body=[Assign(targets=[Subscript(value=Subscript(value=Name(id='maps', ctx=Load()), slice=Name(id='name', ctx=Load()), ctx=Load()), slice=Name(id='tick', ctx=Load()), ctx=Store())], value=Name(id='value', ctx=Load()))], orelse=[])], orelse=[])",
|
||||
"If(test=UnaryOp(op=Not(), operand=Name(id='finite', ctx=Load())), body=[With(items=[withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='first-failure-state.npz')), attr='open', ctx=Load()), args=[Constant(value='xb')], keywords=[]), optional_vars=Name(id='target', ctx=Store()))], body=[Expr(value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='savez_compressed', ctx=Load()), args=[Name(id='target', ctx=Load())], keywords=[keyword(arg='tick', value=Call(func=Attribute(value=Name(id='np', ctx=Load()), attr='array', ctx=Load()), args=[Name(id='tick', ctx=Load())], keywords=[keyword(arg='dtype', value=Attribute(value=Name(id='np', ctx=Load()), attr='int32', ctx=Load()))])), keyword(value=Name(id='actual', ctx=Load())), keyword(value=DictComp(key=BinOp(left=Constant(value='apl_'), op=Add(), right=Name(id='name', ctx=Load())), value=Name(id='value', ctx=Load()), generators=[comprehension(target=Tuple(elts=[Name(id='name', ctx=Store()), Name(id='value', ctx=Store())], ctx=Store()), iter=Call(func=Attribute(value=Name(id='apl_cpu', ctx=Load()), attr='items', ctx=Load()), args=[], keywords=[]), ifs=[], is_async=0)]))]))]), Expr(value=Call(func=Name(id='require', ctx=Load()), args=[Constant(value=False), Constant(value='Nonfinite state; first failure saved')], keywords=[]))], orelse=[])"
|
||||
],
|
||||
"replaced_diagnostic_nodes": [
|
||||
"withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='queue.jsonl')), attr='open', ctx=Load()), args=[Constant(value='x')], keywords=[keyword(arg='encoding', value=Constant(value='utf-8')), keyword(arg='buffering', value=Constant(value=1))]), optional_vars=Name(id='queue_output', ctx=Store()))",
|
||||
"withitem(context_expr=Call(func=Attribute(value=BinOp(left=Name(id='out_dir', ctx=Load()), op=Div(), right=Constant(value='tick-state-hashes.jsonl')), attr='open', ctx=Load()), args=[Constant(value='x')], keywords=[keyword(arg='encoding', value=Constant(value='utf-8')), keyword(arg='buffering', value=Constant(value=1))]), optional_vars=Name(id='hash_output', ctx=Store()))",
|
||||
"Assign(targets=[Name(id='timing', ctx=Store())], value=Call(func=Name(id='audit_sequence', ctx=Load()), args=[Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_inhibition'), ctx=Load()), Subscript(value=Name(id='maps', ctx=Load()), slice=Constant(value='apl_applied'), ctx=Load()), Name(id='pending', ctx=Load()), Name(id='apl_delay', ctx=Load())], keywords=[]))"
|
||||
]
|
||||
},
|
||||
"clock_admission_new": "tick + _continuation.global_offset >= 18",
|
||||
"clock_admission_old": "tick >= 18",
|
||||
"derived_module_ast_sha256": "f6a9a518081089a4be9692178688663cfb39f9d44c92c4abb119620149f54007",
|
||||
"diagnostic_namespace_binding": "audit_sequence checks parent_pending + generated, not an assumed zero-initial queue",
|
||||
"full_AST_rollback_identical": true,
|
||||
"kernels_sorting_and_local_ring_math_unchanged": true,
|
||||
"restore_hook": "_continuation.restore(v, g, ref, counts, ring, apl_ring, apl, upload)"
|
||||
},
|
||||
"complete": true,
|
||||
"finite_audit_sha256": "3c654cdf657f9566f5daa467d94e80d225feaf53858cd87a446c4c0893d97662",
|
||||
"fresh_runtime_sha256": "522b8c31ea938890fe15364fccd25ccc5bded54101754909f255532e7ad01aae",
|
||||
"global_next_tick": 1000,
|
||||
"global_tick_offset": 500,
|
||||
"input_sha256": {
|
||||
"/data/digital-drosophila/experiments/phase4af-author-fullgraph/oracle/no_input/coefficients.json": "bde79d95ef0097b827d5faf4d5658eafc009d8e9fcef1fddd645c953823e3f64",
|
||||
"/data/digital-drosophila/experiments/phase4ag-author-apl-r2/graphs/full/weights.npy": "462839ffc3feb8f6c278044488082b1c8e410e7f23229d6b5e29d1b7042416a1",
|
||||
"/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/overlays/static25.npz": "7805bd2f86de91777bca86c52870607a2e091ed74b901319b896055ad3463f6d",
|
||||
"/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/protocol/base-candidate.float32-mV.npy": "1218d1b328f29a7afefb0ca0b7b6421247f14ad598aa1957a6a7aacbc8cebcae",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/cases/static25--chain--light-s04/requests.npz": "764259eb618a2ee9393b67ec2713cd0c68763a3e55bbd35e261f5c38ea044b0e",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/cases/static25--chain--light-s04/spec.json": "c10065bca4e8cec618c817ed8e86a42b51ef4849804e4369a18586cda34b3205",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/overlays/static25.json": "b0ee003192fbdfd869f8b23c9bbab0ff99079b7bd2bf1dc33b7afef40785a143",
