add run prune_rate_0.2
Browse files
applied/opt06_uticket_prune/prune_rate_0.2.summary.json
ADDED
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@@ -0,0 +1,576 @@
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| 1 |
+
{
|
| 2 |
+
"key": "opt06_uticket_prune/prune_rate_0.2",
|
| 3 |
+
"tag": "prune_rate_0.2",
|
| 4 |
+
"script": "opt06_uticket_prune.py",
|
| 5 |
+
"script_sha256_16": "13957bb36508b8cf",
|
| 6 |
+
"hf_folder": "applied/opt06_uticket_prune",
|
| 7 |
+
"priority": 1,
|
| 8 |
+
"note": "",
|
| 9 |
+
"phase": 4,
|
| 10 |
+
"n_phases": 10,
|
| 11 |
+
"method": "harmonic_matched",
|
| 12 |
+
"command": [
|
| 13 |
+
"/usr/bin/python3",
|
| 14 |
+
"-m",
|
| 15 |
+
"torch.distributed.run",
|
| 16 |
+
"--standalone",
|
| 17 |
+
"--nproc_per_node=2",
|
| 18 |
+
"/kaggle/working/scripts/opt06_uticket_prune.py",
|
| 19 |
+
"--method",
|
| 20 |
+
"harmonic_matched",
|
| 21 |
+
"--data-root",
|
| 22 |
+
"/kaggle/working/data",
|
| 23 |
+
"--epochs",
|
| 24 |
+
"60",
|
| 25 |
+
"--seed",
|
| 26 |
+
"1234",
|
| 27 |
+
"--batch-size",
|
| 28 |
+
"64",
|
| 29 |
+
"--event-eval",
|
| 30 |
+
"--no-resume",
|
| 31 |
+
"--decision-margin",
|
| 32 |
+
"2.0",
|
| 33 |
+
"--hub-dir",
|
| 34 |
+
"/kaggle/working/hub/opt06_uticket_prune/prune_rate_0.2",
|
| 35 |
+
"--keep-epoch-weights",
|
| 36 |
+
"1",
|
| 37 |
+
"--resplit",
|
| 38 |
+
"block",
|
| 39 |
+
"--drop-rest",
|
| 40 |
+
"--bench",
|
| 41 |
+
"--prune-rate",
|
| 42 |
+
"0.2"
|
| 43 |
+
],
|
| 44 |
+
"flags": [
|
| 45 |
+
"--prune-rate",
|
| 46 |
+
"0.2"
|
| 47 |
+
],
|
| 48 |
+
"epochs_requested": 60,
|
| 49 |
+
"gpus": 2,
|
| 50 |
+
"relative_epoch_cost": 1.0,
|
| 51 |
+
"exit_code": 0,
|
| 52 |
+
"status": "ok",
|
| 53 |
+
"duration_s": 328.9,
|
| 54 |
+
"started_utc": "2026-08-23T04:52:48.276413+00:00",
|
| 55 |
+
"finished_utc": "2026-08-23T04:58:17.225020+00:00",
|
| 56 |
+
"optimization_summary": {
|
| 57 |
+
"optimization": "uticket_workload_balanced_pruning",
|
| 58 |
+
"research_section": "3. Spike sparsity & MAC->AC restructuring",
|
| 59 |
+
"reference": "u-Ticket: Workload-Balanced Pruning for Sparse SNNs, arXiv:2302.06746",
|
| 60 |
+
"script": "opt06_uticket_prune.py",
|
| 61 |
+
"baseline_mode": false,
|
| 62 |
+
"method": "harmonic_matched",
|
| 63 |
+
"accuracy": {
|
| 64 |
+
"test_acc": 0.945,
|
| 65 |
+
"test_target_acc": 0.945,
|
| 66 |
+
"best_val_acc": 0.9435714285714286
|
| 67 |
+
},
|
| 68 |
+
"efficiency": {
|
| 69 |
+
"spikes_per_inference": null,
|
| 70 |
+
"syn_ops_per_inference": 1219436.5718344154,
|
| 71 |
+
"dense_macs_per_inference": 122675200.0,
|
| 72 |
+
"event_fraction_of_dense": 0.009940367505693208,
|
| 73 |
+
"syn_ops_per_inference_dense_fanout": 64956449.21347403,
|
| 74 |
+
"weight_sparsity": 0.9065108514190318,
|
| 75 |
+
"effective_ticks": 12.582142857142857,
|
| 76 |
+
"num_ticks": 100,
|
| 77 |
+
"membrane_bytes_per_inference": 451200,
|
| 78 |
+
"weight_bytes": 4907008,
|
| 79 |
+
"input_raster_bytes": null,
|
| 80 |
+
"train_ms_per_step": 98.27910679996421,
|
| 81 |
+
"infer_ms_per_sample": 0.6430302793751252,
|
| 82 |
+
"peak_vram_mb": 2836.18048,
|
| 83 |
+
"weight_bytes_nonzero": 421308
|
| 84 |
+
},
|
| 85 |
+
"optimization_specific": {
|
| 86 |
+
"pruning_enabled": true,
|
| 87 |
+
"balance_enabled": true,
|
| 88 |
+
"rounds": 5,
|
| 89 |
+
"final_sparsity": 0.9141414141414141,
|
| 90 |
+
"nnz_per_layer": {
|
| 91 |
+
"layer0": 7680,
|
| 92 |
+
"layer1": 53760,
|
| 93 |
+
"layer2": 43008
|
| 94 |
+
},
|
| 95 |
+
"pe_stats_per_layer": {
|
| 96 |
+
"layer0": {
|
| 97 |
+
"mean_nnz": 24.0,
|
| 98 |
+
"max_nnz": 24.0,
|
| 99 |
+
"min_nnz": 24.0,
|
| 100 |
+
"total_nnz": 7680,
|
| 101 |
+
"numel": 921600,
|
| 102 |
+
"sparsity": 0.9916666666666667,
|
| 103 |
+
"utilization": 1.0
|
| 104 |
+
},
|
| 105 |
+
"layer1": {
|
| 106 |
+
"mean_nnz": 105.0,
|
| 107 |
+
"max_nnz": 105.0,
|
| 108 |
+
"min_nnz": 105.0,
|
| 109 |
+
"total_nnz": 53760,
|
| 110 |
+
"numel": 163840,
|
| 111 |
+
"sparsity": 0.671875,
|
| 112 |
+
"utilization": 1.0
|
| 113 |
+
},
|
| 114 |
+
"layer2": {
|
| 115 |
+
"mean_nnz": 168.0,
|
| 116 |
+
"max_nnz": 168.0,
|
| 117 |
+
"min_nnz": 168.0,
|
| 118 |
+
"total_nnz": 43008,
|
| 119 |
+
"numel": 131072,
|
| 120 |
+
"sparsity": 0.671875,
|
| 121 |
+
"utilization": 1.0
|
| 122 |
+
}
|
| 123 |
+
},
|
| 124 |
+
"pe_utilization_final": 1.0,
|
| 125 |
+
"pe_utilization_lth": 0.8322065610975112,
|
| 126 |
+
"pe_utilization_uticket": 1.0,
|
| 127 |
+
"latency_proxy_dense": 3712,
|
| 128 |
+
"latency_proxy_final": 297,
|
| 129 |
+
"latency_reduction_frac": 0.919989224137931,
|
| 130 |
+
"rounds_history": [
|
| 131 |
+
{
|
| 132 |
+
"round": 1,
|
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