add run default

applied/opt09_srif_softreset/default.summary.json

@@ -0,0 +1,394 @@
+{
+  "key": "opt09_srif_softreset/default",
+  "tag": "default",
+  "script": "opt09_srif_softreset.py",
+  "script_sha256_16": "dd62e980e1fe3fd1",
+  "hf_folder": "applied/opt09_srif_softreset",
+  "priority": 0,
+  "note": "default: srif reset, learned lam/v_reset, fp32 membrane",
+  "phase": 2,
+  "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/default",
+    "--keep-epoch-weights",
+    "1",
+    "--resplit",
+    "block",
+    "--drop-rest",
+    "--bench"
+  ],
+  "flags": [],
+  "epochs_requested": 60,
+  "gpus": 2,
+  "relative_epoch_cost": 1.0,
+  "exit_code": 0,
+  "status": "ok",
+  "duration_s": 349.8,
+  "started_utc": "2026-08-23T04:44:54.932268+00:00",
+  "finished_utc": "2026-08-23T04:50:44.765308+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": 0.8735714285714286
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+    "efficiency": {
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+      "weight_bytes": 4907008,
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+      "train_ms_per_step": 99.64558419997047,
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+      "peak_vram_mb": 2830.266368,
+      "discarded_charge_per_reset": -0.4044694791624079
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+    "optimization_specific": {
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+      "learn_reset": true,
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+      "u_threshold_level": 0,
+      "u_levels_above_threshold": null,
+      "reset_family": {
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+        "num_spiking_sites": 4,
+        "extra_params": 8,
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+          0.8579108715057373
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+          0.42991286516189575,
+          0.912826657295227
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+        "membrane_saturation_frac": null,
+        "batches": 4,
+        "grid_headroom": 0.0,
+        "grid_levels_above_thresh": null
+      },
+      "reset_x_bits_sweep": {
+        "rows": [
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+            "spikes_per_inference": 6160.265625,
+            "membrane_saturation_frac": null,
+            "membrane_memory_reduction_x": 1.0,
+            "acc_drop_vs_fp32": 0.0
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+          {
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+            "acc": 0.8285714285714286,
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+          {
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+            "acc_drop_vs_fp32": 0.27142857142857135
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+          {
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+            "acc": 0.8521428571428571,
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+            "membrane_saturation_frac": null,
+            "membrane_memory_reduction_x": 1.0,
+            "acc_drop_vs_fp32": 0.0
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+            "membrane_memory_reduction_x": 8.0,
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+          {
+            "reset_mode": "soft",
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+            "acc_drop_vs_fp32": 0.3292857142857142
+          },
+          {
+            "reset_mode": "trained",
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+            "target_acc": 0.8514285714285714,
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+            "membrane_saturation_frac": null,
+            "membrane_memory_reduction_x": 1.0,
+            "acc_drop_vs_fp32": 0.0
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+          {
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+            "acc": 0.9042857142857142,
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+            "grid_levels_above_thresh": 3,
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+          {
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+            "u_bits": 2,
+            "acc": 0.46214285714285713,
+            "target_acc": 0.46214285714285713,
+            "grid_headroom": 1.0,
+            "grid_levels_above_thresh": 0,
+            "discarded_charge_per_reset": -0.4779920437351949,
+            "spikes_per_inference": 12277.90625,
+            "membrane_saturation_frac": 0.31902593085106384,
+            "membrane_memory_reduction_x": 16.0,
+            "acc_drop_vs_fp32": 0.3892857142857143
+          }
+        ],
+        "by_mode": {
+          "hard": {
+            "fp32_acc": 0.7942857142857143,
+            "acc_by_bits": {
+              "0": 0.7942857142857143,
+              "4": 0.8285714285714286,
+              "2": 0.5228571428571429
+            }
+          },
+          "soft": {
+            "fp32_acc": 0.8521428571428571,
+            "acc_by_bits": {
+              "0": 0.8521428571428571,
+              "4": 0.8592857142857143,
+              "2": 0.5228571428571429
+            }
+          },
+          "trained": {
+            "fp32_acc": 0.8514285714285714,
+            "acc_by_bits": {
+              "0": 0.8514285714285714,
+              "4": 0.9042857142857142,
+              "2": 0.46214285714285713
+            }
+          }
+        }
+      },
+      "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,
+      "resplit": "block",
+      "test_blocks": "6",
+      "class_weight": false,
+      "epochs": 60,
+      "batch_size": 64,
+      "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,
+      "time_jitter": 2,
+      "label_smoothing": 0.05,
+      "no_batchnorm": false,
+      "binary_input": false,
+      "beta": 1.0,
+      "thresh": 1.0,
+      "window": 0.5,
+      "gain": 1.0,
+      "alpha": 0.9,
+      "readout": "spikecount",
+      "fake_quant": 0,
+      "amp": false,
+      "spike_reg": 0.0,
+      "event_eval": true,
+      "decision_margin": 2.0,
+      "export": false,
+      "seed": 1234,
+      "hub_dir": "/kaggle/working/hub/opt09_srif_softreset/default",
+      "repo_id": "UWU-R-13/SSVEP-SNN",
+      "push_hf": false,
+      "keep_epoch_weights": 1,
+      "no_resume": true,
+      "selftest": false,
+      "reset_mode": "srif",
+      "learn_reset": true,
+      "lam_init": 0.9,
+      "v_reset_init": 0.0,
+      "u_bits": 0,
+      "u_headroom": 2.0,
+      "reset_sweep": "hard,soft,trained",
+      "bits_sweep": "0,4,2",
+      "baseline": false,
+      "bench": true,
+      "bench_warmup": 10,
+      "bench_iters": 50,
+      "bench_train_steps": 20,
+      "sampling_rate": 250.0
+    }
+  },
+  "final_summary": {
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+    "final_test_target_acc": 0.8514285714285714,
+    "final_test_rest_recall": NaN,
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+    "resplit": "block",
+    "class_weight": false,
+    "drop_rest": true,
+    "epochs": 60,
+    "method": "harmonic_matched",
+    "n_in": 2880,
+    "n_classes": 40,
+    "num_bins": 100
+  },
+  "event_driven_summary": {
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+    "anytime_acc": {
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+      "0.5": 0.6928571428571428,
+      "0.75": 0.7964285714285714,
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+    "dt_ms": 50.0,
+    "margin_decision_acc": 0.4035714285714286,
+    "mean_decision_tick": 14.777142857142858,
+    "mean_decision_ms": 738.8571428571429,
+    "dense_forward_test_acc": 0.8514285714285714
+  },
+  "extra_sweep_file_present": true,
+  "selftest": {
+    "mode": "gate",
+    "passed": true
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+  "driver_version": 1,
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+    "sha256": "8a98ec694efb80858eda68b7de3ac75b4d0d071416308c87d101a29f5d7fa79d"
+  }
+}

applied/opt09_srif_softreset/default.zip

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