|
||||
"/data/digital-drosophila/experiments/phase4an-engineering-validation/runs/static25--chain--light-s03/checkpoint-manifest.json": "7a46fe8914e903760a720caee920070d8dde2e1ecf91190948b3541bbf366505",
|
||||
"/data/digital-drosophila/experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-ids.int64.npy": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
|
||||
"/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/gpu_timing.py": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/timing_queue.py": "54df6d4818e2a0c26e96fb0aaf5d9b71cd964981706da937562d48af79aca14e",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-apl-lab-v2/gpu_apl.py": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-apl-lab-v2/legacy_apl_worker.py": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-fullgraph-lab-v1/oracle_full.py": "d72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/author_ext.cpp": "208a937d17bbb041b9bf6b25b89264ee566830b60609e58491b44583d8541f15",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/author_ext.cu": "669f166e18ce9a3f63fc723db8b0a8b74f7fa4757194b1bd65b4cf6008a7787e",
|
||||
"/data/digital-drosophila/models/male-cns-lif/author-runtime-lab-v1/gpu_backend.py": "03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278",
|
||||
"/data/digital-drosophila/models/male-cns-lif/olfactory-conditioning-lab-v1/runtime_light.py": "522b8c31ea938890fe15364fccd25ccc5bded54101754909f255532e7ad01aae",
|
||||
"/data/digital-drosophila/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4"
|
||||
},
|
||||
"learning_pass_claimed": false,
|
||||
"mode": "light",
|
||||
"old_globals_patched": false,
|
||||
"overlay_audit_sha256": "03fa596094d386840f2a8e00e59d76eb4dea10b5835a8270e32dce50e7640c38",
|
||||
"parent_checkpoint_manifest_sha256": "7a46fe8914e903760a720caee920070d8dde2e1ecf91190948b3541bbf366505",
|
||||
"schema": "phase4an-continuation-runtime-v1",
|
||||
"source_file": "/data/digital-drosophila/models/male-cns-lif/olfactory-conditioning-lab-v1/runtime_continuation.py",
|
||||
"source_sha256": "0b8e8e0a6a23a079dc62a88355ce355d53b3ae22f6665519a8f6aef2dcfc5aba",
|
||||
"state_sha256": "67ecca5b227ec7942c273e2ebecf9d82b4fadd688a4c3fb39e361f6ca1a38c6b",
|
||||
"summary_sha256": "816ee6c491e3ba9e125b178741aa862679772c1861646f216d4ff3a0d83adda7",
|
||||
"terminal_queues_sha256": "279fc5d68f2630b8bb634d01546f529a250a54976ed5f3daef82b8be9d1b683f",
|
||||
"weights_updated_during_run": false
|
||||
}
|
||||
+17
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"sealed_source_sha256": {
|
||||
"ag_gpu": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a",
|
||||
"ag_worker": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291",
|
||||
"ae_backend": "03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278",
|
||||
"af_queue": "d72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961"
|
||||
},
|
||||
"candidate_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"source_diff_sha256": "0584f865885b18e6a36870a7ecfbbc98d7a94274fa5e9e073e7cf97597d78a03",
|
||||
"module_globals_patched": false,
|
||||
"only_dynamics_change": "fixed zero-initialized 0/18-step h32 delay before unchanged end g write",
|
||||
"diagnostic_additions": [
|
||||
"generated/applied/pending trace split",
|
||||
"fixed-sequence bitwise audit",
|
||||
"source provenance and final APL state disclosure"
|
||||
]
|
||||
}
|
||||
+199
@@ -0,0 +1,199 @@
|
||||
{
|
||||
"accepted_arriving_edges": 7959160,
|
||||
"accepted_requests": 47,
|
||||
"all_finite": true,
|
||||
"apl_component": {
|
||||
"array_sha256": {
|
||||
"apl_globals.npy": "979ef88dff30d41168ce9b377a006ccb3cd034b2dce86d54923ca0f4b87cb6a6",
|
||||
"input_matrix.npy": "528a5f6f5ffe424f323c5a44695db4a7cf32570709832eff2f37f49e85c92c3e",
|
||||
"kc_globals.npy": "9e990d10a63b0f74cd7bbbdc5369082f24d5246487af944ba289bc6bf48d4b75",
|
||||
"output_matrix.npy": "0dcf02cdb7836ab72da32ac47f5682ca33e25f63a8a662a8452d4ea9d46babb9"
|
||||
},
|
||||
"decay_f32_bits": "3f7eb923",
|
||||
"dt_ms": 0.1,
|
||||
"environment": {
|
||||
"CUBLAS_WORKSPACE_CONFIG": null,
|
||||
