Invalid JSON:Unexpected token 'N', ..."_recall": NaN,
""... is not valid JSON
| { | |
| "key": "opt09_srif_softreset/reset_hard", | |
| "tag": "reset_hard", | |
| "script": "opt09_srif_softreset.py", | |
| "script_sha256_16": "dd62e980e1fe3fd1", | |
| "hf_folder": "applied/opt09_srif_softreset", | |
| "priority": 1, | |
| "note": "fixed hard reset (no learning)", | |
| "phase": 5, | |
| "n_phases": 10, | |
| "method": "harmonic_matched", | |
| "command": [ | |
| "/usr/bin/python3", | |
| "-m", | |
| "torch.distributed.run", | |
| "--standalone", | |
| "--nproc_per_node=2", | |
| "/kaggle/working/scripts/opt09_srif_softreset.py", | |
| "--method", | |
| "harmonic_matched", | |
| "--data-root", | |
| "/kaggle/working/data", | |
| "--epochs", | |
| "60", | |
| "--seed", | |
| "1234", | |
| "--batch-size", | |
| "64", | |
| "--event-eval", | |
| "--no-resume", | |
| "--decision-margin", | |
| "2.0", | |
| "--hub-dir", | |
| "/kaggle/working/hub/opt09_srif_softreset/reset_hard", | |
| "--keep-epoch-weights", | |
| "1", | |
| "--resplit", | |
| "block", | |
| "--drop-rest", | |
| "--bench", | |
| "--reset-mode", | |
| "hard" | |
| ], | |
| "flags": [ | |
| "--reset-mode", | |
| "hard" | |
| ], | |
| "epochs_requested": 60, | |
| "gpus": 2, | |
| "relative_epoch_cost": 1.0, | |
| "exit_code": 0, | |
| "status": "ok", | |
| "duration_s": 349.5, | |
| "started_utc": "2026-08-23T04:12:44.550991+00:00", | |
| "finished_utc": "2026-08-23T04:18:34.077808+00:00", | |
| "optimization_summary": { | |
| "optimization": "srif_softreset", | |
| "research_section": "4. Membrane-Potential Memory Wall -- Soft Reset Integrate-and-Fire (SRIF), dynamic reset potential", | |
| "reference": "Guo et al., 'Reducing Information Loss for Spiking Neural Networks' (SRIF), ECCV 2022; research.md S4 (stacks with MINT / SpQuant-SNN membrane quantization)", | |
| "script": "opt09_srif_softreset.py", | |
| "baseline_mode": false, | |
| "method": "harmonic_matched", | |
| "accuracy": { | |
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| "best_val_acc": 0.9471428571428572 | |
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| "effective_ticks": 12.062857142857142, | |
| "num_ticks": 100, | |
| "membrane_bytes_per_inference": 451200, | |
| "weight_bytes": 4907008, | |
| "input_raster_bytes": null, | |
| "train_ms_per_step": 100.3461672999947, | |
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| "peak_vram_mb": 2828.251648, | |
| "discarded_charge_per_reset": 0.2713630626355262 | |
| }, | |
| "optimization_specific": { | |
| "reset_mode": "hard", | |
| "learn_reset": false, | |
| "lam_init": 0.9, | |
| "v_reset_init": 0.0, | |
| "u_bits": 0, | |
| "u_scale": 1.0, | |
| "u_headroom_requested": 2.0, | |
| "u_headroom_actual": 0.0, | |
| "u_threshold_level": 0, | |
| "u_levels_above_threshold": null, | |
| "reset_family": { | |
| "reset_mode": "hard", | |
| "learn_reset": false, | |
| "num_spiking_sites": 4, | |
| "extra_params": 0, | |
| "extra_params_frac_of_weights": 0.0, | |
| "extra_flops_per_tick_per_neuron": 0, | |
| "learned_lam_per_layer": [ | |
| 0.0, | |
| 0.0, | |
| 0.0, | |
| 0.0 | |
| ], | |
| "learned_v_reset_per_layer": [ | |
| 0.0, | |
| 0.0, | |
| 0.0, | |
| 0.0 | |
| ] | |
| }, | |
| "reset_stats": { | |
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| "syn_per_inference": 3337387.15625, | |
| "lam_per_site": [ | |
| 0.0, | |
| 0.0, | |
| 0.0, | |
| 0.0 | |
| ], | |
| "v_reset_per_site": [ | |
| 0.0, | |
| 0.0, | |
| 0.0, | |
| 0.0 | |
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| "u_bits": 0, | |
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| "batches": 4, | |
| "grid_headroom": 0.0, | |
| "grid_levels_above_thresh": null | |
| }, | |
| "reset_x_bits_sweep": { | |
| "rows": [ | |
| { | |
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| "spikes_per_inference": 7585.875, | |