"cuda": "13.0",
|
||||
"cuda_matmul_allow_tf32": false,
|
||||
"cudnn": 92400,
|
||||
"cudnn_allow_tf32": true,
|
||||
"cudnn_benchmark": false,
|
||||
"cudnn_deterministic": false,
|
||||
"deterministic_algorithms": false,
|
||||
"device_capability": [
|
||||
8,
|
||||
9
|
||||
],
|
||||
"device_index": 0,
|
||||
"device_name": "NVIDIA GeForce RTX 4090",
|
||||
"float32_matmul_precision": "highest",
|
||||
"numpy": "2.2.6",
|
||||
"precision_configuration_changed_by_component": false,
|
||||
"torch": "2.14.0+cu130"
|
||||
},
|
||||
"files_sha256": {
|
||||
"apl_globals.npy": "8388c8795d49cfe5b14fda54f76ef3a35030c62ba87bd8ca6334a2dcdf186f19",
|
||||
"input_matrix.npy": "c4d3df703ea5f1d7402b8255cfa19d9744139ad1048827c23b151d8ba766fec6",
|
||||
"kc_globals.npy": "97a570aafa089f93e642b2bb07e3a3322dabb14c3c7dd431f0c8d2b3b7951fdd",
|
||||
"output_matrix.npy": "e2d0a1ccd740e6777245ebf2efcd88bf5e1da9e47308c63ec8e83d451e134a73"
|
||||
},
|
||||
"gain_f32_bits": "3c23d70a",
|
||||
"h_units": "legacy mV",
|
||||
"initial_state": "float32 zeros",
|
||||
"n_apl": 2,
|
||||
"n_kc": 4064,
|
||||
"n_neurons": 166700,
|
||||
"ok": true,
|
||||
"operator_sequence": "state.mul_(decay32); drive=mv(I32,spikes32); state.add_(drive); h=matmul(state,O32)*gain32",
|
||||
"protocol": "phase4ag-apl-v1"
|
||||
},
|
||||
"apl_delay_steps": 18,
|
||||
"apl_fast_edges_zeroed": 5845,
|
||||
"apl_precision": "float32",
|
||||
"apl_schedule": "end, after threshold/reset and guarded arrivals, unconditional all KC",
|
||||
"apl_si_conversion": "applied h32 -> float64 -> multiply float64 0.001 -> separate float64 subtraction",
|
||||
"apl_timing": {
|
||||
"apl_delay_steps": 18,
|
||||
"applied_generated_rows": 482,
|
||||
"applied_initial_zero_rows": 0,
|
||||
"applied_parent_generated_rows": 18,
|
||||
"applied_parent_pending_rows": 18,
|
||||
"applied_trace": null,
|
||||
"biological_delay_measurement_claimed": false,
|
||||
"brain_tail_advanced": false,
|
||||
"brain_tail_advanced_scope": "no extra brain ticks beyond this explicit segment",
|
||||
"closed_loop_branch_integrals_claimed_equal": false,
|
||||
"final_apl_state_float32": [
|
||||
158.59405517578125,
|
||||
166.26095581054688
|
||||
],
|
||||
"final_apl_state_nonzero": true,
|
||||
"final_apl_state_u32_bits": [
|
||||
1126078484,
|
||||
1126580942
|
||||
],
|
||||
"finite_generated_sequence_only": true,
|
||||
"full_sequence_bitwise_audit_performed": false,
|
||||
"future_apl_decay_or_feedback_generated": false,
|
||||
"generated_rows": 500,
|
||||
"generated_trace": null,
|
||||
"global_next_tick": 1000,
|
||||
"global_tick_offset": 500,
|
||||
"initial_queue_from_parent": true,
|
||||
"initial_queue_raw_sha256": "057f017d2189e3860d857a4927322484523ae97c4ca343cfbe78204c092ebff9",
|
||||
"pending_application_tick_start": 1000,
|
||||
"pending_application_tick_stop_exclusive": 1018,
|
||||
"pending_generated_count": 18,
|
||||
"pending_generated_tick_start": 982,
|
||||
"pending_generated_tick_stop_exclusive": 1000,
|
||||
"pending_initial_zero_prefix": 0,
|
||||
"pending_parent_generated_rows": 0,
|
||||
"pending_queue_drained": false,
|
||||
"pending_raw_sha256": "cecd6ea2ded3d361e0e2dfe0fe70d4302a207e64249500e1177bb9ad99053112",
|
||||
"pending_segment_generated_rows": 18,
|
||||
"pending_shape": [
|
||||
18,
|
||||
4064
|
||||
],
|
||||
"pending_trace": "apl-pending-tail.float32.npy",
|
||||
"scope": "Original D18 ring math retained with restored queue; histories not recorded",
|
||||
"segment_generated_rows_applied": 482,
|
||||
"segment_steps": 500,
|
||||
"steps": 500,
|
||||
"tick_coordinate": "global"
|
||||
},
|
||||
"arriving_edges": 8654330,
|
||||
"build": {
|
||||
"arch_list": "8.9",
|
||||
"cuda_flags": [
|
||||
"-O2",
|
||||
"--fmad=false",
|
||||
"--ftz=false",
|
||||
"--prec-div=true",
|
||||
"--prec-sqrt=true"
|
||||
],
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||||
"sources": {
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||||
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||||
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||||
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||||
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||||
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|
||||
},
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||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
],
|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
},
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||||
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|
||||
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|
||||
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|
||||
"wall_seconds": 3.025183746998664,
|
||||
"within_trial_weight_updates": false
|
||||
}
|
||||
+45
@@ -0,0 +1,45 @@
|
||||
{
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||||
"array_sha256": {
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||||
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||||
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||||
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||||
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||||
},
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||||
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||||
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|
||||
"environment": {
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||||
"CUBLAS_WORKSPACE_CONFIG": null,
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||||
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||||
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|
||||
"cudnn": 92400,
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
"torch": "2.14.0+cu130"
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||||
},
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||||
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||||
},
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||||
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||||
"h_units": "legacy mV",
|
||||
"initial_state": "float32 zeros",
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||||
"n_apl": 2,
|
||||
"n_kc": 4064,
|
||||
"n_neurons": 166700,
|
||||
"ok": true,
|
||||
"operator_sequence": "state.mul_(decay32); drive=mv(I32,spikes32); state.add_(drive); h=matmul(state,O32)*gain32",
|
||||
"protocol": "phase4ag-apl-v1"
|
||||
}
|
||||
+38
@@ -0,0 +1,38 @@
|
||||
{
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||||
"apl_delay_steps": 18,
|
||||
"applied_generated_rows": 0,
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||||
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||||
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||||
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||||
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||||
"final_apl_state_float32": [
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||||
0.0,
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||||
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||||
],
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||||
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||||
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||||
0,
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||||
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||||
],
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||||
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||||
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|
||||
"generated_rows": 5,
|
||||
"generated_trace": "apl-inhibition.float32.npy",
|
||||
"initial_padding_positive_zero": true,
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||||
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||||
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||||
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||||
],
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||||
"pending_trace": "apl-pending-tail.float32.npy",
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||||
"sample_bits_preserved": true,
|
||||
"steps": 5
|
||||
}
|
||||
+32
@@ -0,0 +1,32 @@
|
||||
{
|
||||
"complete": true,
|
||||
"counts_scope": "segment_only",
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||||
"files_sha256": {
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||||
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||||
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||||
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||||
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||||
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||||
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||||
"requests.csv": "d2250de77a7723e0237f53b54038377b5502ccf3a549cc08f3344a1e924b99ac",
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||||