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| { | |
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| "grid_headroom": 1.75, | |
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| { | |
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| { | |
| "reset_mode": "soft", | |
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| "grid_headroom": 1.75, | |
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| { | |
| "reset_mode": "soft", | |
| "u_bits": 2, | |
| "acc": 0.895, | |
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| "grid_headroom": 1.0, | |
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| { | |
| "reset_mode": "trained", | |
| "u_bits": 0, | |
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| "target_acc": 0.9407142857142857, | |
| "grid_headroom": 0.0, | |
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| "spikes_per_inference": 7585.875, | |
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| { | |
| "reset_mode": "trained", | |
| "u_bits": 4, | |
| "acc": 0.9585714285714285, | |
| "target_acc": 0.9585714285714285, | |
| "grid_headroom": 1.75, | |
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| "discarded_charge_per_reset": 0.16008443018764404, | |
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| { | |
| "reset_mode": "trained", | |
| "u_bits": 2, | |
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| "by_mode": { | |
| "hard": { | |
| "fp32_acc": 0.9407142857142857, | |
| "acc_by_bits": { | |
| "0": 0.9407142857142857, | |
| "4": 0.9585714285714285, | |
| "2": 0.895 | |
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| "fp32_acc": 0.8385714285714285, | |
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| "fp32_acc": 0.9407142857142857, | |
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| "0": 0.9407142857142857, | |
| "4": 0.9585714285714285, | |
| "2": 0.895 | |
| } | |
| } | |
| } | |
| }, | |
| "mechanism": "V = u - s*((1-lam)*u + lam*thresh) + s*v_r; lam=0,v_r=0 is the baseline hard reset exactly, lam=1,v_r=0 discards zero charge", | |
| "cost": "2 scalars per spiking layer; identical FMA count per tick, so the reset change is free at inference time", | |
| "caveat": "the sweep swaps the reset on ALREADY-TRAINED weights, which under-states what training with each reset would give; and a charge-conserving reset can raise the spike count, so read spikes_per_inference next to the accuracy" | |
| }, | |
| "config": { | |
| "method": "harmonic_matched", | |
| "data_root": "/kaggle/working/data", | |
| "subjects": "", | |
| "blocks": "", | |
| "limit": 0, | |
| "drop_rest": true, | |
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| "lr": 0.002, | |
| "weight_decay": 0.0005, | |
| "grad_clip": 5.0, | |
| "num_bins": 100, | |
| "window_sec": 5.0, | |
| "hidden": "512,256", | |
| "freq_groups": 8, | |
| "dropout": 0.3, | |
| "spike_drop": 0.1, | |
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| "beta": 1.0, | |
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| "window": 0.5, | |
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| "seed": 1234, | |
| "hub_dir": "/kaggle/working/hub/opt09_srif_softreset/reset_hard", | |
| "repo_id": "UWU-R-13/SSVEP-SNN", | |
| "push_hf": false, | |
| "keep_epoch_weights": 1, | |
| "no_resume": true, | |
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| "reset_sweep": "hard,soft,trained", | |
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| "sampling_rate": 250.0 | |
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| "final_summary": { | |
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| "mean_decision_tick": 12.062857142857142, | |
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| "extra_sweep_file_present": true, | |
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