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||||
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||||
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||||
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||||
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||||
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||||
},
|
||||
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|
||||
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|
||||
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|
||||
"schema": "phase4an-checkpoint-v1",
|
||||
"segment_steps": 5,
|
||||
"state_binding_origin": "checkpoint seal; fresh runtime receipt did not hash state.npz"
|
||||
}
|
||||
+7
@@ -0,0 +1,7 @@
|
||||
{
|
||||
"all_finite": true,
|
||||
"finite_observed_ticks": 5,
|
||||
"first_failure_tick": -1,
|
||||
"mode": "reference",
|
||||
"scope": "every completed tick; no neuronal or APL tensor mutated by observer"
|
||||
}
|
||||
+40
@@ -0,0 +1,40 @@
|
||||
{
|
||||
"am_helper_sha256": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4",
|
||||
"apl_fast_edges_zeroed": 5845,
|
||||
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|
||||
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|
||||
"bridge": "baseSI64 + (delta32 widened to float64) * float64(0.001); nonzero rows only",
|
||||
"candidate_count": 14232,
|
||||
"complete": true,
|
||||
"delta_dtype": "float32",
|
||||
"delta_raw_sha256": "ea03a0ab6b537ea6bcac86191dc79f4eed997ef890885cb695440a0cfc224a67",
|
||||
"delta_units": "mV",
|
||||
"effective_weights_raw_sha256": "a60a2846dd952916097cecd1d3daf74cf5e785818749e0ffd818b3ced1c58fd2",
|
||||
"eligibility_v2_source_sha256": null,
|
||||
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|
||||
"candidate_sha256": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
|
||||
"diagnostic_additions": [
|
||||
"generated/applied/pending trace split",
|
||||
"fixed-sequence bitwise audit",
|
||||
"source provenance and final APL state disclosure"
|
||||
],
|
||||
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|
||||
"only_dynamics_change": "fixed zero-initialized 0/18-step h32 delay before unchanged end g write",
|
||||
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|
||||
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|
||||
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||||
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|
||||
"ag_worker": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291"
|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
+12
@@ -0,0 +1,12 @@
|
||||
{
|
||||
"aj_model_dir": "/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1",
|
||||
"am_overlay_path": "/data/digital-drosophila/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py",
|
||||
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|
||||
"base_candidate_path": "/data/digital-drosophila/experiments/phase4am-wholebrain-plastic-interface/protocol/base-candidate.float32-mV.npy",
|
||||
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|
||||
"mask_path": "/data/digital-drosophila/experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-ids.int64.npy",
|
||||
"mask_sha256": "8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b",
|
||||
"overlay_name": "static25",
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||||
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|
||||
"schema": "phase4an-overlay-v1"
|
||||
}
|
||||
+1
@@ -0,0 +1 @@
|
||||
tick,neuron_idx,attempted,accepted,rejected
|
||||
|
+57
@@ -0,0 +1,57 @@
|
||||
{
|
||||
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|
||||
"ast": {
|
||||
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|
||||
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|
||||
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|
||||
],
|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
"original_module_file": "/data/digital-drosophila/models/male-cns-lif/apl-timing-lab-v1/gpu_timing.py",
|
||||
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|
||||
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|
||||
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|
||||
"reference_entire_tick_loop_identical": true,
|
||||
"removed_diagnostic_statements": [],
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@@ -0,0 +1,35 @@
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+7
@@ -0,0 +1,7 @@
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||||
{
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||||
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||||
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||||
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||||
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||||
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@@ -0,0 +1,40 @@
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+12
@@ -0,0 +1,12 @@
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+5
@@ -0,0 +1,5 @@
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tick,neuron_idx,attempted,accepted,rejected
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+7
@@ -0,0 +1,7 @@
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{
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@@ -0,0 +1,40 @@
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@@ -0,0 +1,12 @@
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tick,neuron_idx,attempted,accepted,rejected
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+17
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||||
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||||
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||||
+7
@@ -0,0 +1,7 @@
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{
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||||
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||||
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||||
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||||
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||||
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|
||||
}
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+40
@@ -0,0 +1,40 @@
|
||||
{
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||||
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||||
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||||
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||||
"generated/applied/pending trace split",
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||||
"fixed-sequence bitwise audit",
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||||
"source provenance and final APL state disclosure"
|
||||
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||||
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||||
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||||
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@@ -0,0 +1,12 @@
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+42
@@ -0,0 +1,42 @@
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||||
tick,neuron_idx,attempted,accepted,rejected
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+68
@@ -0,0 +1,68 @@
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{
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+17
@@ -0,0 +1,17 @@
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{
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||||
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||||
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||||
+51
@@ -0,0 +1,51 @@
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|
||||
"queue.jsonl": "8f22feee1d6cadb46efddce7c79b3a3c66ad727825c2165e7efd3a551961fe50",
|
||||
"requests.csv": "ea59d983198a1ddb9ca97927561380667ce05d855f8d87dcb4cc89d8b778030f",
|
||||
"runtime-provenance.json": "6a2b572ab789b98ab351ada603e28d6d81e93c1c00f1ec5593ca8a5044ee92e2",
|
||||
"sealed-gpu-source.diff": "0584f865885b18e6a36870a7ecfbbc98d7a94274fa5e9e073e7cf97597d78a03",
|
||||
"source-audit.json": "d644f0265632f117bba0e045d26fb266765b1d005a89426b6242f3de034be935",
|
||||
"state.npz": "67ecca5b227ec7942c273e2ebecf9d82b4fadd688a4c3fb39e361f6ca1a38c6b",
|
||||
"summary.json": "77a48ed4ed8e189ed1553f92387811f0efc7a832015067a00ce84b37776e6149",
|
||||
"terminal-queues.npz": "279fc5d68f2630b8bb634d01546f529a250a54976ed5f3daef82b8be9d1b683f",
|
||||
"tick-state-hashes.jsonl": "9a056a54dceab68d40ab582a6600db6be668ad21cdd8857685fa82383ddb5107"
|
||||
},
|
||||
"global_next_tick": 1000,
|
||||
"global_tick_offset": 500,
|
||||
"pre_seal_state_integrity_independently_proven": false,
|
||||
"schema": "phase4an-checkpoint-v1",
|
||||
"segment_steps": 500,
|
||||
"state_binding_origin": "checkpoint seal; fresh runtime receipt did not hash state.npz"
|
||||
}
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user